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8461 | 2 | null | 8456 | 9 | null | Use a Scatter Plot where the horizontal axis is time. Below is a screenshot of an Excel sheet where two temperatures are shown. Temp 1 starts at 9:00:00 AM and increments by 1 minute and 26 seconds. Temp 2 starts at 9:30:00 AM and increments by 2 minutes and 53 seconds. They are both plotted in the graph.
As sh... | null | CC BY-SA 2.5 | null | 2011-03-18T18:13:25.927 | 2011-03-18T18:13:25.927 | null | null | 2775 | null |
8462 | 1 | 8484 | null | 10 | 1107 | We're creating a chart showing traffic by time of day over a given period. So the y-axis is traffic, the x-axis is midnight, 1am, 2am, etc. It could also be days of the week. What's the generic name for this type of chart? I've come up with "cycle chart". Is that the standard? Is there one?
![example](https://i.stack.i... | What's a good, generic name for chart of things by time of day? | CC BY-SA 2.5 | null | 2011-03-18T18:19:39.250 | 2011-03-19T15:02:19.393 | 2011-03-18T21:56:26.593 | 1531 | 1531 | [
"time-series",
"data-visualization"
] |
8463 | 2 | null | 8455 | 4 | null | Before you set up your analysis, keep in mind the reality of what the current situation involves.
This meltdown was not directly caused by the earthquake or the tsunami. It was because of a lack of back-up power. If they had enough back-up power, regardless of the earthquake/tsunami, they could have kept the coolin... | null | CC BY-SA 2.5 | null | 2011-03-18T18:47:04.663 | 2011-03-21T17:36:23.963 | 2011-03-21T17:36:23.963 | 2775 | 2775 | null |
8464 | 2 | null | 8462 | 0 | null | The type of chart you've drawn is known as a Histogram [http://en.wikipedia.org/wiki/Histogram](http://en.wikipedia.org/wiki/Histogram)
| null | CC BY-SA 2.5 | null | 2011-03-18T19:05:28.163 | 2011-03-18T19:05:28.163 | null | null | null | null |
8465 | 2 | null | 8462 | 4 | null | What you've illustrated is a time series column (or bar) graph. The two graphs are of differing time resolution or differing time aggregation.
There may be industry specific terms for these types of charts. In finance, for example, the [open-high-low-close chart](http://en.wikipedia.org/wiki/Open-high-low-close_chart)... | null | CC BY-SA 2.5 | null | 2011-03-18T19:05:58.343 | 2011-03-18T19:05:58.343 | null | null | 29 | null |
8466 | 1 | 8482 | null | 3 | 10269 | We know that density for a student-t distribution is given as
$$\frac{\Gamma(\frac{\nu + 1}{2})}{\Gamma(\frac{\nu}{2})} \left(\frac{\lambda}{\pi\nu}\right)^{\frac{1}{2}} \left[1+\frac{\lambda(x-\mu)^2}{\nu}\right]^{-\frac{\nu+1}{2}}$$
with
$\text{E}(X) = \mu$,
$\text{var}(X) = \frac{1}{\lambda}\frac{\nu}{\nu-2}$
wher... | Standardized Student's-t distribution | CC BY-SA 2.5 | null | 2011-03-18T19:07:53.047 | 2015-05-04T08:28:58.207 | 2011-03-19T04:11:17.990 | 919 | 862 | [
"likelihood",
"t-distribution"
] |
8467 | 2 | null | 8462 | 0 | null | Short, simple, descriptive: time series plot.
Edit: In light of the discussion, I'd vote for histogram as well. At least, thats the generic name for this kind of chart, where the hours of the day are a natural division of stacks.
| null | CC BY-SA 2.5 | null | 2011-03-18T19:58:55.227 | 2011-03-18T23:20:04.863 | 2011-03-18T23:20:04.863 | 1766 | 1766 | null |
8468 | 1 | null | null | 3 | 617 | Let's say I'm performing regularized regression and I want to validate the results using holdout. (I'm choosing holdout instead of cross-validation because my dataset is fairly large, so computational power is an issue and the difference between holdout and cross-validation estimates will likely be negligible.) I wan... | Confidence Intervals for Holdout R^2? | CC BY-SA 2.5 | null | 2011-03-18T21:04:55.237 | 2011-03-19T00:01:10.343 | 2011-03-19T00:01:10.343 | 159 | 1347 | [
"regression",
"correlation",
"confidence-interval",
"forecasting"
] |
8469 | 2 | null | 8033 | 1 | null | Ten days later this is probably worth an answer:
A normal distribution has about 20% of its distribution more than 0.842 standard deviations above the mean; using the cumulative distribution of standard normal $\Phi$,
$$\Phi(0.842) \approx 0.8$$
so the threshold should be about $70 + 8\times 0.842 \approx 76.7$.
I do w... | null | CC BY-SA 2.5 | null | 2011-03-18T21:12:59.237 | 2011-03-18T21:12:59.237 | null | null | 2958 | null |
8470 | 1 | null | null | 3 | 1998 | I'm working on a naive Bayes classifier that calculates probabilities using a normal Gaussian distribution. This works very well when I am classifying something into two mutually exclusive buckets (e.g. spam vs. not-spam), but when I am working with a factor that is not easily classified that way (when the classificati... | Can you express a probability density as a percentage? | CC BY-SA 2.5 | null | 2011-03-18T21:27:39.560 | 2011-04-28T22:54:36.987 | 2011-04-28T22:54:36.987 | null | 3784 | [
"probability"
] |
8471 | 2 | null | 8462 | 4 | null | I'd suggest "diurnal" or "circadian" rhythm chart. For weekly, the latter would be "circaseptan", "circamensual" for "monthly", and "circannual" for "yearly".
| null | CC BY-SA 2.5 | null | 2011-03-18T22:12:17.783 | 2011-03-18T22:20:42.863 | 2011-03-18T22:20:42.863 | 3369 | 3369 | null |
8472 | 1 | 8495 | null | 12 | 52713 | In network motif algorithms, it seems quite common to return both a [p-value](http://en.wikipedia.org/wiki/P-value) and a [Z-score](http://en.wikipedia.org/wiki/Standard_score) for a statistic: "Input network contains X copies of subgraph G". A subgraph is deemed a motif if it satisfies
- p-value < A,
- Z-score > B ... | What is the difference between Z-scores and p-values? | CC BY-SA 2.5 | null | 2011-03-18T23:33:45.757 | 2011-04-29T00:42:18.500 | 2011-04-29T00:42:18.500 | 3911 | 386 | [
"hypothesis-testing",
"p-value",
"z-statistic"
] |
8473 | 2 | null | 8472 | 6 | null | $p$-value indicates how unlikely the statistic is. $z$-score indicates how far away from the mean it is. There may be a difference between them, depending on the sample size.
For large samples, even small deviations from the mean become unlikely. I.e. the $p$-value may be very small even for a low $z$-score. Conversel... | null | CC BY-SA 2.5 | null | 2011-03-18T23:40:41.547 | 2011-03-18T23:40:41.547 | null | null | 3369 | null |
8474 | 2 | null | 8468 | 2 | null | That should work ok provided the lower limit of your confidence interval is positive. Otherwise the square transformation is not monotonically increasing and then the probability coverage is not preserved.
I've never seen it done before either.
| null | CC BY-SA 2.5 | null | 2011-03-19T00:00:53.150 | 2011-03-19T00:00:53.150 | null | null | 159 | null |
8475 | 2 | null | 8470 | 2 | null | You can use any "monotonic" transformation of the probabilities as you choose (at least as far as I know). As long as your transformation preserves the ordering of probabilities, you will not be lead astray in your decision making. Personally, I prefer to use odds ratios. They seem to make intuitive sense to me, and... | null | CC BY-SA 2.5 | null | 2011-03-19T00:23:09.483 | 2011-03-19T00:23:09.483 | 2017-04-13T12:44:44.530 | -1 | 2392 | null |
8476 | 2 | null | 8472 | 8 | null | A $Z$-score describes your deviation from the mean in units of standard deviation. It is not explicit as to whether you accept or reject your null hypothesis.
A $p$-value is the probability that under the null hypothesis we could observe a point that is as extreme as your statistic. This explicitly tells you whether yo... | null | CC BY-SA 2.5 | null | 2011-03-19T00:51:10.900 | 2011-03-19T00:51:10.900 | null | null | 3786 | null |
8477 | 1 | 8489 | null | 1 | 825 | I am reading Stephen Taylor's Asset Dynamics book and came across something I didn't fully understand.
For an ARCH process, the return series is modeled as
$r_t = \mu_t + h_t^{1/2}z_t$ where is $z_t$ is $D(0,1)$ and may be normal/non-normal and $h_t$ is conditional variance (some function of subset of $\theta$).
Then h... | Expression for conditional density for ARCH processes | CC BY-SA 2.5 | null | 2011-03-19T01:03:17.700 | 2011-03-19T11:10:07.747 | 2011-03-19T11:03:50.653 | null | 862 | [
"likelihood",
"conditional-probability",
"garch"
] |
8478 | 2 | null | 8466 | 0 | null | If you're referring to the density function it's the exact same thing. You have simply shifted the distribution and normalized by the standard deviation.
| null | CC BY-SA 2.5 | null | 2011-03-19T01:03:58.207 | 2011-03-19T01:03:58.207 | null | null | 3786 | null |
8479 | 2 | null | 8446 | 3 | null | This looks a lot like a Beta distribution from its shape and seemingly bounded domain. You can use maximum likelihood estimation to estimate the parameters $\alpha$ and $\beta$.
| null | CC BY-SA 2.5 | null | 2011-03-19T01:10:58.090 | 2011-03-19T01:10:58.090 | null | null | 3786 | null |
8480 | 2 | null | 866 | 39 | null | Generally, when you have many small/medium sized effects you should go with ridge. If you have only a few variables with a medium/large effect, go with lasso.
[Hastie, Tibshirani, Friedman](http://www-stat.stanford.edu/~tibs/ElemStatLearn/)
| null | CC BY-SA 2.5 | null | 2011-03-19T01:21:05.993 | 2011-03-19T01:21:05.993 | null | null | 3786 | null |
8481 | 2 | null | 8401 | 2 | null | There isn't any indication that your variables here are correlated so I dont know why you would use MCMC as opposed to regular Monte Carlo. There are many different sampling methods including the mentioned stratified sampling (Latin hypercube) and QMC. Sparse quadrature methods are very good if the dimension of the pro... | null | CC BY-SA 2.5 | null | 2011-03-19T01:38:59.533 | 2011-03-19T01:38:59.533 | null | null | 3786 | null |
8482 | 2 | null | 8466 | 7 | null | Assume $\nu \gt 2$ so that this distribution actually has a mean and standard deviation (otherwise you cannot standardize it). By direct calculation, its mean equals $\mu$ and its variance equals $\nu / (\lambda (\nu-2))$. Standardizing it, by construction, creates a distribution of the same shape but zero mean and u... | null | CC BY-SA 2.5 | null | 2011-03-19T04:10:02.780 | 2011-03-19T04:10:02.780 | null | null | 919 | null |
8483 | 1 | null | null | 3 | 707 | I am researching age at first sexual debut and HIV prevalence in Lesotho. I want to analyse the data using logistic regression with SPSS. My variables are age, sex, social status, education level, and environment. How am I to allocate my variables?
| Analysis plan using logistic regression | CC BY-SA 2.5 | null | 2011-03-19T07:48:59.207 | 2011-03-19T14:07:17.233 | 2011-03-19T14:07:17.233 | 919 | null | [
"logistic"
] |
8484 | 2 | null | 8462 | 7 | null | Nick Cox [(Stata Journal 2006, p403)](http://stata-journal.com/sjpdf.html?articlenum=gr0025) calls this sort of plot a 'cycle plot', but notes that:
>
Cycle plots have been discussed under other names in the literature, including cycle-subseries plot, month plot, seasonal-by-month plot, and seasonal subseries plot.
... | null | CC BY-SA 2.5 | null | 2011-03-19T08:32:20.230 | 2011-03-19T08:32:20.230 | null | null | 449 | null |
8485 | 1 | 8509 | null | 29 | 11457 | I want to learn how Gibbs Sampling works and I am looking for a good basic to intermediate paper. I have a computer science background and basic statistic knowledge.
Anyone has read good material around? where did you learn it?
| A good Gibbs sampling tutorials and references | CC BY-SA 4.0 | null | 2011-03-19T09:07:52.767 | 2021-04-29T00:08:47.333 | 2021-04-29T00:08:47.333 | 11887 | 3788 | [
"references",
"gibbs"
] |
8486 | 1 | null | null | 2 | 625 | I want to compare the slopes of progression of a variable that is measured in percentage versus a variable that is measured in decibels. What is a good method to compare?
| How to compare slopes between variables with different scales? | CC BY-SA 2.5 | null | 2011-03-19T09:26:43.973 | 2011-03-19T11:17:48.263 | 2011-03-19T11:17:48.263 | 930 | 3194 | [
"multiple-comparisons"
] |
8487 | 1 | null | null | 17 | 13442 | I've calculated Cohen's d for regression coefficients (from the t statistic), odds ratios and means differences, hoping to pool the results in a meta-analysis and see how it works. However, in Stata, it doesn't seem you're able to pool these results without confidence intervals for Cohen's d, so my question is how do I... | How do you calculate confidence intervals for Cohen's d? | CC BY-SA 3.0 | null | 2011-03-19T09:37:12.297 | 2020-11-02T16:13:11.490 | 2014-04-20T15:26:01.210 | 22047 | null | [
"cohens-d"
] |
8488 | 2 | null | 8349 | 1 | null | If you only have two charts I would show the following pair. You are right to want to avoid percentages if some items have several errors, but you can show average errors per item which amounts to the same thing without the misleading impression, and could go over 1 without any need for an explanation of how a percent... | null | CC BY-SA 2.5 | null | 2011-03-19T10:40:15.893 | 2011-03-19T10:40:15.893 | null | null | 2958 | null |
8489 | 2 | null | 8477 | 3 | null | If the formula in the question is exactly how it is written in the book, then this is a bit of slack notation, with the ambiguous looking $f(.)$. The subscripts, while a bit ugly, are one way to make it more clear what the function represents (for $f(.)$ is essentially defined as two different things, which in "nit-pi... | null | CC BY-SA 2.5 | null | 2011-03-19T11:10:07.747 | 2011-03-19T11:10:07.747 | null | null | 2392 | null |
8490 | 1 | null | null | 3 | 620 | I'm trying to make sense of some data and get statistical results on them.
What I have is the following:
```
Subject TimeOfDay Test1 Test2 Test3
A 10:00 valA1 valA2 valA3
B 10:00 valB1 valB2 valB3
C 15:00 valC1 valC2 valC3
D 15:00 ... | What kind of statistical analysis should I do to aggregate these values? | CC BY-SA 2.5 | null | 2011-03-19T11:38:14.290 | 2011-03-20T18:42:55.053 | 2011-03-19T15:32:26.560 | null | 3791 | [
"correlation",
"multivariate-analysis",
"factor-analysis"
] |
8491 | 2 | null | 3542 | 6 | null | I cover table design in the seminars I offer. My sources are primarily Chapter 8 of Few’s Show Me the Numbers and a paper by Martin Koschat:
Koschat, Martin. 2005. “A Case for Simple Tables,” The American Statistician 59:1, 31-40. [https://doi.org/10.1198/000313005X21429](https://doi.org/10.1198/000313005X21429)
Also,... | null | CC BY-SA 4.0 | null | 2011-03-19T12:09:23.263 | 2019-09-10T19:22:57.187 | 2019-09-10T19:22:57.187 | 7290 | null | null |
8492 | 2 | null | 8483 | 2 | null | You will find help on allocating categorical variables with [UCLA's tutorials](http://www.ats.ucla.edu/stat/spss/dae/logit.htm).
```
logistic regression HIV with age sex
/categorical = sex.
```
You might also find help [here](http://www.childrens-mercy.org/stats/weblog2004/categorical.asp).
| null | CC BY-SA 2.5 | null | 2011-03-19T12:43:19.813 | 2011-03-19T12:43:19.813 | null | null | 1351 | null |
8495 | 2 | null | 8472 | 10 | null | I would say, based on your question, that there is no difference between the three tests. This is in the sense that you can always choose A, B, and C such that the same decision is arrived at regardless of what criterion you are using. Although you need to have the p-value be based on the same statistic (i.e. the Z-s... | null | CC BY-SA 2.5 | null | 2011-03-19T13:49:39.730 | 2011-03-19T13:49:39.730 | null | null | 2392 | null |
8496 | 5 | null | null | 0 | null | These guidelines are for those who are asking and those who would answer homework-related questions.
### They are rooted in two principles:
- It is okay to ask about homework. This site exists to help people learn and provide a standard repository for questions in statistics and machine learning, both simple and c... | null | CC BY-SA 3.0 | null | 2011-03-19T13:54:41.287 | 2011-03-19T13:54:41.287 | 2014-04-23T13:43:43.010 | -1 | 919 | null |
8497 | 4 | null | null | 0 | null | A routine question from a textbook, course, or test used for a class or self-study. This community's policy is to "provide helpful hints." | null | CC BY-SA 2.5 | null | 2011-03-19T13:54:41.287 | 2011-03-19T13:54:41.287 | 2011-03-19T13:54:41.287 | 919 | 919 | null |
8498 | 2 | null | 8462 | 0 | null | Your charts are a diurnal hourly-average bar chart, and a one-week daily-average bar chart, respectively.
| null | CC BY-SA 2.5 | null | 2011-03-19T15:02:19.393 | 2011-03-19T15:02:19.393 | null | null | 3794 | null |
8499 | 2 | null | 8455 | 2 | null | The underlying difficulty behind the question is that situations that have been anticipated, have generally been planned for, with mitigation measures in place. Which means that the situation should not even turn into a serious accident.
The serious accidents stem from unanticipated situations. Which means that you can... | null | CC BY-SA 2.5 | null | 2011-03-19T15:10:37.453 | 2011-03-19T15:10:37.453 | null | null | 3794 | null |
8500 | 2 | null | 8459 | 2 | null | I think that there might be a conceptual problem with this approach. If your piece of paper is not flat it is possible that a "kink" in the paper at a point with no ink dot might be higher than surrounding areas with ink dots. The proposed algorithm might inadvertently average away the very points of interest. Also "I ... | null | CC BY-SA 2.5 | null | 2011-03-19T15:40:13.427 | 2011-03-19T15:56:45.143 | 2011-03-19T15:56:45.143 | 226 | 226 | null |
8501 | 1 | null | null | 4 | 1503 | I'm using the following function to calculate Edwards R^2 (formula 19 in Edwards et al. 2008) of a mixed effects model (I hope the implementation is correct):
```
r2lmer <- function(model) {
require(aod) # need the aod package for wald.test function
if (class(model) != "mer") stop("mer object expected")
n <- m... | Variance explained of a mixed effects model in a new data set | CC BY-SA 2.5 | null | 2011-03-19T15:56:42.623 | 2011-04-18T10:01:20.853 | 2011-04-05T15:50:11.470 | 919 | 3795 | [
"r",
"mixed-model",
"variance",
"validation"
] |
8502 | 1 | 8684 | null | 6 | 2729 | I have two sets of coefficients from similar data taken at different times. What I want to do is combine the two sets of coefficients giving greater weight to the more most recent set.
The goal is building a predictive model. So say I have dataset A from 2009, and dataset B from 2010.
My coefficients for A are:
```
p... | Combining 2 sets of coefficients, weighting one of the sets | CC BY-SA 2.5 | null | 2011-03-19T16:32:07.477 | 2011-04-29T01:05:55.050 | 2011-04-29T01:05:55.050 | 3911 | 3491 | [
"time-series",
"multivariate-analysis",
"predictive-models"
] |
8503 | 2 | null | 8502 | 1 | null | There is no reason accounting for the use of convex linear combinations of coefficients in order to "average" two models.
At best, you could consider the three coefficients for each dataset are realizations of the same three random variables, and you would be interested in the distribution of each random variable.
What... | null | CC BY-SA 2.5 | null | 2011-03-19T16:40:18.300 | 2011-03-19T16:46:40.243 | 2011-03-19T16:46:40.243 | 1351 | 1351 | null |
8504 | 1 | null | null | 8 | 5197 | car packages's [ellipse function](http://finzi.psych.upenn.edu/R/library/car/html/Ellipses.html) asks for a `radius` parameter. In help says that is the "radius of circle generating the ellipse". Could you please tell me which circle is this?
Thank you very much
| Help in drawing confidence ellipse | CC BY-SA 2.5 | null | 2011-03-19T17:49:13.440 | 2011-03-19T19:40:46.057 | 2011-03-19T18:55:07.057 | null | 339 | [
"r",
"confidence-interval",
"multivariate-analysis"
] |
8505 | 1 | null | null | 23 | 9204 | A Poisson regression is a [GLM](http://en.wikipedia.org/wiki/Generalized_linear_model) with a log-link function.
An alternative way to model non-normally distributed count data is to preprocess by taking the log (or rather, log(1+count) to handle 0's). If you do a least-squares regression on log-count responses, is th... | Poisson regression vs. log-count least-squares regression? | CC BY-SA 3.0 | null | 2011-03-19T17:58:42.400 | 2011-08-25T22:23:22.477 | 2011-08-25T19:12:30.840 | 919 | 3799 | [
"regression",
"poisson-distribution",
"generalized-linear-model"
] |
8506 | 2 | null | 8505 | 25 | null | On the one hand, in a Poisson regression, the left-hand side of the model equation is the logarithm of the expected count: $\log(E[Y|x])$.
On the other hand, in a "standard" linear model, the left-hand side is the expected value of the normal response variable: $E[Y|x]$. In particular, the link function is the identity... | null | CC BY-SA 2.5 | null | 2011-03-19T18:27:09.653 | 2011-03-19T18:27:09.653 | null | null | 3019 | null |
8507 | 2 | null | 8504 | 4 | null | An ellipse can be parametrized as the affine image of any given circle. If we consider the unit circle:
$$x=a \cos (t)$$
$$y=b \sin (t)$$
```
ellipse(center, shape, radius, log="", center.pch=19, center.cex=1.5,
segments=51, add=TRUE, xlab="", ylab="",
col=palette()[2], lwd=2, fill=FALSE, fill.alpha=0.3, grid=TR... | null | CC BY-SA 2.5 | null | 2011-03-19T18:49:26.673 | 2011-03-19T19:40:46.057 | 2011-03-19T19:40:46.057 | 1351 | 1351 | null |
8508 | 2 | null | 8487 | 11 | null | According to [p238](http://books.google.com/books?id=cQxN792ttyEC&pg=PA238) of standard text on meta-analysis in social science [The Handbook of Research Synthesis](http://books.google.com/books?id=cQxN792ttyEC), the variance of Cohen's $d$ is
$$\left( \frac{n_1 + n_2}{n_1 n_2} + \frac{d^2}{2(n_1+n_2-2)}\right) \left(\... | null | CC BY-SA 2.5 | null | 2011-03-19T19:59:33.950 | 2011-03-19T20:05:45.363 | 2011-03-19T20:05:45.363 | 449 | 449 | null |
8509 | 2 | null | 8485 | 21 | null | I'd start with:
Casella, George; George, Edward I. (1992). "[Explaining the Gibbs sampler](http://www.jstor.org/stable/2685208)". The American Statistician 46 (3): 167–174. ([FREE PDF](http://biostat.jhsph.edu/~mmccall/articles/casella_1992.pdf))
>
Abstract: Computer-intensive algorithms, such as the Gibbs sampler, ha... | null | CC BY-SA 3.0 | null | 2011-03-19T20:19:38.393 | 2012-03-19T00:37:18.213 | 2012-03-19T00:37:18.213 | 183 | 449 | null |
8510 | 2 | null | 8485 | 12 | null | One online article that really helped me understand Gibbs Sampling is [Parameter estimation for text analysis](http://www.arbylon.net/publications/text-est.pdf) by Gregor Heinrich. It's not a general Gibbs sampling tutorial but it discusses it in terms of latent dirichlet allocation, a fairly popular Bayesian model for... | null | CC BY-SA 2.5 | null | 2011-03-19T21:18:56.360 | 2011-03-19T21:18:56.360 | null | null | 3167 | null |
8511 | 1 | null | null | 63 | 126468 | Christopher Manning's [writeup on logistic regression in R](http://nlp.stanford.edu/~manning/courses/ling289/logistic.pdf) shows a logistic regression in R as follows:
```
ced.logr <- glm(ced.del ~ cat + follows + factor(class),
family=binomial)
```
Some output:
```
> summary(ced.logr)
Call:
glm(formula = ced.del ~... | How to calculate pseudo-$R^2$ from R's logistic regression? | CC BY-SA 3.0 | null | 2011-03-19T22:44:06.767 | 2023-01-05T19:47:56.373 | 2022-02-18T15:37:58.850 | 11887 | 2849 | [
"r",
"logistic",
"likelihood",
"pseudo-r-squared"
] |
8512 | 1 | null | null | 3 | 69 | Suppose I have some stochastic process $X_t$. At each time $t$, I receive an estimated probability distribution for $x_t$, followed by an observation $x_t$. After receiving a set of observations ${x_1, \ldots, x_n}$, I want to go back and re-estimate the probability distribution for each $x_t$, $1 \le t \le n$. What ar... | Updating a set of estimated forecasts | CC BY-SA 2.5 | null | 2011-03-20T04:19:28.777 | 2011-03-20T04:19:28.777 | null | null | 1106 | [
"estimation",
"forecasting",
"stochastic-processes",
"smoothing"
] |
8513 | 1 | null | null | 13 | 6752 | Let's say $y$ is a linear function of $x$ and a dummy $d$. My hypothesis is that $d$ itself is like a hedonistic index of a vector of other variables, $Z$. I have support for this in a $MANOVA$ of $Z$ (i.e. $z_1$, $z_2$, ..., $z_n$) on $d$. Is there any way to test the equivalence of these two models:
Model 1: $y = b_0... | Test equivalence of non-nested models | CC BY-SA 2.5 | null | 2011-03-20T06:47:01.650 | 2013-06-25T10:34:46.157 | 2011-03-20T09:53:58.310 | 2645 | 3671 | [
"r",
"hypothesis-testing",
"regression",
"model-selection"
] |
8514 | 1 | null | null | 12 | 2851 | I am by no means good in statistics, but I think I have come to the right place.
My question is simple:
My problem consists of comparing the population of several states in a small country, but some states have a population of 3000,000 and some a population of 2,000.
I am painting it on a map, and the "intensity" of th... | How to make a good color intensity scale? | CC BY-SA 2.5 | null | 2011-03-20T07:38:30.500 | 2011-05-13T21:01:47.547 | 2011-03-20T10:11:32.580 | null | 3803 | [
"data-visualization"
] |
8515 | 1 | 89026 | null | 9 | 3905 | Positive stable distributions are described by four parameters: the skewness parameter $\beta\in[-1,1]$, the scale parameter $\sigma>0$, the location parameter $\mu\in(-\infty,\infty)$, and the so-called index parameter $\alpha\in(0,2]$. When $\beta$ is zero the distribution is symmetric around $\mu$, when it is positi... | The positive stable distribution in R | CC BY-SA 2.5 | null | 2011-03-20T07:49:43.677 | 2018-11-10T16:15:06.827 | 2018-11-10T16:15:06.827 | 11887 | 3019 | [
"r",
"stable-distribution"
] |
8516 | 2 | null | 8514 | 3 | null | You could divide by the total population. This would ensure that everything lies between 0 and 1. If the scales are still too disparate, consider a log scale.
| null | CC BY-SA 2.5 | null | 2011-03-20T08:08:21.577 | 2011-03-20T08:08:21.577 | null | null | 3786 | null |
8517 | 2 | null | 8514 | 5 | null | Good question, One solution is to rescale the colors to have them more uniformly distributed, or to a distribution with lower tails... but then your legend has to be clear enough because deforming the scale, somehow, is unfair...
For example, in R, rescaling a normal to a uniform . (what you have maybe goes more the o... | null | CC BY-SA 2.5 | null | 2011-03-20T08:10:04.853 | 2011-03-20T08:15:42.257 | 2011-03-20T08:15:42.257 | 223 | 223 | null |
8518 | 2 | null | 8358 | 1 | null | What time-lag might you expect between cases recorded, and fatality? What time-lag between start of treatment and impact on fatality rates?
If either of those numbers is much greater than one year, then there may be a case for aggregating all your data from first year of treatment impact (i.e. 1996+time to impact) to 2... | null | CC BY-SA 2.5 | null | 2011-03-20T09:03:55.500 | 2011-03-20T09:03:55.500 | null | null | 3794 | null |
8519 | 2 | null | 8513 | 8 | null | To begin with you have to define the equivalence concept. One may think that two models are equivalent when they do produce almost the same forecasting accuracy (this one would be relevant for time series and panel data), another one could be interested in if the fits from the model are close. The former is the object ... | null | CC BY-SA 3.0 | null | 2011-03-20T09:09:12.033 | 2013-06-25T10:34:46.157 | 2013-06-25T10:34:46.157 | 21054 | 2645 | null |
8520 | 2 | null | 665 | 4 | null | In probability, the distribution is known and knowable in advance - you start with a known probability distribution function (or similar), and sample from it.
In statistics, the distribution is unknown in advance. It may even be unknowable. Assumptions are hypothesised about the probability distribution behind observed... | null | CC BY-SA 2.5 | null | 2011-03-20T09:27:37.320 | 2011-03-20T09:27:37.320 | null | null | 3794 | null |
8521 | 1 | null | null | 11 | 225 | I have a set of systems where uncertainties accumulate within it. These aren't always purely additive - sometimes they are, sometimes they aren't. I've had some success in using fan-charts, bar charts with confidence-intervals, and box plots for communicating single items.
But how can I show how uncertainties accumulat... | What graphical methods are useful for visualising how uncertainties aggregate? | CC BY-SA 3.0 | null | 2011-03-20T09:36:05.143 | 2016-02-04T15:47:00.453 | 2015-09-29T22:07:37.863 | 22228 | 3794 | [
"data-visualization",
"confidence-interval",
"uncertainty"
] |
8522 | 1 | null | null | 3 | 310 | We're thinking of adding an interactive near real-time analytics functionality (a-la "Google Analytics") to a product Movie Recommender Engine.
We need to let the user interactively create analyses deciding on a case by case basis the analysis dimensions (e.g. by Genre, by Actor, by Publisher), metrics (e.g. Views, Pur... | Suggestions for embedded interactive analytical functionalities? | CC BY-SA 2.5 | null | 2011-03-20T12:30:45.973 | 2011-05-24T14:18:05.413 | 2011-03-20T15:53:55.847 | 930 | 3804 | [
"data-visualization",
"interactive-visualization",
"recommender-system"
] |
8523 | 2 | null | 2181 | 4 | null | If you look at [Paul Hewison's webpage](http://www.plymouth.ac.uk/staff/phewson), you can find his free book on Multivariate Statistics and R. Another free book is by Wolfgang Hardle and Leopold Simar. I have been
working my way through Johnson and Wichern, a book that has been used in the US for
over twenty years; you... | null | CC BY-SA 2.5 | null | 2011-03-20T12:49:47.597 | 2011-03-21T22:38:56.370 | 2011-03-21T22:38:56.370 | 3582 | 3805 | null |
8524 | 1 | null | null | 4 | 1259 | Here's what I know:
I have read the chapter (p347ff) in Agresti, 1990, regarding dependent two-way tables, and I believe I understand the basics. My problem is that Agresti's model-based approaches seem to rely on large-sample theory.
I have questions from 24 students where they rate something on a scale from 1-5. If ... | Is there an exact version of marginal homogeneity test? | CC BY-SA 2.5 | null | 2011-03-20T13:06:51.123 | 2011-03-20T20:52:23.870 | 2011-03-20T20:52:23.870 | null | null | [
"r",
"heteroscedasticity"
] |
8525 | 2 | null | 8514 | 2 | null | I feel awkward asking it, but are you really committed to using colour to portray a quantitative amount? Is there no way to put a bar in each state, whose height represents the quantity?
Another way might be to show the map with areas representing the geographic areas, together with a map where each state's area is pro... | null | CC BY-SA 2.5 | null | 2011-03-20T13:25:00.360 | 2011-03-20T13:25:00.360 | null | null | 3794 | null |
8526 | 1 | 8529 | null | 5 | 646 | I have a rather basic question about [Probabilistic Principal Component Analysis](http://research.microsoft.com/en-us/um/people/cmbishop/downloads/Bishop-PPCA-JRSS.pdf), which I am now trying to apply to a real-world problem.
In PPCA, the crucial assumption is that the generating process of the observations in $R^n$ i... | Question about probabilistic principal component analysis | CC BY-SA 2.5 | null | 2011-03-20T13:33:59.587 | 2011-03-21T15:11:04.680 | 2011-03-21T15:11:04.680 | 919 | 30 | [
"pca",
"dimensionality-reduction"
] |
8528 | 1 | 8550 | null | 9 | 2667 | First of all I'd like to apologize for the vague title, I couldn't really formulate a better one just now, please feel free to change, or advice me to change, the title to make it better fit the core of the question.
Now about the question itself, I have been working on a software in which I have come across the idea o... | How to use/interpret empirical distribution? | CC BY-SA 3.0 | null | 2011-03-20T14:07:14.917 | 2017-09-18T11:18:10.080 | 2017-09-18T11:18:10.080 | 60613 | 3014 | [
"distributions",
"sampling",
"java"
] |
8529 | 2 | null | 8526 | 6 | null | Unless I'm missing something, I think $U_q U_q' \neq I$ here (almsot surely, at least). The columns of $U_q$ are orthogonal, not the rows since the last $n-q$ columns are removed.
| null | CC BY-SA 2.5 | null | 2011-03-20T14:19:44.563 | 2011-03-20T14:19:44.563 | null | null | 26 | null |
8530 | 2 | null | 8524 | 5 | null | 1: `mh_test()` is an `S3` generic function, you can check what methods it has using `methods("mh_test")`. To show the source of a non-visible method, you can use `getAnywhere()` or `getS3method()`:
```
library(coin) # for mh_test()
methods("mh_test") # available methods for mh_test(),... | null | CC BY-SA 2.5 | null | 2011-03-20T14:40:12.293 | 2011-03-20T16:35:29.667 | 2011-03-20T16:35:29.667 | 1909 | 1909 | null |
8531 | 2 | null | 8455 | 1 | null | To answer the pure probabilistic question that J Presley presented, using bayer's notation (p=probability of an item failing), the the probability of at least one element failing is 1-P(none fail)= 1-(1-p)^n. This type of calculation is common in system reliability where a bunch of components are linked in parallel, so... | null | CC BY-SA 2.5 | null | 2011-03-20T15:18:34.720 | 2011-03-20T15:18:34.720 | null | null | 1945 | null |
8532 | 2 | null | 8522 | 1 | null | I love interactive visualization software like Spotfire and Tableau because it is easy to use and very insightful. My MBA students also become addicted.
I am more familiar with Spotfire, so I can say that they have a nice solution (Spotfire Silver) that allows you to create a dashboard of visualizations and post it to ... | null | CC BY-SA 2.5 | null | 2011-03-20T15:26:14.557 | 2011-03-20T15:26:14.557 | null | null | 1945 | null |
8534 | 2 | null | 8515 | 6 | null | What I think is happening is that in the output `delta` may be reporting an internal location value, while in the input `delta` is describing the shift. [There seems to be a similar issue with `gamma` when `pm=2`.] So if you try increasing the shift to 2
```
> dstable(4, alpha=0.4, beta=1, gamma=0.4, delta=2, pm=1)
[1... | null | CC BY-SA 2.5 | null | 2011-03-20T15:45:20.570 | 2011-03-20T15:45:20.570 | null | null | 2958 | null |
8536 | 2 | null | 665 | 72 | null | It's misleading to simply say that statistics is simply the inverse of probability. Yes, statistical questions are questions of inverse probability, but they are ill-posed inverse problems, and this makes a big difference in terms of how they are addressed.
Probability is a branch of pure mathematics--probability ques... | null | CC BY-SA 3.0 | null | 2011-03-20T16:02:25.653 | 2016-03-25T04:33:28.400 | 2016-03-25T04:33:28.400 | 108339 | 3567 | null |
8537 | 2 | null | 2181 | 6 | null | Hands down best basic text on multivariate regression is (still) Cohen, J., Cohen, P., West, S.G. & Aiken, L.S. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, (L. Erlbaum Associates, Mahwah, N.J., 2003).
Cohen made his name in statistics yet was a psychologist; still if you want social ps... | null | CC BY-SA 2.5 | null | 2011-03-20T16:20:26.003 | 2011-03-20T16:33:12.413 | 2011-03-20T16:33:12.413 | 11954 | 11954 | null |
8538 | 2 | null | 8501 | 2 | null | I tend to be more and more convinced that this just generally isn't a good idea because the meaning the R^2 isn't really exactly the same as in a conventional linear regression. As such, one always runs into interpretation issues and it often distracts from the meat of the story. Time spent writing a good description ... | null | CC BY-SA 2.5 | null | 2011-03-20T18:11:16.920 | 2011-03-20T18:11:16.920 | null | null | 601 | null |
8539 | 2 | null | 8514 | 6 | null | I'm sorry, but to me it sounds like you are trying to fix what isn't broken. In fact, you might even be trying to break what isn't broken. When you have a quantitative variable (here, population) that spans a wide range, then whatever metric you use to represent it should also span a wide range.
But for all things re... | null | CC BY-SA 2.5 | null | 2011-03-20T18:38:25.820 | 2011-03-20T18:38:25.820 | null | null | 686 | null |
8540 | 2 | null | 8490 | 2 | null | If you only have three or four people, then the right test is IOTT - the inter-ocular trauma test. That is, it hits you between the eyes. To allow the data to hit you properly, I would recommend graphics. In particular, I'd put time on the x-axis, score on the y-axis, and put lines for each person.
| null | CC BY-SA 2.5 | null | 2011-03-20T18:42:55.053 | 2011-03-20T18:42:55.053 | null | null | 686 | null |
8541 | 1 | 8607 | null | 5 | 414 | I've been trying to get my hands on a substantial resource for using Gibbs sampling in hybrid Bayesian networks, that is, networks with both continuous and discrete variables.
So far I can't say I have succeeded. I'm interested in hybrid networks where there are no constraints regarding discrete children having contin... | Resources about Gibbs sampling in hybrid Bayesian networks | CC BY-SA 3.0 | null | 2011-03-20T19:09:39.007 | 2016-05-01T20:20:44.297 | 2016-05-01T20:20:44.297 | 7290 | 3280 | [
"machine-learning",
"bayesian",
"references",
"gibbs"
] |
8543 | 2 | null | 8358 | 3 | null | I don't know why I took the time to answer this. Is it because I can or maybe it's because DrWho seems to think it is very important. In either case ....
Though well intentioned
“Time series expert modeler of IBM SPSS Forecast v19 was used. Both exponential smoothening models and ARIMA models were examined.Outliers wer... | null | CC BY-SA 2.5 | null | 2011-03-20T20:31:57.940 | 2011-03-20T20:31:57.940 | null | null | 3382 | null |
8544 | 2 | null | 8515 | 6 | null | Also of note: Martin Maechler just refactored the code for the stable distributed and added some improvements.
His new package [stabledist](http://cran.r-project.org/package=stabledist) will be used by fBasics as well, so you may want to give this a look as well.
| null | CC BY-SA 2.5 | null | 2011-03-20T20:50:31.327 | 2011-03-20T20:50:31.327 | null | null | 334 | null |
8545 | 1 | null | null | 4 | 7984 | I have some problems in using (and finding) the Chow test for structural breaks in a regression analysis using R. I want to find out if there are some structural changes including another variable (represents 3 spatial subregions).
Namely, is the regression with the subregions better than the overall model. Therefore I... | Identifying structural breaks in regression with Chow test | CC BY-SA 2.5 | 0 | 2011-03-20T20:54:24.877 | 2011-03-21T12:39:22.767 | 2011-03-21T12:39:22.767 | 1390 | null | [
"r",
"chow-test",
"structural-change"
] |
8546 | 2 | null | 8456 | 2 | null | Simple answer:
Select one set of X and Y values, and create your XY chart.
Copy the second set of X and Y values, select the chart, and use paste special to add the data as a new series.
| null | CC BY-SA 2.5 | null | 2011-03-20T21:41:48.500 | 2011-03-20T21:41:48.500 | null | null | null | null |
8547 | 2 | null | 8545 | 5 | null | The [strucchange](http://cran.r-project.org/web/packages/strucchange/index.html) package contains Chow and F tests for structural changes in regression models. The package comes with a vignette which shows how to use the package.
| null | CC BY-SA 2.5 | null | 2011-03-20T21:51:03.190 | 2011-03-20T21:51:03.190 | null | null | 1390 | null |
8548 | 2 | null | 8541 | 0 | null | I think this is still an open research question and there has been little consensus on the best way to do this.
| null | CC BY-SA 2.5 | null | 2011-03-20T22:23:16.703 | 2011-03-20T22:23:16.703 | null | null | 3816 | null |
8549 | 2 | null | 6033 | 4 | null | There are a number of ways that "a structural break" may occur.
If there is a change in the Intercept or a change in Trend in "the latter portion of the time series" then one would be better suited to perform Intervention Detection (N.B. this is the empirical identification of the significant impact of an unspecified D... | null | CC BY-SA 2.5 | null | 2011-03-21T00:08:22.847 | 2011-04-01T09:08:51.430 | 2011-04-01T09:08:51.430 | 3382 | 3382 | null |
8550 | 2 | null | 8528 | 5 | null | Empirical distributions are used all the time for inference so you're definitely on the right track! One of the most common use of empirical distributions is for bootstrapping. In fact, you don't even have to use any of the machinery you've described above. In an nutshell, you make many draws (with replacement) from th... | null | CC BY-SA 2.5 | null | 2011-03-21T02:15:26.610 | 2011-03-21T08:29:02.110 | 2011-03-21T08:29:02.110 | 2116 | 3786 | null |
8551 | 1 | null | null | 2 | 3141 | What do you call a curve that is just the first half of a bell curve. For example, let's say in a typical bell curve of letter grades, a few students get F grades most get C grades and just a few get A grades.
I'd like a curve that is the first half of the bell curve so that a few students get F grades and the most co... | What do you call just the first half of a bell curve? | CC BY-SA 2.5 | null | 2011-03-21T03:31:20.583 | 2017-05-26T01:00:50.850 | null | null | 3820 | [
"distributions"
] |
8552 | 2 | null | 8551 | 7 | null | A "bell curve" in the non-technical sense could refer to one of a family of statistical distributions which are bell-shaped. In the context of grading I've only ever seen the normal distribution (and it is by far the most common in general), but others include the logistic, t, etc. The [half-normal distribution](http... | null | CC BY-SA 2.5 | null | 2011-03-21T03:43:56.787 | 2011-03-22T05:20:15.463 | 2011-03-22T05:20:15.463 | 2975 | 2975 | null |
8553 | 2 | null | 1556 | 10 | null | Why stop at $t$-tests?
You can think of two variables being uncorrelated as two orthogonal vectors, exactly like the $x$ and $y$ axes in a two dimensional Cartesian coordinate system.
When either of two vectors, let's say $\mathbf{x}$ and $\mathbf{y}$ is correlated with the other, there will be a certain part of x that... | null | CC BY-SA 3.0 | null | 2011-03-21T04:16:34.817 | 2012-03-24T22:50:53.610 | 2012-03-24T22:50:53.610 | 2660 | 2660 | null |
8555 | 5 | null | null | 0 | null | The [Pearson correlation](http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient) between two random variables $X$ and $Y$ is defined as
$$ {\rm cor}(X,Y) = \frac{ E(XY) - E(X)E(Y) }{ \sqrt{ {\rm var}(X) {\rm var}(Y) } }$$
and is bounded between $-1$ (perfect negative linear relationship) and $1$ (... | null | CC BY-SA 4.0 | null | 2011-03-21T04:30:19.377 | 2022-09-04T18:17:14.293 | 2022-09-04T18:17:14.293 | 919 | 4856 | null |
8556 | 4 | null | null | 0 | null | A measure of the degree of linear association among a pair of variables. | null | CC BY-SA 3.0 | null | 2011-03-21T04:30:19.377 | 2012-04-23T01:23:09.580 | 2012-04-23T01:23:09.580 | 919 | 2660 | null |
8557 | 1 | null | null | 14 | 15869 | The whole point of AIC or any other information criterion is that less is better. So if I have two models M1: y = a0 + XA + e and M2: y = b0 + ZB + u, and if the AIC of the first (A1) is less than that of the second (A2), then M1 has a better fit from the information theory standpoint. But is there any cutoff benchmark... | Testing the difference in AIC of two non-nested models | CC BY-SA 2.5 | null | 2011-03-21T04:57:51.157 | 2013-06-25T10:38:20.780 | 2011-03-21T11:28:01.733 | 3671 | 3671 | [
"regression",
"aic"
] |
8558 | 2 | null | 8557 | 15 | null | Is the question of curiosity, i.e. you are not satisfied by my answer [ here ](https://stats.stackexchange.com/questions/8513/test-equivalence-of-non-nested-models/8519#8519)? If not...
The further investigation of this tricky question showed that there do exist a commonly used rule-of-thumb, that states two models are... | null | CC BY-SA 3.0 | null | 2011-03-21T05:56:28.850 | 2013-06-25T10:38:20.780 | 2020-06-11T14:32:37.003 | -1 | 2645 | null |
8559 | 1 | null | null | 4 | 136 | Related to [my previous question](https://stats.stackexchange.com/questions/8236/how-to-find-relationships-between-different-types-of-events-defined-by-their-2d), I have a dataset of 2D points with an associated label (this label can take 6 different values). As suggested in the answers to my other question, this can b... | How can I rediscretize my data? | CC BY-SA 2.5 | null | 2011-03-21T07:48:30.303 | 2011-03-21T08:57:00.910 | 2017-04-13T12:44:20.840 | -1 | 3699 | [
"pca",
"multivariate-analysis",
"normalization"
] |
8560 | 2 | null | 8557 | 8 | null | I think this may be an attempt to get what you don't really want.
Model selection is not a science. Except in rare circumstances, there is no one perfect model, or even one "true" model; there is rarely even one "best" model. Discussions of AIC vs. AICc vs BIC vs. SBC vs. whatever leave me somewhat nonplussed. I thi... | null | CC BY-SA 2.5 | null | 2011-03-21T10:13:20.787 | 2011-03-21T10:13:20.787 | null | null | 686 | null |
8561 | 1 | null | null | 5 | 2330 | I wonder if it possible to include a mediation effect in multinomial logistic regression. I have a categorical (3 categories) outcome variable and four predictors (all continuous). I expect one of the predictors (X1) to mediate the relationship between the outcome variable and another predictor (X2). I also expect dire... | How to assess mediation effect in multinomial logistic regression? | CC BY-SA 2.5 | null | 2011-03-21T11:28:58.193 | 2011-03-21T11:37:40.173 | 2011-03-21T11:37:40.173 | 930 | null | [
"logistic",
"spss",
"multinomial-distribution",
"mediation"
] |
8562 | 1 | null | null | 4 | 381 | I have a completely within-subjects design with 3 independent variables:
- Trial type (3 levels)
- Task order (2 levels)
- Modality (3 levels)
However, for one of my levels of Trial type, the Task order and Modality levels are redundant (because it is essentially a baseline measurement).
Ideally, I'd like to run a... | How to deal with a specific case of unbalanced within-subjects design? | CC BY-SA 2.5 | null | 2011-03-21T11:49:35.680 | 2011-04-13T14:22:25.767 | 2011-03-21T12:28:42.143 | 930 | 3822 | [
"anova",
"repeated-measures"
] |
8566 | 1 | 8616 | null | 6 | 1445 | Actually this question may be simple for you, but I need to learn the correct answer.
If I remove misclassified instances from data set with Naive Bayes (it gives minimum FP rate) and then train logistic classifier on this filtered data set, will it overfit or not?
Thanks in advance.
| Overfit by removing misclassified objects? | CC BY-SA 2.5 | null | 2011-03-21T13:07:22.040 | 2011-11-24T10:38:49.250 | 2011-03-21T13:53:24.840 | null | 2170 | [
"machine-learning",
"naive-bayes"
] |
8567 | 1 | null | null | 5 | 2293 | I am trying to use DLM to model a time series. Candiate model includes local level, local trend and local trend with seasonal part. I do not know how to do model selection. Can AIC be calculated? I found no function in the R package [dlm](http://cran.r-project.org/web/packages/dlm/index.html).
| How to do model selection in dynamic linear model? | CC BY-SA 2.5 | null | 2011-03-21T13:29:38.997 | 2016-11-29T10:48:52.983 | 2011-03-21T13:49:35.403 | null | null | [
"r",
"time-series",
"model-selection",
"dlm"
] |
8568 | 1 | 8838 | null | 5 | 135 | The research group I work for have developed a theoretical growth model for a particular species of fish. The idea is that if you provide some initial starting values for the model you then generate an expected growth curve along with 95% confidence bands. To extend the model we would like to be able to update the mode... | Updating/ adjusting theoretical growth curves when raw data becomes available | CC BY-SA 4.0 | null | 2011-03-21T15:08:27.397 | 2020-01-25T02:34:44.757 | 2020-01-25T02:34:44.757 | 11887 | 3136 | [
"regression",
"time-series",
"forecasting",
"growth-model"
] |
8569 | 1 | null | null | 2 | 288 | I am trying to test importance sampling for a simple a Wiener process $W_t$ in R:
```
set.seed(123)
Z <- matrix(rnorm(12*1000),12,1000)
W <- apply(Z,2,cumsum) #Wiener process simulated 1000 times for 12 periods
B <- W-(1:12) #Brownian motion with drift -1
w <- exp(-W[12,]) #Radon-Nikodym derivative (actually w <- exp(-... | Change of measures with Wiener process | CC BY-SA 2.5 | null | 2011-03-21T15:10:02.380 | 2011-03-21T15:46:03.440 | 2011-03-21T15:46:03.440 | 1443 | 1443 | [
"r",
"monte-carlo"
] |
8570 | 1 | 8574 | null | 11 | 808 | I'm looking for a solid reference (or references) on numerical optimization techniques aimed at statisticians, that is, it would apply these methods to some standard inferential problems (eg MAP/MLE in common models). Things like gradient descent (straight and stochastic), EM and its spinoffs/generalizations, simulated... | References on numerical optimization for statisticians | CC BY-SA 2.5 | null | 2011-03-21T15:24:18.457 | 2015-04-22T14:02:28.933 | 2011-04-30T12:04:29.620 | 930 | 26 | [
"estimation",
"references",
"optimization"
] |
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