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<p>I saw Vapnik's books about statistical learning... I read the first few chapters. Anyway what surprised me the most was that he thought that the Occam's razor was obsolete.</p> <p>I thought it was related to the situation in which assuming higher dimension improves the fit significantly.</p> <p>Am I understood rig...
g42233
[ 0.042851004749536514, 0.03627978265285492, 0.02080640196800232, -0.04800285026431084, -0.011048181913793087, 0.021938061341643333, 0.05072876065969467, 0.025567105039954185, -0.010630479082465172, 0.005631118547171354, 0.057687439024448395, 0.021099207922816277, 0.08103293180465698, 0.0367...
<p>I have build a $\rho$ function which has the following definition:</p> <p>\begin{equation} \rho(x)= \left\{ \begin{array}{ll} 4- \frac{8}{x^2} \text{if } x \lt-2\\ \frac{x^2}{2} \text{if } x \in [-2,3] \\ 9-\frac{81}{2*x^2} \text{if } x \gt 3 \end{array} \right. \end{equation}</p> <p>The f...
g61581
[ 0.02860633097589016, -0.040902622044086456, -0.018379751592874527, -0.033884961158037186, 0.04610002040863037, -0.02142885886132717, 0.014154594391584396, 0.012769876979291439, -0.040243975818157196, 0.00008599647844675928, -0.04375565052032471, 0.05555172637104988, 0.048257578164339066, -...
<p>I have some problems I need help with. I am running a binary logistic regression.</p> <pre><code>DV: Brand choice (0/1) IV1: Attitude towards product (p&lt;0.05) IV2: Price sensitivity (p&lt;0.05) </code></pre> <p>(Both IV1 and IV2 are measured on the same scale)</p> <p>I have found that “Attitude towards product...
g61582
[ -0.039141640067100525, 0.009017684496939182, 0.00028095307061448693, -0.022841639816761017, 0.026382116600871086, -0.05457492917776108, 0.024264641106128693, -0.00640822434797883, -0.031187690794467926, 0.021591467782855034, -0.026299288496375084, 0.045142412185668945, 0.024040604010224342, ...
<p>I'm working with an artificially generated dataset that is separated by many sharp corners. As an example, imagine an H-shape in a 3D (or higher-dimensional) space. Points within the H are positive, points outside are negative. In my application, many new points will be generated at runtime. I would like to classify...
g18214
[ 0.06378424912691116, -0.024305514991283417, 0.0013938656775280833, -0.004464132245630026, 0.04346297308802605, -0.05587821826338768, 0.01463053748011589, 0.017110763117671013, -0.05500846728682518, -0.0014326346572488546, 0.05501196160912514, -0.010115575045347214, 0.10046815872192383, 0.0...
<p>I have a set of univariate data, where the response variable in a trial is a sequence of time intervals between button presses (my experimental subjs have to press a button intermittently to react to some task conditions). Eventually I have to run a within-subject regression to see if my hypothesized predictors a...
g48067
[ 0.020351603627204895, -0.00945794302970171, -0.01048174686729908, -0.05747396871447563, -0.04101799428462982, -0.0021485972683876753, 0.037952665239572525, -0.003178643761202693, -0.005850987043231726, 0.009958483278751373, 0.015542171895503998, -0.040702756494283676, 0.009733746759593487, ...
<p>I am trying to do multiple imputation using the mice package in R, and the imputation keeps stopping with the following error:</p> <pre><code>Error in mice.impute.logreg(c(1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, : dims [product 145] do not match the length of object [146] In addition: There were 50 or more warn...
g61583
[ 0.032579515129327774, -0.045961420983076096, 0.020840736106038094, -0.054019492119550705, 0.030385008081793785, -0.012523174285888672, 0.08280514925718307, -0.013877801597118378, -0.056371111422777176, -0.007720290217548609, -0.03762102499604225, 0.052325062453746796, 0.006428508087992668, ...
<p>Suppose you have a linear model where the model is significant but some coefficients are not. How does one interpret the model when some coefficients are not significant?</p>
g564
[ -0.035608358681201935, 0.0002864959533326328, 0.020318083465099335, 0.003806151682510972, 0.07847008109092712, 0.0031280932016670704, 0.0033761125523597, 0.04591817408800125, 0.007268169429153204, -0.015008778311312199, -0.06076255068182945, -0.014971833676099777, 0.06539587676525116, -0.0...
<p>From What I understand about classification is that it is used to distinguish unlabeled data points in a collection. So if we have data which is labeled(age, height, weight,...) then we don't need classification, its used only in cases where data might be multidimensional but not classified, i.e without variables(ag...
g48071
[ 0.03482168912887573, -0.022960620000958443, -0.005343143362551928, -0.05257841572165489, -0.016177259385585785, 0.008962240070104599, -0.0036237197928130627, -0.02037716843187809, -0.06699448078870773, -0.04940512031316757, 0.021944358944892883, 0.03434468060731888, 0.0725511759519577, 0.0...
<p>I have a result from a study in a research paper which gives a mean/SD for 2 time points (pre &amp; post treatment), and a p-value based on a paired-samples t-test. What I want to calculate is the SD of the change from pre to post. Is there any way I can back-calculate this using the p-value and mean/SD for each t...
g38004
[ -0.022883962839841843, 0.013384198769927025, -0.014629220589995384, -0.05031317099928856, -0.054693203419446945, -0.06618499755859375, -0.004438008181750774, -0.008188795298337936, -0.047548629343509674, 0.05091935023665428, -0.011533941142261028, 0.07478012144565582, 0.06637272238731384, ...
<p>Cross-correlation can be used to measure a 'lag' (or shift or offset) between two data sets (e.g., data streams). Is there a standard way to measure the errors in the 'lag'? Or better yet, is there a <em>good</em> way to measure those errors?</p> <p>(related: <a href="http://stats.stackexchange.com/questions/2815...
g48881
[ 0.009719927795231342, -0.047813836485147476, -0.005599380936473608, -0.053911931812763214, 0.015929415822029114, 0.05149636045098305, 0.006991707254201174, 0.0148092582821846, -0.04590381309390068, 0.004853961989283562, 0.06724812090396881, 0.0556490533053875, 0.024452002719044685, -0.0212...
<p>I am working on an analysis using exploratory factor analysis (EFA) with the common factor model. This question concerns a methodological issue. Any insights from someone who knows about EFA would be appreciated.</p> <p>We measured the wellbeing of people using a <strong>15 question</strong> survey. The same quest...
g18222
[ 0.023264307528734207, 0.0061035980470478535, 0.01828717440366745, -0.05427100509405136, 0.03381069749593735, 0.041748661547899246, 0.04574623703956604, 0.013904305174946785, -0.0037833619862794876, 0.0260836910456419, 0.03002200648188591, -0.05902617797255516, 0.02721278741955757, 0.017051...
<p>I have used the least mean square (LMS) algorithm to estimate a signal in the presence of high chaotic and random noise. MSE values in db at each SNR for the coefficients is positive even though I converted to Db scale. What is the reason that LMS may not perform?</p> <p>For an MA(4) model, estimating the coefficie...
g61584
[ -0.007091382518410683, -0.05567402392625809, 0.0008843843243084848, -0.0236665029078722, 0.07181712985038757, 0.015296947211027145, 0.019602887332439423, 0.024371691048145294, -0.01351811271160841, 0.0003823083534371108, -0.03315557539463043, 0.043945763260126114, 0.05567432567477226, 0.08...
<p>I would like to know the effect of an external factor on the number of visits on a website during a period of 4 weeks (only search visits from Google). For this, I measured the number of visits every day through Google research. For example I have:</p> <pre><code> Date Visits 01/01/2014 456 02/01/2014 42...
g61585
[ -0.022688576951622963, 0.04571087658405304, -0.0044168648310005665, -0.03717353567481041, -0.0618167482316494, -0.03544091433286667, 0.07741604745388031, -0.015140672214329243, 0.008161747828125954, 0.004874660167843103, 0.02716861665248871, 0.04300949349999428, 0.03597591444849968, -0.000...
<p>I was working on an assignment. The data set was really simple, only consisting one independent variable $y$ and dependent variable $x$. Someone suggested me plot a histogram of $y$ before running simple linear regression. He told me that by plotting frequency at y-axis and value of $y$ on x-axis, and then examining...
g18224
[ 0.01841902919113636, 0.0036862269043922424, -0.00922818761318922, -0.043644651770591736, -0.03953313082456589, -0.0330115370452404, 0.03540961071848869, 0.0016841910546645522, -0.04071836546063423, -0.05726175755262375, 0.02483001910150051, 0.04851590096950531, 0.021589195355772972, 0.0203...
<p>if a stationary time series verifies that each variable depends only on the variable before it, and the joint p.d.f. of xi and xi-1 is f(xi-1,xi), which is the joint p.d.f. of xi,xi+1,xi+2, and of xi,xi+1,xi+2,xi+3?</p>
g61586
[ 0.041275132447481155, -0.03327377513051033, 0.022449322044849396, 0.0024025444872677326, -0.033143311738967896, -0.02735760807991028, 0.03408367931842804, -0.03794432058930397, -0.044849976897239685, -0.023620791733264923, -0.022987110540270805, 0.010546182282269001, -0.01940576359629631, ...
<p>Given an ordered i.i.d sample $X_{(1)}, \dots, X_{(n)}$ from a continuous distribution $F(x)$. How can it be shown that:</p> <p>(1) $\text{Pr}(X_{(k)} \leq x) = \text{P}r(N(x) \geq k)$</p> <p>where $N(x)$ is the number of sample values less than $x$; furthermore, $N(x) \sim \text{Bin}(n, F(x))$</p> <p>and</p> <p...
g49081
[ -0.008440276607871056, -0.027290070429444313, -0.03571123257279396, -0.0337621308863163, 0.028508901596069336, -0.04166034236550331, -0.015118054114282131, -0.005083097144961357, -0.03946525976061821, -0.029442140832543373, -0.02267291210591793, 0.037719715386629105, 0.013135943561792374, ...
<p><strong>BACKGROUND</strong></p> <p>I have data in which the dependent variable is binary with a highly-skewed distribution: &lt;1% records are 1 (doers), >99% records are 0 (non-doers). I'm using logistic regression to predict the <strong>probability</strong> that new records are doers.</p> <p>To handle this rare-...
g61587
[ -0.06428340822458267, -0.04687478765845299, 0.007485658396035433, 0.005421128123998642, 0.03433898463845253, -0.01252145878970623, -0.01828903891146183, 0.0686284601688385, -0.03926713019609451, -0.018967054784297943, -0.015813080593943596, 0.028345927596092224, 0.04373203590512276, 0.0564...
<p>Self-learning statistics by fiddling around with some modeling. Having trouble finding distributions for this data however.</p> <ul> <li>Defined for $x &gt;0$</li> <li>$P(0) &gt; 0$</li> <li>$P(X) \to 0$ as $X \to \infty$, (very quicky)</li> <li>One hump</li> </ul> <p>I haven't found any distributions that fit the...
g61588
[ 0.02179158478975296, 0.0018510631052777171, -0.012520517222583294, -0.07612829655408859, -0.013216342777013779, -0.030575482174754143, -0.019361529499292374, -0.01016640942543745, 0.020048249512910843, -0.009167490527033806, -0.0008298034081235528, 0.0243042204529047, 0.07988815754652023, ...
<p>I did a stepwise regrssion analysis to predict energy expenditure using the variables, height, weight, age, gender and energy intake. The final model contains the variables gender and weight. Now does this final model take into account gender by weight interaction? Or do I have to construct a new equation from this ...
g61589
[ 0.008525402285158634, 0.011865133419632912, 0.0026109605096280575, 0.02438114583492279, -0.006482323165982962, -0.010109438560903072, 0.011814449913799763, 0.013437767513096333, -0.09987878799438477, -0.011043902486562729, -0.04234331101179123, -0.02110280841588974, 0.03892592713236809, 0....
<p>I am looking for an R-implementation of the Lempel-Ziv data compression algorithm, to estimate the <em>source</em> entropy of a time-series consisting of a sequence of symbols.</p> <p>Rather than simply measuring the entropy of the (time-aggregated) symbol-frequency distribution, the Lempel-Ziv algorithm can be use...
g18230
[ -0.05794038251042366, -0.026851804926991463, -0.0008728503598831594, -0.08451970666646957, -0.04729561135172844, -0.06958990544080734, 0.0039213960990309715, 0.004265616647899151, -0.0516836941242218, 0.004523479845374823, -0.04137280955910683, 0.056388258934020996, 0.03453243151307106, 0....
<p>I have a set of user data and I want to build some kind of metric to evaluate the probability of the user being a sybil (a "fake" account).</p> <p><strong>But</strong> I have a very limited set of users who are sybils with 100% certainty.</p> <p>How do I use machine learning here?</p> <p>Also, as for now, I've bu...
g61590
[ -0.015354972332715988, 0.011445078998804092, -0.008646354079246521, -0.02900250069797039, -0.021110761910676956, 0.030160168185830116, -0.014348690398037434, 0.10840857028961182, -0.04596588388085365, -0.01938965916633606, -0.006764159072190523, 0.00591819453984499, 0.11383281648159027, -0...
<p>In particular, I am wondering why we have this concept Multiple R (which I can understand as the correlation between observed and predicted scores in multiple regression), and then a separate concept R-squared which is just the square or R. </p> <p>I've been informed that R-squared is the percentage variation expla...
g18232
[ 0.03829069435596466, -0.0037404184695333242, -0.0007063876837491989, 0.03982112556695938, 0.002787715522572398, -0.023472262546420097, 0.057223472744226456, 0.02510872855782509, 0.013969764113426208, -0.07481186836957932, -0.0021321913227438927, 0.0005122889415360987, 0.05245225876569748, ...
<p>I am trying to analyze a data set in which the response variable is a proportion that can range from 0-1 (inclusive). This response was measured from the same individuals under four different experimental conditions. I am interested in determining the effect of these conditions on the response. I have read up on so...
g61591
[ 0.00782790221273899, -0.05058463290333748, -0.011512847617268562, -0.05481376126408577, -0.013100284151732922, -0.015808045864105225, 0.05934540182352066, 0.030130939558148384, -0.0586431622505188, 0.0021705401595681906, -0.03234928101301193, -0.0008321604109369218, 0.00650210864841938, 0....
<p>I have two different formulations of the Lasso regression for the same problem. For each formulation, I selected the best model based on cross validation error. But Now, I want to compare two models that come from two different formulations of Lasso regression. The cross validation error of theses two models are cl...
g61592
[ 0.07976049184799194, -0.041850265115499496, 0.030573010444641113, -0.006673937663435936, 0.04012765735387802, 0.034724365919828415, 0.013701102696359158, 0.019777486100792885, -0.03801456093788147, 0.02435309812426567, 0.01692396029829979, 0.020139891654253006, 0.07516561448574066, -0.0111...
<p>I've been asked to undertake a power calculation because the regular statistician is not available. </p> <p>I am calculating power for a trial where the endpoint will be a percentage of patients not achieving remission at a given timepoint after receiving a drug or placebo. The ratio of case:controls is 1:1</p> <p...
g18235
[ 0.016557149589061737, -0.04645954817533493, -0.02205832675099373, -0.0793142020702362, 0.026813818141818047, -0.05451423302292824, 0.03408459946513176, -0.00020955641230102628, -0.05449710786342621, -0.0030950033105909824, 0.004458279814571142, 0.021133098751306534, 0.05820142850279808, -0...
<p>Is there an expression for $\text{cov}(a,bc)$ in terms of $a$, $b$ and $c$ separately. More concretely, if $\text{cov}(a,b)=0$ and $\text{cov}(a,c)&gt;0$, is $\text{cov}(a,bc)=0$?</p>
g61593
[ 0.03470367565751076, -0.03531969338655472, 0.001725265639834106, -0.04434167221188545, 0.04951797053217888, -0.036591313779354095, 0.03333769366145134, -0.011406708508729935, -0.004528586287051439, -0.01566634140908718, -0.05582646653056145, 0.022090831771492958, -0.05424121022224426, 0.05...
<p>I use mostly "Gaussian distribution" in my book, but someone just suggested I switch to "normal distribution". Any consensus on which term to use for beginners? </p> <p>Of course the <a href="http://stats.stackexchange.com/questions/55962/what-is-the-difference-between-a-normal-and-a-gaussian-distribution">two term...
g18236
[ 0.05332497879862785, -0.030164804309606552, -0.0010111192241311073, -0.0497005395591259, -0.05039744824171066, 0.020058169960975647, 0.0070233577862381935, 0.0017110974295064807, 0.01543984841555357, -0.005723152309656143, 0.07103535532951355, -0.010921921581029892, 0.05816157907247543, -0...
<p>I have fit a logistic regression model with original y and standardized x variables. Slope coefficients can be easily converted back to their original scale by $\beta^*_j/\sigma_{x_j}$ where $\beta^*_j$ is the output from the fitted model. However, I am not sure how to get the original intercept estimate from the ou...
g9873
[ 0.025532763451337814, -0.088388592004776, 0.0034330892376601696, -0.03284021094441414, 0.01882859878242016, -0.07633320987224579, 0.005234747193753719, 0.03412513807415962, -0.05892818048596382, 0.011704282835125923, -0.04074199125170708, 0.05858799070119858, 0.027484409511089325, -0.01307...
<p>In the usual VIF calculation for a linear regression, each independent/explanatory variable $X_j$ is treated as the dependent variable in an ordinary least squares regression. i.e.</p> <p>$$ X_j = \beta_0 + \sum_{i=1, i \neq j}^n \beta_i X_i $$</p> <p>The $R^2$ values are stored for each of the $n$ regressions and...
g18238
[ 0.013553799130022526, -0.04428653046488762, -0.024297740310430527, -0.030937574803829193, -0.002528758952394128, -0.04014799743890762, 0.031015804037451744, 0.006575652863830328, -0.02687867544591427, -0.018574818968772888, -0.06212475523352623, 0.02314237877726555, 0.013814187608659267, 0...
<p>Let us say I have data set of distinct $x_i$. A Gaussian is fitted to it with maximum likelihood, obtaining some $\mu$ and some $\sigma^2$. I will also obtain a likelihood $\mathcal{L}$.</p> <p>Now, I copy the data set where I set $\tilde{x}_i = 2 x_i$. I estimate another Gaussian, obtaining $\tilde{\mu}, \tilde{\s...
g18240
[ -0.039572734385728836, -0.050008613616228104, 0.005715842358767986, -0.04033593833446503, -0.010700713843107224, 0.012042349204421043, 0.0006044834735803306, 0.006545925512909889, -0.017211029306054115, 0.008688581176102161, 0.009481205604970455, 0.030254533514380455, 0.03237680345773697, ...
<p>I got the following result of a ANOVA analysis of five independent variables with 5,8,2,2,6 levels and 5 replications for each combination:</p> <pre><code> Df Sum Sq Mean Sq F value Pr(&gt;F) IV1 4 129805 32451 243.35 &lt;2e-16 *** IV2 7 67227 9604 72.0...
g61594
[ -0.010768815875053406, -0.02054006978869438, -0.0045964340679347515, 0.0009775420185178518, 0.000714895490091294, -0.029536694288253784, 0.0746200829744339, 0.026311330497264862, 0.005922623910009861, 0.01940089464187622, -0.06667228788137436, 0.03979909420013428, 0.027685662731528282, 0.0...
<p>So, I have a huge number of amplitude modulated waves and I am attempting to determine which modulation parameter modulates each time series. To do this, I folded each time series over at the repetition frequency of the modulator wave, to produce an averaged modulation index for each time series.</p> <p><img src="h...
g48086
[ -0.0362662747502327, -0.012202940881252289, 0.00019996310584247112, -0.051118966192007065, -0.01218342687934637, -0.09392700344324112, 0.02788570150732994, -0.009283295832574368, -0.005912698805332184, 0.04051223024725914, -0.04475381597876549, 0.031962938606739044, 0.07832582294940948, 0....
<p>I tried to model $\text{Saving} = a + b_1*\text{Income} + b_2*\text{Wealth}$ but found that $\text{Income}$ and $\text{Wealth}$ were highly correlated. I applied PCA to get a new variable $\text{New}$ based on the first component. Next, I modeled $\text{Saving} = c + b_3*\text{New}$. I then had two questions as foll...
g18242
[ 0.006881973706185818, -0.049622781574726105, 0.0009469161741435528, -0.05977635085582733, 0.021591464057564735, -0.0037690913304686546, 0.0609467476606369, -0.01703718490898609, -0.058511000126600266, 0.006812740117311478, -0.009759682230651379, 0.017451273277401924, 0.03277437761425972, 0...
<p>I have the variables $Y$, $x_{m1}$, $x_{m2}$, $\ldots$, $x_{mn}$, $x_{p1}$, $x_{p2}$, $\ldots$, $x_{pn}$, $x_{q1}$, $x_{q2}$, $\ldots$, $x_{qn}$. </p> <p>$Y$ is the class label (0 or 1). $x_{mj}$, $x_{pj}$ and $x_{qj}$ can be regarded as the same kind of property, but different combination of three properties can ...
g61595
[ -0.03503865748643875, -0.03636232018470764, 0.008367609232664108, -0.0025759954005479813, 0.0267837792634964, -0.033278752118349075, -0.006627135910093784, -0.04075271636247635, -0.005345114041119814, -0.018381664529442787, 0.012794770300388336, 0.06703213602304459, 0.03222886472940445, 0....
<p>I have carried out my pilot study on language learning motivation using a 6 point Likert scale but from 0 (strongly disagree) to 5 (very much agree). I noticed a colleague in his survey used 1 to 6. Will my computed variables (sum and mean) be the same as if I had used 1 to 6? Is it normally recommended to not use a...
g61596
[ -0.01657472923398018, -0.03253840282559395, 0.00508773373439908, -0.049158625304698944, -0.032189659774303436, -0.018099967390298843, -0.02695377729833126, 0.034311167895793915, -0.009252816438674927, -0.027262764051556587, 0.024544278159737587, 0.03286755084991455, 0.03969607874751091, 0....
<p>Here is a rather involved question. It can be summed up as follows: <strong>how can I test the effect of a potential mediating variable, independent of the effect of a possible covariate with which it is confounded?</strong></p> <p>Here is a simplified description of my study and then the analysis problem I'm facin...
g18245
[ -0.00777869438752532, -0.022675668820738792, 0.027301503345370293, -0.041240185499191284, 0.040664996951818466, 0.023404886946082115, 0.028290875256061554, 0.02878298982977867, 0.014672008343040943, 0.024930093437433243, 0.011179077439010143, 0.031603120267391205, 0.015903938561677933, 0.0...
<p>I saw a talk that mentioned this theorem. I am now trying to find details of the theorem, but I'm not having any luck. I hope that if I can describe roughly what the theorem said, someone can recognise it and point me to some literature.</p> <p>So the theorem basically said something like the expected self-informat...
g31809
[ 0.02964308299124241, 0.031183384358882904, -0.009239081293344498, -0.0424015037715435, -0.04162019491195679, -0.025812199339270592, 0.0019457103917375207, -0.0026689786463975906, -0.03594416379928589, -0.018647681921720505, -0.045267947018146515, 0.05054352059960365, -0.029721340164542198, ...
<p>When you read about perceptron variants at Wikipedia there is explained an algorithm: <a href="http://en.wikipedia.org/wiki/Perceptron#Variants" rel="nofollow">Pocket Algorithm</a> It is said that:</p> <blockquote> <p>solves the stability problem of perceptron learning by keeping the best solution seen so far "in...
g61597
[ 0.0012444037711247802, 0.028540626168251038, 0.008972158655524254, -0.061228569597005844, 0.047376442700624466, -0.08849523216485977, 0.028612861409783363, 0.017297878861427307, -0.05389169231057167, 0.0014116090023890138, -0.04471072554588318, 0.03908305615186691, 0.02294459566473961, 0.0...
<p>I have a theoretical question about regression models. Let's say I measured multiple responses from $n$ subjects and these responses are correlated with each other. For example, let's say I measured heart rate and body temperature from $n$ individuals with the following categorical factors: sex (male/female) and ag...
g18249
[ 0.00670445803552866, -0.04095190390944481, -0.002274269936606288, 0.006088428199291229, 0.0429563894867897, -0.01582331955432892, 0.025634819641709328, -0.0012927551288157701, -0.03066101297736168, -0.025136496871709824, -0.011098457500338554, 0.029422719031572342, -0.010187672451138496, 0...
<p>How do decision tree based ensembles like random forest deal with categorical ("factor") predictor variables? My guess would be that indicator variables are created for each factor via a one-hot-encoding (aka 1 of K coding) but I wonder if that is true? The reason I doubt it is that it seems that such a coding for a...
g49622
[ -0.04684819281101227, -0.03217030689120293, 0.004767854232341051, -0.003815805772319436, 0.02141129970550537, -0.05057521536946297, -0.016875488683581352, 0.0532592311501503, -0.015078398399055004, 0.009314329363405704, -0.022842617705464363, -0.0024853392969816923, 0.07460103183984756, 0....
<p>I have following 3 two dimensional datasets.</p> <p>Case 1: (Two continuous random variables)</p> <p>A = 1.3, 2.7, 3.9, 4.7, 5.6, 6.3, 7.5, 8.9, 9.1, 10</p> <p>B = 7.4, 15.3, 24.4, 25.4, 29.6, 32.1, 34.5, 35.7, 27.8, 39.1</p> <p>Case 2: (One discrete and one continuous random variable)</p> <p>C = 1, 1, 1, 1, 1,...
g61598
[ 0.03159598633646965, -0.08502916246652603, -0.0009240360232070088, -0.027006156742572784, 0.0009439450805075467, 0.012868456542491913, -0.0207504965364933, 0.026913626119494438, -0.06107137352228165, 0.05838252604007721, -0.0007501128129661083, -0.002251093043014407, 0.010973521508276463, ...
<p>I read an article entitled "Permutation Tests for Studying Classifier Performance" which explains how to use "permutation-based p-value" to test the performance of a classifier. I can not understand how to calculate the p-value. The article reports this formula:</p> <pre><code> p = (|{D′ ∈ D: e(f,D′) ≤ e(f,D)}|+1)/...
g61599
[ -0.020618319511413574, -0.015713253989815712, -0.012635570019483566, -0.036056894809007645, 0.003244363470003009, -0.03092353604733944, 0.040929634124040604, 0.038251589983701706, -0.058813270181417465, -0.03782004863023758, -0.0005406358977779746, 0.06333395093679428, 0.1054072454571724, ...
<p>I have a classifier. when I shuffle input data (a few times), make training/test data and run classifier, the accuracy is high but when I use cross validation in sklearn it drops by 15% (both recall and precision). Wondering what is the problem? and how to fix it?</p>
g61600
[ -0.019368082284927368, -0.035907503217458725, 0.006879896856844425, -0.011547846719622612, 0.048860322684049606, 0.024092281237244606, 0.060506775975227356, 0.057730771601200104, 0.02100514806807041, 0.027340620756149292, 0.008224636316299438, 0.024600865319371223, 0.01093902625143528, 0.0...
<p>I would like to understand the difference between the binomial, multinomial and ordinal models when it comes to interpreting the "distance" between classes, in terms of response probabilities. </p> <p>To illustrate my question, I have prepared the following graph (just for the sake of example)</p> <p><img src="htt...
g61601
[ -0.005016776267439127, -0.013571936637163162, -0.00826309248805046, -0.01335875689983368, 0.0038050427101552486, -0.016262516379356384, -0.004457112401723862, 0.023044465109705925, -0.03914815932512283, -0.04281977564096451, 0.018698954954743385, -0.021613501012325287, 0.053953126072883606, ...
<p>I'm interested about the field of energy consumption forecasting, and because I'm in the learning stage I'm looking for some source codes and samples. More exactly I'm interested about forecasting with neural networks approach. Yesterday I've found on CV the link to the <a href="http://www.neural-forecasting-compet...
g18252
[ 0.013329596258699894, -0.017187999561429024, 0.026333454996347427, -0.0065653664059937, -0.004781701602041721, -0.08724648505449295, 0.011735156178474426, 0.021263759583234787, -0.07918531447649002, 0.02008824050426483, 0.04190796986222267, -0.0004402102204039693, 0.04097774624824524, 0.04...
<p>I have a program system, where present a lot of tasks. Each task need some time for an execution and monitoring system writes time of execution for each task to a database. I need to calculate average execution time for each task for a long time period (much more than half year while it executes at least four times ...
g48009
[ -0.020744547247886658, 0.004069615621119738, 0.018258295953273773, -0.04356770217418671, -0.03154947608709335, -0.06348560750484467, 0.05955537036061287, 0.01641888916492462, -0.021115263924002647, 0.019079266116023064, -0.023944033309817314, 0.0028289256151765585, 0.03727351501584053, 0.0...
<p>I have panel data and for the I have a following equation</p> <p>$$ logY = \beta_1 + \beta_2 logX + \beta_3 m logW $$</p> <p>Problem is with $\beta_3$ coefficient. Since m is outside the log and it is a very small value, the overall $mlogW$ is very small and the resulting coefficient is very large (in thousands...
g31836
[ -0.01022537425160408, -0.018201882019639015, 0.020601576194167137, -0.0240213293582201, -0.008982534520328045, -0.045676857233047485, -0.006578098051249981, 0.03322749212384224, -0.015737975016236305, -0.01804826408624649, -0.05167423188686371, 0.03390752151608467, 0.03351758047938347, 0.0...
<p>Sorry for my title, but I really don't know how to describe this question. I am fitting a linear regression in R now, and I find that there is one parameter showing linear relationship before certain point and cubic relationship after that point. What I did is to separate the whole dataset with reference to that poi...
g61602
[ 0.07894221693277359, -0.0642034187912941, -0.02123531512916088, -0.024741806089878082, 0.019781479611992836, -0.0480392761528492, 0.0694589614868164, 0.057765811681747437, -0.05382981896400452, 0.0006097406148910522, -0.012272168882191181, -0.0029348561074584723, 0.01517327781766653, 0.004...
<p>I want to interpret the goodness of attributes using feature selection with 10-fold cross validation.</p> <p>With ChiSquared I get something like this (deletet attributes with merrit was 0 in all folds):</p> <pre><code>average merit average rank attribute 13.632 +- 1.6 1 +- 0 8 E8 </code></pr...
g61603
[ 0.013863002881407738, -0.024280104786157608, 0.015616894699633121, -0.032004840672016144, 0.06156257912516594, -0.01621539331972599, 0.057129520922899246, 0.08229219913482666, -0.03404918685555458, 0.0394224151968956, 0.00019601541862357408, 0.05606229230761528, 0.05868856981396675, 0.0107...
<p>I understand the critiques of pie charts as referenced here: <a href="http://stats.stackexchange.com/questions/8974/problems-with-pie-charts">Problems with pie charts</a></p> <p>However, the above response (and the R manual) always cite dot plots from Cleveland as an alternative. My question is why are dot plots co...
g61604
[ -0.011368856765329838, 0.029639415442943573, 0.004996078088879585, -0.13972854614257812, -0.042373258620500565, 0.010026560164988041, 0.06492124497890472, -0.04003991186618805, 0.006741407793015242, -0.01430013868957758, 0.05473290756344795, -0.024086007848381996, 0.08978509902954102, -0.0...
<p>The function <code>p.adjust()</code> in R accepts a parameter <code>n</code> that defaults to the length of the vector of p-values one wants to adjust:</p> <p><code>p.adjust(p, method = p.adjust.methods, n = length(p))</code></p> <p>In the documentation the explanation for <code>n</code> says:</p> <blockquote> ...
g18255
[ 0.044004060328006744, 0.03341399505734444, -0.023147933185100555, -0.011276118457317352, 0.0678703784942627, -0.05244404450058937, 0.014932652935385704, 0.04170065373182297, -0.04846819490194321, 0.007620885036885738, -0.0752197653055191, 0.021956974640488625, -0.007634719833731651, 0.0678...
<p>What are some good ways of presenting/comparing cross-validated RMSE errors for regression using various models, graphically via plots? As of now, I have been presenting the quantitative results in tabular form.</p>
g48100
[ 0.01525108888745308, -0.07056073099374771, -0.006453769281506538, -0.016587087884545326, -0.019848033785820007, -0.00993742048740387, 0.07981357723474503, -0.013767184689640999, -0.046844545751810074, 0.050169672816991806, 0.08601674437522888, 0.04413440078496933, 0.06670520454645157, 0.04...
<p>I want to find an example such that $X_n\rightarrow0$ as $n\rightarrow \infty$ while $E(X_n)=\infty$.</p> <p>I am thinking of making use the divergence of $\sum\frac{1}{n}$, but fail to find suitable $X_n$ and $\Pr(X_n=k)$.</p> <p>Can you show me some examples or give me some hints?</p>
g61605
[ 0.032609906047582626, 0.06420712172985077, 0.012145014479756355, -0.04614383727312088, 0.0006125132204033434, -0.0705711618065834, 0.02032909169793129, -0.008760537952184677, -0.019688736647367477, 0.013276073150336742, -0.07117423415184021, -0.025861680507659912, -0.004514852073043585, 0....
<p>I have a system that find best model (best inputs and parameters of MLP/SVM) model in a financial problem for every inserted database and create a specific model for a specific data sample. I'm using 5-fold cross validation that repeats for 5 times (for increasing reliability of my system) for cost function of my op...
g61606
[ 0.01792907528579235, -0.013280444778501987, 0.007099805865436792, -0.009110946208238602, -0.0005328396800905466, -0.04034347087144852, 0.026825979351997375, 0.024007340893149376, -0.06515220552682877, 0.008376934565603733, -0.009613966569304466, -0.0029351806733757257, 0.02338380366563797, ...
<p>I have a quick question that should hopefully require a quick answer (my apologies if this is a rather simple question). I have two estimates of relative abundance from two sub-populations and want to sum them to obtain one overall number. Being that they're just estimates, I also have their corresponding measures...
g18258
[ -0.028162309899926186, -0.04720820486545563, -0.018160380423069, -0.014975417405366898, 0.004245234187692404, -0.03789897635579109, 0.017648596316576004, -0.004358917474746704, -0.04115373268723488, 0.006095529068261385, -0.026311563327908516, 0.024402907118201256, 0.007492657285183668, -0...
<p>My experiment had a 2x3 design with one covariate. If I analyse the results using an ANOVA, I get a strongly significant interaction between the two main factors (p&lt;.001). If I add the covariate into the analysis and do an ANCOVA, the interaction between the two main factors is not significant (p=.252).</p> <p>T...
g61607
[ -0.02704656682908535, 0.014619476161897182, 0.004207033198326826, -0.022939307615160942, 0.029491227120161057, 0.04852951318025589, 0.05367986857891083, 0.011119993403553963, -0.01544316578656435, -0.00018516453565098345, -0.0067983223125338554, -0.02068464457988739, 0.022919006645679474, ...
<p>In 6 forests, I've 3 variables that I know the values for all trees: $height$, $diameter$ and $density$. I can only cut some trees to know their $mass$. The question is how to choose the trees to cut?</p> <p>As I supposed a linear model such as: $Mass = a_1 Diameter + a_2 Height + a_3 Density + a_4$ (or as mention ...
g61608
[ 0.01623697020113468, -0.06415443122386932, 0.013775811530649662, 0.005098967347294092, -0.010366136208176613, -0.04519475996494293, -0.03521718457341194, -0.0018256537150591612, -0.03980078548192978, 0.024256201460957527, 0.03390269726514816, -0.03706538677215576, 0.0002470806357450783, -0...
<p>Suppose that I have an infinite scale mixture of zero-mean normal distributions, whose mixing distribution is gamma with parameters $\alpha$ and $\beta$. The data is thus distributed according to a generalized Student's $t$ distribution. I am handed a pair of samples, $(z,y)$, generated through the following procedu...
g61609
[ -0.02028273046016693, -0.06689520925283432, -0.01758747175335884, -0.05821995064616203, 0.03881988674402237, 0.039241623133420944, -0.0009324062266387045, 0.04129882529377937, -0.032443296164274216, 0.0116769690066576, 0.013305402360856533, 0.0036347212735563517, -0.016966791823506355, 0.0...
<p>I would like to fit an ordinal regression model using proportional odds. I learned to test for "equal slopes" in order to say something about the model's validity. Therefore, I fit a model <em>with</em> equal slopes and I fit a model <em>without</em> equal slopes (e.g. with R using the VGAM package). After that, I d...
g61610
[ 0.056500162929296494, -0.005687959026545286, 0.012535414658486843, -0.010508039966225624, 0.04105733707547188, 0.009611595422029495, -0.007170813623815775, 0.008261162787675858, -0.027446595951914787, 0.006666972767561674, 0.05462619289755821, -0.007018950302153826, 0.029103565961122513, 0...
<p>All software programs I have tried report only odds ratios (ORs) for binary logistic regression predictors (as exponential of the betas).</p> <p>I am interested to know how can I compute the relative risk (RR) from a binary logistic regression model?</p> <p>My reason is that RRs (besides ORs) would make my variabl...
g61611
[ 0.026927564293146133, -0.03621531277894974, 0.004272608086466789, -0.037859100848436356, 0.00048209866508841515, -0.06752301007509232, 0.017647765576839447, 0.05374417454004288, -0.04068542644381523, -0.004406930413097143, 0.045448847115039825, 0.042555924504995346, 0.08031244575977325, 0....
<p>For one campaign, I have X as independent variable, Y as dependent variable, i.e., X is income, Y is credit score. I can use X to predict Y with proper model. Now I want to know how Y would perform if I added one more independent variable Z into the model, i.e., age. The challenge is I don't have any data on Z, that...
g18261
[ -0.05132998898625374, -0.021994365379214287, -0.006278255023062229, -0.046857304871082306, -0.02067749574780464, -0.012072740122675896, -0.01967504806816578, -0.0005208617658354342, 0.004717996809631586, -0.014170147478580475, 0.016311001032590866, 0.009395213797688484, 0.014715607278048992,...
<p>We know that martingale difference is an assumption weaker than dependence, and stronger than uncorrelated. The same is true for sub-independence. My question is how sub-independence and martingale difference are related.</p>
g18262
[ 0.025791315361857414, -0.02484545111656189, 0.015539376065135002, 0.041757915169000626, -0.0638972669839859, -0.005292884539812803, 0.052555523812770844, 0.011475656181573868, -0.0427514985203743, -0.030720114707946777, -0.04852297157049179, 0.04595164582133293, 0.0017485691932961345, 0.02...
<p>Is it possible that two random variables have the same distribution and yet they are almost surely different?</p>
g61612
[ 0.012265615165233612, -0.030255362391471863, 0.016183672472834587, -0.03477412834763527, 0.001617962378077209, 0.007594414055347443, -0.03388696536421776, -0.007752712350338697, -0.007117492146790028, -0.015209364704787731, 0.00235552666708827, -0.015145497396588326, -0.028593506664037704, ...
<p>According to <em>Regression Analysis by Example</em>, the residual is the difference between response and predicted value, then it is said that every residual has different variance, so we need to consider standardized residuals. </p> <p>But the variance is for a group of values, how could a single value have varia...
g61613
[ -0.0023386108223348856, -0.03126763179898262, -0.018623199313879013, 0.010865968652069569, -0.020654093474149704, 0.02889969013631344, 0.011679064482450485, 0.04370155930519104, -0.04125801473855972, -0.04323321208357811, -0.040083322674036026, 0.025141913443803787, -0.013054285198450089, ...
<p>I have a set of measurements which is partitioned into M partitions. However, I only have the partition sizes $N_i$ and the means $\bar{x}_i$ from each partition. Because all measurements are assumed to be from the same distribution, I believe I can estimate the mean of the population, $\bar{y}$, and standard deviat...
g48110
[ -0.0019450471736490726, -0.006585301365703344, -0.016180122271180153, -0.0016017032321542501, -0.005018115043640137, -0.05338292941451073, -0.012462402693927288, 0.042861197143793106, -0.0070092519745230675, -0.042928215116262436, -0.03249770402908325, -0.009389877319335938, 0.02772243320941...
<p>1. Is there any naming convention regarding the hat and the tilde symbol in stats? I found $\hat{\beta}$ is describing an estimator for $\beta$ ( <a href="http://%5BWikipedia%5D%3a%20http://en.wikipedia.org/wiki/Estimator">Wikipedia</a> ) But I also found $\tilde{\beta}$ is describing an estimator for $\beta$ (<a hr...
g61614
[ 0.043016694486141205, -0.029943296685814857, -0.022354857996106148, -0.07103408873081207, 0.043914683163166046, -0.016050215810537338, 0.08715808391571045, 0.021598834544420242, -0.05748658627271652, 0.01964922435581684, -0.04760707914829254, 0.04159834608435631, 0.043609656393527985, 0.03...
<p>Is there any command-line tool that accepts the flow of numbers (in ascii format) from standard input and gives the basic descriptive statistics for this flow, such as min, max, average, median, RMS, quantiles etc? The output is welcome to be parseable by the next command in command-line chain. Working environment i...
g208
[ 0.033366963267326355, -0.0058374167419970036, -0.02004546858370304, -0.05584307387471199, -0.03736745938658714, -0.06615198403596878, 0.0009461863082833588, -0.049179624766111374, -0.06504757702350616, -0.09104049205780029, 0.027986938133835793, 0.028246182948350906, 0.08324670046567917, -...
<p>I am a newbie to principal component analysis (PCA). I will have to do PCA to data sets consisting of count statistics: all data are positive integers.</p> <p>Before PCA the data needs to be normalized. It is more or less standard to do that by subtracting the mean and dividing by the standard deviation in the vari...
g61615
[ 0.016576223075389862, -0.02088269405066967, 0.003022789256647229, -0.004165565129369497, -0.07127034664154053, -0.0005288572865538299, 0.014695300720632076, 0.041554223746061325, -0.004152174573391676, -0.016533270478248596, 0.03579361364245415, 0.025843655690550804, -0.035093650221824646, ...
<p>I understand the rules for combining experimental errors in sums, differences and ratios (<a href="http://www.rod.beavon.clara.net/err_comb.htm" rel="nofollow">as explained here</a>), but what happens to an experimental error when you average it?</p> <p>Say, ruler measurements of the length of beetles that are all ...
g18264
[ 0.054938506335020065, -0.0390198789536953, -0.01343016978353262, -0.009602169506251812, 0.04488999769091606, -0.041614238172769547, 0.041260022670030594, 0.00127904221881181, -0.03151871636509895, 0.011337053962051868, -0.03891514614224434, -0.03153451532125473, 0.07059366255998611, 0.0195...
<p>I'm student and I have project from Data Warehouses's course. I have to create cube from database (or I should create database from raw date). It is required that the data are real (I don't mean real number). Maybe someone with your experience knows source of date on statistics in volleyball</p>
g48113
[ 0.0023013371974229813, 0.035018619149923325, 0.005369078367948532, -0.010261200368404388, -0.0395587794482708, -0.007681397721171379, 0.058815211057662964, 0.0293381717056036, -0.021955914795398712, 0.010986755602061749, -0.059927694499492645, 0.01092134602367878, 0.052438680082559586, -0....
<p>I have a subset of data from a panel covering 100 cities and 20 years but the subset for some reason does not include the time variable or a variable to distinguish one city from another.</p> <p>What are the implications for OLS? Would this violate some assumptions? How can I get around it (if at all)?</p> <p>Can ...
g61616
[ 0.026469115167856216, -0.01751362718641758, -0.025570163503289223, -0.0754818245768547, -0.05167408660054207, -0.011628922075033188, -0.010570242069661617, 0.011753911152482033, 0.01131422072649002, -0.0020232386887073517, 0.020239319652318954, 0.03469108045101166, 0.05779484659433365, 0.0...
<p>How can reliability and validity of <a href="http://en.wikipedia.org/wiki/Content_analysis">content analysis</a> be quantified when there is only one person coding the data?</p>
g61617
[ -0.014360662549734116, -0.0063093239441514015, -0.024621928110718727, -0.013841995038092136, 0.05093415081501007, 0.051237188279628754, -0.003907191101461649, 0.026002641767263412, -0.03312751278281212, -0.0034878100268542767, -0.002762421267107129, -0.042989011853933334, 0.02696757018566131...
<p>Assume that I have two time series $Y_{1t}$ and $Y_{2t}$ that are sampled at the same frequency. Is there a way to quantify the uncertainty in their difference $Y_{1t} - Y_{2t}$? That is, can we get confidence bands on $Y_{1t} - Y_{2t}$?</p> <p>My thought is that some sort of a dependent bootstrap should apply.</p>...
g3013
[ -0.012029953300952911, -0.02304990403354168, 0.013873256742954254, -0.013166694901883602, 0.05222286283969879, -0.01641865447163582, -0.00399441784247756, -0.07290798425674438, -0.06911935657262802, -0.01949751377105713, 0.004513530060648918, 0.06733734905719757, 0.00003517006553011015, 0....
<p>Let $A$ and $B$ denote two events, and suppose that </p> <p>$\text{P}(A) = 0.2$, $\text{P}(B) = 0.3$, and $\text{P}(A\cap B) = 0.1$.</p> <p>Are the following computations correct?</p> <ol> <li>$\rm{P}(A \cup B) = \rm{P}(A) + \rm{P}(B) - \rm{P}(A\cap B) = 0.4$</li> <li>$\rm{P}(B') = 1 - \rm{P}(B) = 0.7$, where $B...
g61618
[ 0.016081789508461952, -0.05999485403299332, -0.014720983803272247, -0.007913554087281227, 0.056580252945423126, -0.09031550586223602, 0.056005965918302536, 0.02056809514760971, -0.030324449762701988, 0.023066775873303413, -0.062128644436597824, 0.02129371464252472, 0.011915318667888641, -0...
<p>Given a sequence of i.i.d. random variables, say, $X_i \in [0,1]$ for $i = 1,2,...,n$, I'm trying to bound the expected number of times the empirical mean $\frac{1}{n}\sum_{i=1}^n X_i$ will exceed a value, $c \geq 0$, as we continue to draw samples, that is: $$ \mathcal{T} \overset{def}{=} \sum_{j=1}^n \mathbb{P} \l...
g61619
[ -0.04708566889166832, 0.02926396019756794, -0.006787958554923534, -0.03569110110402107, -0.03679228946566582, -0.0243441890925169, 0.022189006209373474, -0.01726723648607731, -0.04103823006153107, -0.02394302375614643, -0.0072572058998048306, 0.010906339623034, 0.028958749026060104, 0.0456...
<p>I have a model that has the following characteristics:</p> <ul> <li>The covariate $X$ follows a $Be(1/3)$.</li> <li>If $X=0$, survival time $Y$ follows an $E=Exponential (1)$.</li> <li>If $X=1$, survival time $Y$ is generated as $E$ if $E\le\Psi$, and as $\Psi+E_\lambda$ if $E&gt;\Psi$, where $\Psi$ is the 'change ...
g61620
[ 0.006271860562264919, -0.0556122325360775, -0.002705440390855074, -0.02896237000823021, 0.018139317631721497, 0.0010919789783656597, -0.0382254421710968, 0.04154679551720619, -0.025736410170793533, 0.06975176185369492, 0.011154843494296074, 0.01518226321786642, 0.04233083501458168, -0.0093...
<p>I want to project a vector onto space transformed by PCA. I've calculated PCA in R language using <code>prcomp</code>. </p> <p>Now I should be able to multiply my vector by matrix of rotation. </p> <p>Should principal components in this matrix be arranged in rows or columns?</p> <p>Vector that I want to project:<...
g48116
[ 0.050837110728025436, -0.01526134554296732, 0.0028146745171397924, -0.04110801964998245, -0.009948805905878544, -0.07269708067178726, 0.05005194991827011, 0.039012081921100616, -0.038529716432094574, -0.03226660192012787, 0.030496252700686455, 0.014384116046130657, -0.012634387239813805, -...
<p>Let $X_1$ and $X_2$ be discrete non-negative random variables with $E(X_1) \le E(X_2)$. Assume a function $f$ with the following properties:</p> <ul> <li>$f$ is positive, i.e. $f(x) \ge 0$</li> <li>$f$ is (strictly) monotone increasing</li> <li>$f$ is concave </li> </ul> <p>I conjecture that $E(f(X_1)) \le E(f(X_2...
g18268
[ -0.03389829769730568, 0.028226885944604874, 0.008185687474906445, -0.021740863099694252, 0.0029919485095888376, -0.02026134729385376, 0.013545185327529907, -0.038002993911504745, 0.022325482219457626, 0.03066202625632286, -0.02436823770403862, 0.021368136629462242, -0.008067871443927288, 0...
<p>Let's pretend there are 10 doors in front of me. Behind one of them, there is a treasure and nothing behind all the others. Intuitively, I can easily determine I have 1 chance out of 10 the pick open the right door (the one with the treasure). I repeat this 5 times (i.e. all door closed, open one door). What are my ...
g18271
[ -0.05093967169523239, 0.0021486394107341766, -0.01946818269789219, -0.019627107307314873, 0.027010153979063034, -0.050772637128829956, 0.12686720490455627, 0.018357763066887856, 0.0007983184768818319, 0.014426568523049355, -0.0662035346031189, -0.016246657818555832, -0.012133842334151268, ...
<p>In section 3.3 of Kutner's Applied Statistical Linear Models:</p> <blockquote> <p><strong>Nonindependence of Error Terms</strong></p> <p>Whenever data are obtained in a time sequence or some other type of sequence, such as for adjacent geographic areas, it is a good idea to prepare a sequence plot of the r...
g61621
[ 0.030167052522301674, -0.03211067244410515, 0.0068782782182097435, -0.002799122128635645, -0.057706233114004135, -0.00576423853635788, 0.03283603489398956, 0.012540020979940891, 0.008364099077880383, -0.020383913069963455, 0.002789872232824564, 0.02718217298388481, 0.010417141951620579, 0....
<p>Is there anyone who can explain as simple as possible how to go about doing this?</p> <p>I have been watching different youtube videos and using google as well, however, I have not understood how to go about approaching this.</p> <p>I know of the Durbin-Watson Test, of dl, du, 4, 0, 2 but it just doesn't make sens...
g61622
[ 0.05945105850696564, -0.03847359120845795, 0.0000978525640675798, -0.08018913865089417, -0.00416899798437953, -0.051124438643455505, 0.1031840518116951, 0.03372693061828613, 0.03291822224855423, -0.04335229843854904, 0.010229239240288734, 0.05070967599749565, 0.056911345571279526, -0.00113...
<p>I am fitting a model to some sales data and looking to accurately represent male/female behaviour (e.g basket analysis).</p> <p>For example, I know the proportion of females/males in the population buying these products are 50:50, and my products are identical to competitor products, however, my data contains 30% f...
g61623
[ 0.040853213518857956, -0.01992887072265148, 0.0040058265440166, -0.05924920737743378, 0.0010724968742579222, 0.020071083679795265, 0.03721677511930466, -0.020983202382922173, -0.051745787262916565, 0.0203106626868248, 0.014640217646956444, -0.005402951501309872, 0.0689096599817276, 0.03330...
<p>The content of this question is about rigorously proving something which is otherwise considered easily correct intuitively.</p> <p>Let's assume we have a multivariate distribution $g(x_1,x_2,...,x_n)$ over the variables $x_{1:n}$. Let's assume that we know how to sample from that distribution, too. We draw sample...
g61624
[ 0.02732856757938862, -0.014788449741899967, -0.02097224071621895, -0.05008435249328613, 0.028951434418559074, -0.08495324850082397, -0.02762545272707939, -0.03785419464111328, -0.030994446948170662, 0.023439975455403328, -0.02160332351922989, 0.02369818650186062, 0.007363344542682171, 0.00...
<p>Apologies for the noob question. After a day on Google and Wikipedia I still can't quite work out what to do. So here I am.</p> <p>A small private healthcare clinic in the UK has asked me to look at their patient appointments data. Patients hear about the clinic from various sources (Google, word-of-mouth, leaflets...
g61625
[ -0.02480906993150711, 0.0306476391851902, -0.0188871119171381, -0.05722175911068916, -0.01158967800438404, -0.018878158181905746, 0.04273506626486778, 0.029519401490688324, 0.017104027792811394, 0.023574765771627426, 0.03350817412137985, 0.05005144700407982, 0.04792033135890961, 0.01257074...
<p>I recently read the excellent book <a href="http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/#contents">Probabilistic Programming &amp; Bayesian Methods for Hackers</a> and I'm trying to solve some problems on my own:</p> <blockquote> <p>I perform an experiment to estim...
g61626
[ -0.05368279665708542, 0.017322110012173653, 0.018528982996940613, 0.028788160532712936, 0.005100575275719166, -0.03407777473330498, 0.0675625279545784, -0.007834542542696, -0.03789477422833443, -0.03052905946969986, -0.015295722521841526, 0.016006937250494957, 0.05019332095980644, 0.037418...
<p>I am trying to optimize my set of features against random forest cross-validation using MAPE criteria. </p> <p>I tried forward selection with Univariate linear regression test (f_regression in sklearn), I calculate MAPE for each set of variables selected by SelectKBest:</p> <pre><code>for i in range(1,len(X.column...
g18283
[ -0.02946758083999157, -0.03188305348157883, 0.021320682018995285, -0.019772296771407127, -0.033074989914894104, -0.03319414332509041, -0.009982245974242687, 0.022050321102142334, -0.008679067716002464, 0.019097886979579926, 0.02382073365151882, -0.001371207763440907, 0.06434513628482819, 0...
<p>Does the autocorrelation function have any meaning with a non-stationary time series?</p> <p>The time series is generally assumed to be stationary before autocorrelation is used for Box and Jenkins modeling purposes.</p>
g48136
[ 0.03376992046833038, 0.005163177847862244, 0.03738173469901085, -0.038179926574230194, 0.022157272323966026, -0.014906402677297592, 0.07581193745136261, 0.015361861325800419, -0.01486615277826786, -0.033249836415052414, -0.014254087582230568, 0.02137812413275242, 0.011275854893028736, -0.0...
<p>I'm trying to build a prediction model with SVMs on fairly unbalanced data. My labels/output have three classes, positive, neutral and negative. I would say the positive example makes about 10 - 20% of my data, neutral about 50 - 60%, and negative about 30 - 40%. I'm trying to balance out the classes as the cost ass...
g42631
[ -0.0018334240885451436, -0.03074229508638382, 0.02136182226240635, 0.0009638188639655709, 0.014591182582080364, 0.002310799201950431, -0.011077272705733776, 0.05604296550154686, -0.02091480791568756, -0.009095658548176289, 0.029781099408864975, 0.004667217843234539, 0.07631298899650574, 0....
<p>I have a 2x2x2 factorial design with two dependent variables (lets say height and weight). I can examine the effect of the three factors for each dependent variable separately. But I also want to check if height has anything to do with weight? I.e., is the tallest subject the heaviest?</p> <ul> <li>Any idea on ho...
g61627
[ 0.035267554223537445, -0.027906283736228943, -0.01836075633764267, -0.03944217413663864, -0.02620757557451725, 0.008936681784689426, 0.012968567200005054, 0.022344226017594337, -0.07398277521133423, -0.0471690408885479, -0.004859549459069967, 0.037368882447481155, 0.051110927015542984, -0....
<p>Most of the text classifiers are based on the bag-of-words approach where you loose the context that a particular word appears. As a solution (or simple solution?) we can use n-grams as features. But are there any classifiers which "gist" the idea and model it in someway before training?</p>
g61628
[ -0.02510875090956688, -0.011071408167481422, 0.005471039563417435, -0.07779472321271896, -0.04403140768408775, -0.03575878217816353, -0.008851717226207256, 0.05175638198852539, -0.035056378692388535, -0.012449907138943672, 0.021517658606171608, -0.026493340730667114, 0.06047968566417694, 0...
<p>need to do time series analysis(TSA) and forecasting on over 100 customers in Hadoop environment(RHadoop), for each customer, it has its own time series which I can analyze individually, but when I do it in Hadoop, is it possible that each customer's time series might be broken into pieces(i.e it doesn't have contin...
g61629
[ -0.024550247937440872, 0.01071222499012947, 0.01784839667379856, -0.0031323893927037716, -0.018296990543603897, -0.0661625936627388, 0.04940690100193024, 0.0028580555226653814, -0.03493845835328102, 0.005100298672914505, 0.03423495590686798, 0.002496155211701989, -0.025183066725730896, 0.0...
<p>I am running a pooled OLS and Random Effects (RE) model and I would like to test for whether there are any outliers. </p> <p>I know how to do this for OLS, but I just dont know how to do it for Random Effects model?</p> <p>If there is outliers when running pooled OLS does it mean that outliers are also present whe...
g9889
[ -0.02544247917830944, -0.05149805173277855, 0.03167878836393356, -0.06821148097515106, 0.06024473160505295, 0.036277614533901215, 0.0007213335484266281, 0.03838464990258217, 0.027095509693026543, -0.007616296876221895, -0.035157326608896255, 0.06969816982746124, 0.019984427839517593, 0.018...
<p>I'm want to do a PhD in NLP and I'm defining the topic at the moment.</p> <p>I've heard that NLP can be used to track online sentiment which in turn can be used for algorithmic trading on stock markets. <a href="http://www.globalpost.com/dispatches/globalpost-blogs/weird-wide-web/twitter-hedge-fund-derwent-capital-...
g48140
[ 0.03873882815241814, 0.05964205414056778, 0.025419259443879128, -0.05398792028427124, 0.01630493439733982, -0.04301140084862709, -0.03298503905534744, 0.05024394392967224, -0.03589840605854988, 0.00595624977722764, 0.018096135929226875, -0.015491698868572712, 0.054557010531425476, -0.03473...
<p>Imagine you have to do reporting on the numbers of candidates who yearly take a given test. It seems rather difficult to infer the observed % of success, for instance, on a wider population due to the specifity of the target population. So you may consider that these data represent the whole population. </p> <p>Are...
g49321
[ -0.020148305222392082, -0.04862460866570473, 0.007951748557388783, -0.02263704501092434, -0.0011689094826579094, 0.023260436952114105, 0.021589400246739388, 0.02246183156967163, 0.024032222107052803, -0.01392616331577301, 0.054927580058574677, -0.0351884663105011, 0.03455542027950287, 0.04...
<p>If I have a coin that is not necessarily expected to turn up heads half of the time, then is it correct to call the coin biased? Or does <em>bias</em> in statistics only mean the bias of an estimator in which case it would be inappropriate to describe the coin itself as biased?</p> <p>This question does not mean t...
g61630
[ 0.008484303019940853, -0.006126886233687401, 0.013079964555799961, -0.05852728709578514, 0.029266968369483948, -0.020189717411994934, 0.032678473740816116, -0.02760990336537361, -0.00793032068759203, 0.0017372999573126435, 0.015031763352453709, 0.07539808005094528, 0.030160697177052498, -0...
<p>I have Group A, B, C. My hypotheses are"</p> <p>1) proportions of C are different from proportions of A (=independance) <br /> 2) proportions of C are different from proportions of B (=independance) <br /> 3) proportions of A are NOT different from proportions of B (=NO independance) <br /></p> <p>Is there somethi...
g18289
[ 0.02914002165198326, -0.03465502709150314, -0.001625098753720522, -0.032652974128723145, 0.025114357471466064, -0.032708074897527695, -0.010133505798876286, 0.008456937968730927, -0.05605928599834442, 0.00032352370908483863, 0.031209927052259445, -0.022679094225168228, -0.014489728026092052,...
<p>I want to build a document classifier in R, using the Naive Bayes approach.</p> <p>Here are steps, that I've done so far:</p> <ul> <li>I have corpus with about 30 documents from 2 authors (Classes are: "target author" and "other author").</li> <li>"Vocabulary" (training set) has been pre-processed (removed numbers...
g18290
[ 0.017717231065034866, -0.018837055191397667, 0.009207800030708313, -0.05181346833705902, 0.010334127582609653, -0.03724826127290726, 0.007391124498099089, 0.05339755117893219, -0.024409933015704155, -0.02629772387444973, 0.016736652702093124, 0.04017046466469765, -0.00839405506849289, -0.0...
<p>If I give you three numbers that are independently and identically drawn from a standard normal distribution, then have I given you three samples or one sample?<br> If the answer is one sample, then is there a short name for what I have given you three of?</p>
g18291
[ 0.03075067140161991, -0.017351524904370308, 0.007010700646787882, -0.040154553949832916, -0.05076179653406143, 0.02208317071199417, -0.02046755887567997, -0.008007930591702461, 0.009125563316047192, -0.010553724132478237, -0.011553240939974785, -0.0007337863789871335, -0.02137327939271927, ...
<p>I have a huge dataset which contains 20 columns and many rows. I have done clustering in SAS, Knime and SPSS, but I am new to R. I have to do clustering on my dataset. I have imported my data into R.</p> <ul> <li>What are some suggestions for getting started with cluster analysis in R?</li> </ul>
g61631
[ 0.030673127621412277, 0.00482498575001955, -0.010929315350949764, -0.045599378645420074, -0.0415327288210392, -0.027615206316113472, -0.009923383593559265, 0.043667133897542953, -0.017418384552001953, -0.03883622959256172, 0.003961530514061451, 0.010833341628313065, 0.08576656132936478, 0....
<p>Excuse what may be an obvious question about bootstrapping. I got sucked in the Bayesian world early and never really explored bootstrapping as much as I should have. </p> <p>I ran across an analysis in which the authors were interested in a survival analysis related to some time to failure data. They had about 1...
g18293
[ -0.02027525193989277, 0.006364251486957073, 0.004561460576951504, 0.014676272869110107, -0.017270222306251526, 0.051077719777822495, 0.0060760886408388615, -0.026183707639575005, -0.10555563122034073, -0.0008231009705923498, -0.011110221035778522, -0.00849677249789238, 0.08580319583415985, ...