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github | auranic/Elastic-principal-graphs-master | PrimitiveElasticGraphEmbedmentDeb.m | .m | Elastic-principal-graphs-master/ElPiGraph/test_code/PrimitiveElasticGraphEmbedmentDeb.m | 15,158 | utf_8 | 718357f7d1e02ef968e6df1499a93589 | function [EmbeddedNodePositions, ElasticEnergy, partition, dists,...
MSE, EP, RP] = PrimitiveElasticGraphEmbedment(X, NodePositions,...
ElasticMatrix, varargin)
% This is the core function for fitting a primitive elastic graph to the data
% Inputs
% X - is the n-by-m data matrix. Each row corresponds to one d... |
github | auranic/Elastic-principal-graphs-master | project_point_onto_graph.m | .m | Elastic-principal-graphs-master/ElPiGraph/test_code/projectTest/project_point_onto_graph.m | 2,400 | utf_8 | 2170675df886403d891779bf0aaf862c | function [MSE, X_projected, EdgeIndices, ProjectionValues] =...
project_point_onto_graph(X, NodePositions, Edges, partition)
%% This function calculates piece-wise linear projection of a dataset onto
%% the graph defined by NodePositions and Edges
% Input arguments:
% X - is the n-by-m data matrix. Each row corre... |
github | auranic/Elastic-principal-graphs-master | PrimitiveElasticGraphEmbedment.m | .m | Elastic-principal-graphs-master/ElPiGraph/test_code/testing280817/PrimitiveElasticGraphEmbedment.m | 7,998 | utf_8 | 3fa96b7e730e056662f004273713ce27 | function [EmbeddedNodePositions, ElasticEnergy, partition, MSE,EP,RP] =...
PrimitiveElasticGraphEmbedment(X, NodePositions, ElasticMatrix, varargin)
% This is the core function fitting a primitive elastic graph to the data
%Inputs
% X - is the n-by-m data matrix.
% NodePositions - is k-by-m matrix of positions ... |
github | auranic/Elastic-principal-graphs-master | PartitionData.m | .m | Elastic-principal-graphs-master/ElPiGraph/test_code/testing280817/PartitionData.m | 1,704 | utf_8 | 5782b50504622a73201d240a079a96f5 |
function [partition, dists] = ...
PartitionData(X, NodePositions, MaxBlockSize, SquaredX, TrimmingRadius)
%%%%%%%%%%%%%%%%%%%%%%%
%% Partition the data by proximity to graph nodes (same step as in K-means EM procedure)
%%%%%%%%%%%%%%%%%%%%%%%
%
%Inputs:
% X is n-by-m matrix of datapints with one data point per r... |
github | auranic/Elastic-principal-graphs-master | associate.m | .m | Elastic-principal-graphs-master/ElPiGraph/test_code/benchmarking/associate.m | 3,373 | utf_8 | e436b5393406802ee028ff1e8fdb0651 | function ass = associate(data, k, N, meth)
%This function present standard kmeans clusterisation with two possible
%methods of calculations.
%Input features
% data is n-by-m matrix of data points. Each row perpresents one
% observations.
% k is required number of centroids
% N is required number of distanc... |
github | auranic/Elastic-principal-graphs-master | kmeans.m | .m | Elastic-principal-graphs-master/ElPiGraph/test_code/benchmarking/kmeans.m | 3,913 | utf_8 | 2b752ae21dc1b6a58eb2ebad9877a679 | function centroids = kmeans(data, k, meth)
%This function present standard kmeans clusterisation with two possible
%methods of calculations.
%Input features
% data is n-by-m matrix of data points. Each row perpresents one
% observations.
% k is required number of centroids
% meth is method of distances cal... |
github | auranic/Elastic-principal-graphs-master | TF1_mutualinhibition_TF2_cofactorTF3.m | .m | Elastic-principal-graphs-master/ElPiGraph/simulations/tf_dynamics/TF1_mutualinhibition_TF2_cofactorTF3.m | 649 | utf_8 | f7132b15518b2755f07a2666e0e5ec46 | function [TF_dynamics,t] = TF1_mutualinhibition_TF2_cofactorTF3(parameters,tspan,initial_conditions)
%% Example of a function generating TF dynamics
%
%
[t,TF_dynamics] = ode23(@(t,y) func(t,y,parameters), tspan, initial_conditions);
end
function dydt = func(t,y,parameters)
ks1 = parameters(1,1);
ks2 = parameters... |
github | auranic/Elastic-principal-graphs-master | TF1_inhibits_TF2.m | .m | Elastic-principal-graphs-master/ElPiGraph/simulations/tf_dynamics/TF1_inhibits_TF2.m | 449 | utf_8 | 9fe9abce4b58e8a172cb81218ec5f0b2 | function [TF_dynamics,t] = TF1_inhibits_TF2(parameters,tspan,initial_conditions)
%% Example of a function generating TF dynamics
%
%
[t,TF_dynamics] = ode23(@(t,y) func(t,y,parameters), tspan, initial_conditions);
end
function dydt = func(t,y,parameters)
ks1 = parameters(1,1);
ks2 = parameters(2,1);
kd1 = paramet... |
github | auranic/Elastic-principal-graphs-master | TF1_mutualinhibition_TF2.m | .m | Elastic-principal-graphs-master/ElPiGraph/simulations/tf_dynamics/TF1_mutualinhibition_TF2.m | 521 | utf_8 | 79ab792e5afe33577ebe9c921110f144 | function [TF_dynamics,t] = TF1_mutualinhibition_TF2(parameters,tspan,initial_conditions)
%% Example of a function generating TF dynamics
%
%
[t,TF_dynamics] = ode23(@(t,y) func(t,y,parameters), tspan, initial_conditions);
end
function dydt = func(t,y,parameters)
ks1 = parameters(1,1);
ks2 = parameters(2,1);
kd1 =... |
github | vancesteven/OceanColumnConvection-master | swEOS_chooser.m | .m | OceanColumnConvection-master/swEOS_chooser.m | 5,693 | utf_8 | 6f42fe02c4dbe64912cdd330d614960d | function swEOS = swEOS_chooser(EOStype)
% swEOS Seawater Equation of state
%=========================================================================
%
% USAGE: swEOS = swEOS_chooser(EOStype)
% DESCRIPTION:
% Set the seawater equation of state to be used by the column-convect
% model. Input units for all fun... |
github | vancesteven/OceanColumnConvection-master | mgso4_ptmp.m | .m | OceanColumnConvection-master/mgso4interp/mgso4_ptmp.m | 1,624 | utf_8 | 5f409b9e245380b329fc117afd9b11d9 |
function PT = mgso4_ptmp(S,T,P,PR)
% MGSO4_PTMP Potential temperature
%===========================================================================
%
% USAGE: ptmp = mgso4_ptmp(S,T,P,PR)
%
% DESCRIPTION:
% Calculates potential temperature for MgSO4 brines, using UNESCO 1983
% method from terrestrial literat... |
github | surban/DeepBraille-master | matlab_install.m | .m | DeepBraille-master/Matlab/GPstuff/matlab_install.m | 3,438 | utf_8 | 4b7e178ff9eaa47c32ba615c65eba469 | function matlab_install(SuiteSparse_path)
% Matlab function to compile all the c-files to mex in the GPstuff toolbox.
%
% Some of the sparse GP functionalities in the toolbox require
% SuiteSparse toolbox by Tim Davis:
% http://www.cise.ufl.edu/research/sparse/SuiteSparse/current/SuiteSparse/
%
% This package i... |
github | surban/DeepBraille-master | m2kml.m | .m | DeepBraille-master/Matlab/GPstuff/misc/m2kml.m | 1,807 | utf_8 | 6ab3b7f8f1cac70d62e51ac3b881ffdf | % M2KML Converts GP prediction results to a KML file
%
% Input:
% input_file - Name of the .mat file containing GP results
% cellsize - Size of the cells in meters
% output_file - Name of the output file without the file extension!
% If output is not given the name of the input f... |
github | surban/DeepBraille-master | mapcolor2.m | .m | DeepBraille-master/Matlab/GPstuff/misc/mapcolor2.m | 1,972 | utf_8 | f7dbf666bab483d8ed612da8f6957629 |
function map = mapcolor2(A, breaks)
%MAPCOLOR2 Create a blue-gray-red colormap.
% MAPCOLOR2(A, BREAKS), when A is a matrix and BREAKS a vector, returns a
% colormap that can be used as a parameter in COLORMAP function. BREAKS
% has to contain six break values for a 7-class colormap. The break
% values define ... |
github | surban/DeepBraille-master | fminlbfgs.m | .m | DeepBraille-master/Matlab/GPstuff/optim/fminlbfgs.m | 36,309 | utf_8 | 12a2dd6e67c20d564a7d29b912af502e | function [x,fval,exitflag,output,grad]=fminlbfgs(funfcn,x_init,optim)
%FMINLBFGS finds a local minimum of a function of several variables.
% This optimizer is developed for image registration
% methods with large amounts of unknown variables.
%
% Description
% Optimization methods supported:
% ... |
github | surban/DeepBraille-master | prior_gaussian.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_gaussian.m | 3,574 | windows_1250 | 75e7bb2ecce3c1914ee64e07e6d0d01f | function p = prior_gaussian(varargin)
%PRIOR_GAUSSIAN Gaussian prior structure
%
% Description
% P = PRIOR_GAUSSIAN('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates Gaussian prior structure in which the named
% parameters have the specified values. Any unspecified
% parameters are set to de... |
github | surban/DeepBraille-master | prior_sqrtunif.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_sqrtunif.m | 1,684 | windows_1250 | 9a94dd07ac6320b5829f35fd2f036efc | function p = prior_sqrtunif(varargin)
%PRIOR_SQRTUNIF Uniform prior structure for the square root of the parameter
%
% Description
% P = PRIOR_SQRTUNIF creates uniform prior structure for the
% square root of the parameter.
%
% See also
% PRIOR_*
%
% Copyright (c) 2009 Jarno Vanhatalo
% Copyright... |
github | surban/DeepBraille-master | normtrand.m | .m | DeepBraille-master/Matlab/GPstuff/dist/normtrand.m | 1,912 | utf_8 | 8420418c944aa575ac4f7577538f089d | function result = normtrand(mu,sigma2,left,right)
%NORMTRAND random draws from a normal truncated to (left,right) interval
% ------------------------------------------------------
% USAGE: y = normtrand(mu,sigma2,left,right)
% where: mu = mean (nobs x 1)
% sigma2 = variance (nobs x 1)
% left = left trunc... |
github | surban/DeepBraille-master | prior_sqinvunif.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_sqinvunif.m | 1,674 | utf_8 | ca61346b925c7dd4d60852d541184b94 | function p = prior_sqinvunif(varargin)
%PRIOR_SQINVUNIF Uniform prior structure for the square inverse of the parameter
%
% Description
% P = PRIOR_SQINVUNIF creates uniform prior structure for the
% square inverse of the parameter.
%
% See also
% PRIOR_*
%
% Copyright (c) 2009 Jarno Vanhatalo
% ... |
github | surban/DeepBraille-master | prior_sqrtinvunif.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_sqrtinvunif.m | 1,759 | windows_1250 | bef7189045403a9f0458482b63918979 | function p = prior_sqrtinvunif(varargin)
%PRIOR_INVSQRTUNIF Uniform prior structure for the square root of inverse of the parameter
%
% Description
% P = PRIOR_INVSQRTUNIF creates uniform prior structure for the
% square root of inverse of the parameter.
%
% See also
% PRIOR_*
%
% Copyright (c) 2... |
github | surban/DeepBraille-master | prior_logunif.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_logunif.m | 1,637 | windows_1250 | 865dc15b1df8b93e27eebb3b013353a0 | function p = prior_logunif(varargin)
%PRIOR_LOGUNIF Uniform prior structure for the logarithm of the parameter
%
% Description
% P = PRIOR_LOGUNIF creates uniform prior structure for the
% logarithm of the parameter.
%
% See also
% PRIOR_*
%
% Copyright (c) 2009 Jarno Vanhatalo
% Copyright (c) 20... |
github | surban/DeepBraille-master | prior_sqinvsinvchi2.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_sqinvsinvchi2.m | 4,380 | windows_1250 | 35766f18c3161f0ada89a8de52c19c2b | function p = prior_sqinvsinvchi2(varargin)
%PRIOR_SQINVSINVCHI2 Scaled-Inv-Chi^2 prior structure for square inverse of
% the parameter
%
% Description
% P = PRIOR_SQINVSINVCHI2('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates Scaled-Inv-Chi^2 prior structure for square inverse of
% ... |
github | surban/DeepBraille-master | prior_loggaussian.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_loggaussian.m | 3,905 | windows_1250 | bb91cf7abadec50b9d76b9d62ff2322f | function p = prior_loggaussian(varargin)
%PRIOR_LOGGAUSSIAN Log-Gaussian prior structure
%
% Description
% P = PRIOR_LOGGAUSSIAN('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates Log-Gaussian prior structure in which the named
% parameters have the specified values. Any unspecified
% paramet... |
github | surban/DeepBraille-master | prior_invgamma.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_invgamma.m | 3,717 | windows_1250 | 8e9bd40defd43709f7c441cfa0511166 | function p = prior_invgamma(varargin)
%PRIOR_INVGAMMA Inverse-Gamma prior structure
%
% Description
% P = PRIOR_INVGAMMA('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates inverse-Gamma prior structure in which the named
% parameters have the specified values. Any unspecified parameters
% are... |
github | surban/DeepBraille-master | prior_t.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_t.m | 5,197 | windows_1250 | fd4443cc21a52597ce8898752a2742b7 | function p = prior_t(varargin)
%PRIOR_T Student-t prior structure
%
% Description
% P = PRIOR_T('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates Student's t-distribution prior structure in which the
% named parameters have the specified values. Any unspecified
% parameters are set to defaul... |
github | surban/DeepBraille-master | prior_logt.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_logt.m | 4,985 | windows_1250 | 4c5ab93ffc0895f3724be262dc6eac6a | function p = prior_logt(varargin)
%PRIOR_LOGT Student-t prior structure for the log of the parameter
%
% Description
% P = PRIOR_LOGT('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates for the log of the parameter Student's t-distribution
% prior structure in which the named parameters have the
% ... |
github | surban/DeepBraille-master | prior_invt.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_invt.m | 5,131 | windows_1250 | 392f35226653e1921a3481943678c531 | function p = prior_invt(varargin)
%PRIOR_INVT Student-t prior structure for the inverse of the parameter
%
% Description
% P = PRIOR_INVT('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates for the inverse of the parameter Student's
% t-distribution prior structure in which the named parameters
% h... |
github | surban/DeepBraille-master | prior_unif.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_unif.m | 1,374 | utf_8 | e364b4ece656594bcc8a014c97440c32 | function p = prior_unif(varargin)
%PRIOR_UNIF Uniform prior structure
%
% Description
% P = PRIOR_UNIF creates uniform prior structure.
%
% See also
% PRIOR_*
%
% Copyright (c) 2009 Jarno Vanhatalo
% Copyright (c) 2010 Aki Vehtari
% This software is distributed under the GNU General Public
% L... |
github | surban/DeepBraille-master | prior_gamma.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_gamma.m | 3,675 | windows_1250 | 99b2fba5943d18cc3b028ce2f156c5d4 | function p = prior_gamma(varargin)
%PRIOR_GAMMA Gamma prior structure
%
% Description
% P = PRIOR_GAMMA('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates Gamma prior structure in which the named parameters
% have the specified values. Any unspecified parameters are set
% to default values.
%
% P... |
github | surban/DeepBraille-master | prior_sqinvlogunif.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_sqinvlogunif.m | 1,767 | windows_1250 | 8ecb33e816f4958821f4ad00c392aa48 | function p = prior_sqinvlogunif(varargin)
%PRIOR_SQINVLOGUNIF Uniform prior structure for the log of the square inverse of parameter
%
% Description
% P = PRIOR_SQINVLOGUNIF creates uniform prior structure for the
% log of the square inverse of the parameter.
%
% See also
% PRIOR_*
%
% Copyright ... |
github | surban/DeepBraille-master | prior_loglogunif.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_loglogunif.m | 1,598 | utf_8 | b0dbffe2f3dbd120b541613c657b12e3 | function p = prior_loglogunif(varargin)
%PRIOR_LOGLOGUNIF Uniform prior structure for the log-log of the parameter
%
% Description
% P = PRIOR_LOGLOGUNIF creates uniform prior structure for the
% log-log of the parameters.
%
% See also
% PRIOR_*
%
% Copyright (c) 2009 Jarno Vanhatalo
% Copyright ... |
github | surban/DeepBraille-master | prior_sqrtinvt.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_sqrtinvt.m | 5,138 | windows_1250 | 9ab3499a4beb80dd2191448ff802e970 | function p = prior_sqrtinvt(varargin)
%PRIOR_SQRTINVT Student-t prior structure for the square root of inverse of the parameter
%
% Description
% P = PRIOR_SQRTINVT('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates for square root of inverse of the parameter Student's
% t-distribution prior structur... |
github | surban/DeepBraille-master | prior_sqinvgamma.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_sqinvgamma.m | 4,153 | windows_1250 | fd592709b4f238cab1bf0a79f4fce609 | function p = prior_sqinvgamma(varargin)
%PRIOR_SQINVGAMMA Inverse-Gamma prior structure for square inverse of the parameter
%
% Description
% P = PRIOR_SQINVGAMMA('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates inverse-Gamma prior structure for square inverse of the
% parameter in which the named paramet... |
github | surban/DeepBraille-master | prior_laplace.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_laplace.m | 3,496 | windows_1250 | 62a1a5e73044d4b176444c53def9c3d8 | function p = prior_laplace(varargin)
%PRIOR_LAPLACE Laplace (double exponential) prior structure
%
% Description
% P = PRIOR_LAPLACE('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates Laplace prior structure in which the named parameters
% have the specified values. Any unspecified parameters are... |
github | surban/DeepBraille-master | prior_invunif.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_invunif.m | 1,627 | utf_8 | 476e27f80cccf901eb41842540a118b1 | function p = prior_invunif(varargin)
%PRIOR_INVUNIF Uniform prior structure for the inverse of the parameter
%
% Description
% P = PRIOR_INVUNIF creates uniform prior structure for the
% inverse of the parameter.
%
% See also
% PRIOR_*
%
% Copyright (c) 2009 Jarno Vanhatalo
% Copyright (c) 2010,2... |
github | surban/DeepBraille-master | prior_sinvchi2.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_sinvchi2.m | 3,862 | windows_1250 | 9bf2e8b2293220c041b0812b0de58c2e | function p = prior_sinvchi2(varargin)
%PRIOR_SINVCHI2 Scaled-Inv-Chi^2 prior structure
%
% Description
% P = PRIOR_SINVCHI2('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates Scaled-Inv-Chi^2 prior structure in which the named
% parameters have the specified values. Any unspecified
% parameters are... |
github | surban/DeepBraille-master | prior_sqrtt.m | .m | DeepBraille-master/Matlab/GPstuff/dist/prior_sqrtt.m | 5,067 | windows_1250 | a6a0b350cb791ed359325a80e0fdf501 | function p = prior_sqrtt(varargin)
%PRIOR_SQRTT Student-t prior structure for the square root of the parameter
%
% Description
% P = PRIOR_SQRTT('PARAM1', VALUE1, 'PARAM2', VALUE2, ...)
% creates for the square root of the parameter Student's
% t-distribution prior structure in which the named parame... |
github | surban/DeepBraille-master | kernelp.m | .m | DeepBraille-master/Matlab/GPstuff/diag/kernelp.m | 1,371 | utf_8 | 2b2f0dbc51c0952f90db26b833a7f346 | function [p,xx,sh]=kernelp(x,xx)
%KERNELP 1D Kernel density estimation of data, with automatic kernel width
%
% [P,XX]=KERNELP(X,XX) return density estimates P in points XX,
% given data and optionally evaluation points XX. Density
% estimate is based on simple Gaussian kernel density estimate
% where all kernels h... |
github | surban/DeepBraille-master | gradcheck.m | .m | DeepBraille-master/Matlab/GPstuff/diag/gradcheck.m | 2,489 | utf_8 | 1e4a8a8b0e776eb3b76a4be1c60b649e | function delta = gradcheck(w, func, grad, varargin)
%GRADCHECK Checks a user-defined gradient function using finite differences.
%
% Description
% This function is intended as a utility to check whether a gradient
% calculation has been correctly implemented for a given function.
% GRADCHECK(W, FUNC, GRAD... |
github | surban/DeepBraille-master | geyer_icse.m | .m | DeepBraille-master/Matlab/GPstuff/diag/geyer_icse.m | 1,895 | utf_8 | 8db021b75953dce62d429ad16d78b8dc | function [t,t1] = geyer_icse(x,maxlag)
% GEYER_ICSE - Compute autocorrelation time tau using Geyer's
% initial convex sequence estimator
%
% C = GEYER_ICSE(X) returns autocorrelation time tau.
% C = GEYER_ICSE(X,MAXLAG) returns autocorrelation time tau with
% MAXLAG . Default MAXLAG = M-1.
%
... |
github | surban/DeepBraille-master | ksstat.m | .m | DeepBraille-master/Matlab/GPstuff/diag/ksstat.m | 3,201 | utf_8 | bea38f6583298a14a9042b254b28fa15 | function [snks, snkss] = ksstat(varargin)
%KSSTAT Kolmogorov-Smirnov statistics
%
% ks = KSSTAT(X) or
% ks = KSSTAT(X1,X2,...,XJ)
% returns Kolmogorov-Smirnov statistics in form sqrt(N)*K
% where M is number of samples. X is a NxMxJ matrix which
% contains J MCMC simulations of length N, each with
% dimen... |
github | surban/DeepBraille-master | hmc2.m | .m | DeepBraille-master/Matlab/GPstuff/mc/hmc2.m | 9,845 | utf_8 | 4a06c9a759a73a727cd280c3d43cf40f | function [samples, energies, diagn] = hmc2(f, x, opt, gradf, varargin)
%HMC2 Hybrid Monte Carlo sampling.
%
% Description
% SAMPLES = HMC2(F, X, OPTIONS, GRADF) uses a hybrid Monte Carlo
% algorithm to sample from the distribution P ~ EXP(-F), where F is the
% first argument to HMC2. The Mark... |
github | surban/DeepBraille-master | hmc_nuts.m | .m | DeepBraille-master/Matlab/GPstuff/mc/hmc_nuts.m | 10,910 | utf_8 | 66776656d5c679ad1bded5bc046e9076 | function [samples, logp, diagn] = hmc_nuts(f, theta0, opt)
%HMC_NUTS No-U-Turn Sampler (NUTS)
%
% Description
% [SAMPLES, LOGP, DIAGN] = HMC_NUTS(f, theta0, opt)
% Implements the No-U-Turn Sampler (NUTS), specifically,
% algorithm 6 from the NUTS paper (Hoffman & Gelman, 2011). Runs
% opt.Madapt steps of b... |
github | surban/DeepBraille-master | sls.m | .m | DeepBraille-master/Matlab/GPstuff/mc/sls.m | 18,996 | utf_8 | 909e1e12015c1cde6f731f39015ae059 | function [samples,energies,diagn] = sls(f, x, opt, gradf, varargin)
%SLS Markov Chain Monte Carlo sampling using Slice Sampling
%
% Description
% SAMPLES = SLS(F, X, OPTIONS) uses slice sampling to sample
% from the distribution P ~ EXP(-F), where F is the first
% argument to SLS. Markov chain starts fro... |
github | surban/DeepBraille-master | metrop2.m | .m | DeepBraille-master/Matlab/GPstuff/mc/metrop2.m | 4,703 | utf_8 | 08184b230c18c07d461096023d9c021a | function [samples, energies, diagn] = metrop2(f, x, opt, gradf, varargin)
%METROP2 Markov Chain Monte Carlo sampling with Metropolis algorithm.
%
% Description
% SAMPLES = METROP(F, X, OPT) uses the Metropolis algorithm to
% sample from the distribution P ~ EXP(-F), where F is the first
% argument to METROP. The Mark... |
github | surban/DeepBraille-master | gp_optim.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gp_optim.m | 5,814 | utf_8 | 9aabd75d3faecee97886b7927003bbbf | function [gp, varargout] = gp_optim(gp, x, y, varargin)
%GP_OPTIM Optimize paramaters of a Gaussian process
%
% Description
% GP = GP_OPTIM(GP, X, Y, OPTIONS) optimises the parameters of a
% GP structure given matrix X of training inputs and vector
% Y of training targets.
%
% [GP, OUTPUT1, OUTPUT2, ...]... |
github | surban/DeepBraille-master | gpcf_linearLogistic.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_linearLogistic.m | 24,569 | windows_1250 | 8f95f318eb64dc6bc9dd8d955f6ddbf3 | function gpcf = gpcf_linearLogistic(varargin)
%GPCF_LINEARLOGISTIC Create a covariance function corresponding to
% logistic mean function
%
% Description
% GPCF = GPCF_LINEARLOGISTIC('PARAM1',VALUE1,'PARAM2,VALUE2,...) creates
% a covariance function structure corresponding to logistic mean... |
github | surban/DeepBraille-master | gp_mc.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gp_mc.m | 24,843 | utf_8 | 66163717ee78d1499db637a21912293e | function [record, gp, opt] = gp_mc(gp, x, y, varargin)
%GP_MC Markov chain Monte Carlo sampling for Gaussian process models
%
% Description
% [RECORD, GP, OPT] = GP_MC(GP, X, Y, OPTIONS) Takes the Gaussian
% process structure GP, inputs X and outputs Y. Returns record
% structure RECORD with parameter samp... |
github | surban/DeepBraille-master | gpla_e.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpla_e.m | 89,626 | utf_8 | 73adecf6ebdc65c135573cba3b140f0a | function [e, edata, eprior, param] = gpla_e(w, gp, varargin)
%GPLA_E Do Laplace approximation and return marginal log posterior estimate
%
% Description
% E = GPLA_E(W, GP, X, Y, OPTIONS) takes a GP structure GP
% together with a matrix X of input vectors and a matrix Y of
% target vectors, and finds the Lap... |
github | surban/DeepBraille-master | lik_qgp.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_qgp.m | 20,337 | utf_8 | 51fb08fc41e923fb163931821a988451 | function lik = lik_qgp(varargin)
%LIK_QGP Create a Quantile Gaussian Process likelihood (utility) structure
%
% Description
% LIK = LIK_QGP('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a quantile gp likelihood structure in which the named
% parameters have the specified values. Any unspecified
% paramet... |
github | surban/DeepBraille-master | gpcf_periodic.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_periodic.m | 39,377 | utf_8 | 54fbe442cdbd504673bbc9481b676817 | function gpcf = gpcf_periodic(varargin)
%GPCF_PERIODIC Create a periodic covariance function for Gaussian Process
%
% Description
% GPCF = GPCF_PERIODIC('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates periodic covariance function structure in which the
% named parameters have the specified values. Any unspec... |
github | surban/DeepBraille-master | metric_euclidean.m | .m | DeepBraille-master/Matlab/GPstuff/gp/metric_euclidean.m | 15,501 | utf_8 | b052a0f5a65c65aed64da38e2fbcf2c7 | function metric = metric_euclidean(varargin)
%METRIC_EUCLIDEAN An euclidean metric function
%
% Description
% METRIC = METRIC_EUCLIDEAN('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a an euclidean metric function structure in which the
% named parameters have the specified values. Either
% 'components' or... |
github | surban/DeepBraille-master | lik_negbinztr.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_negbinztr.m | 33,415 | utf_8 | f7081479fda75d41293d9584be042501 | function lik = lik_negbinztr(varargin)
%LIK_NEGBINZTR Create a zero-truncated Negative-binomial likelihood structure
%
% Description
% LIK = LIK_NEGBINZTR('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates zero-truncated Negative-binomial likelihood structure
% in which the named parameters have the specified va... |
github | surban/DeepBraille-master | gpcf_neuralnetwork.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_neuralnetwork.m | 25,721 | utf_8 | 50dadee5f07c63608a4a0edaaf8fcdbb | function gpcf = gpcf_neuralnetwork(varargin)
%GPCF_NEURALNETWORK Create a neural network covariance function
%
% Description
% GPCF = GPCF_NEURALNETWORK('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates neural network covariance function structure in which
% the named parameters have the specified values. Any
%... |
github | surban/DeepBraille-master | gp_g.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gp_g.m | 55,338 | UNKNOWN | 0163ae135b56f3688121e019bea83789 | function [g, gdata, gprior] = gp_g(w, gp, x, y, varargin)
%GP_G Evaluate the gradient of energy (GP_E) for Gaussian Process
%
% Description
% G = GP_G(W, GP, X, Y, OPTIONS) takes a full GP parameter
% vector W, GP structure GP, a matrix X of input vectors and a
% matrix Y of target vectors, and evaluates the... |
github | surban/DeepBraille-master | gpcf_ppcs1.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_ppcs1.m | 38,745 | utf_8 | 2871acf94d24f84723244b339b08d7de | function gpcf = gpcf_ppcs1(varargin)
%GPCF_PPCS1 Create a piece wise polynomial (q=1) covariance function
%
% Description
% GPCF = GPCF_PPCS1('nin',nin,'PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates piece wise polynomial (q=1) covariance function
% structure in which the named parameters have the specified... |
github | surban/DeepBraille-master | gpcf_ppcs3.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_ppcs3.m | 40,793 | utf_8 | f1efd766ea328dfaa1f8ff1b6c073f65 | function gpcf = gpcf_ppcs3(varargin)
%GPCF_PPCS3 Create a piece wise polynomial (q=3) covariance function
%
% Description
% GPCF = GPCF_PPCS3('nin',nin,'PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates piece wise polynomial (q=3) covariance function
% structure in which the named parameters have the specified
... |
github | surban/DeepBraille-master | esls.m | .m | DeepBraille-master/Matlab/GPstuff/gp/esls.m | 5,593 | utf_8 | 606472af5b1d3fe12875fa0792c089ba | function [f, energ, diagn] = esls(f, opt, gp, x, y, z, angle_range)
%ESLS Markov chain update for a distribution with a Gaussian "prior"
% factored out
%
% Description
% [F, ENERG, DIAG] = ESLS(F, OPT, GP, X, Y) takes the current
% latent values F, options structure OPT, Gaussian process
% structure GP... |
github | surban/DeepBraille-master | svigp.m | .m | DeepBraille-master/Matlab/GPstuff/gp/svigp.m | 15,331 | utf_8 | d24e17f25fcdbfddfd9a1486676f2063 | function [gp, diagnosis] = svigp(gp, x, y, varargin)
%SVIGP Stochastic variational inference for GP
%
% Description
% GP = SVIGP(GP, X, Y, OPTIONS) optimises the variational, likelihood
% and covariance function parameters of a sparse SVI GP model
% given matrix X of training inputs and vector Y of training ... |
github | surban/DeepBraille-master | gpcf_linear.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_linear.m | 29,694 | windows_1250 | 6411eecdafc6eebe19e3260f7292f41f | function gpcf = gpcf_linear(varargin)
%GPCF_LINEAR Create a linear (dot product) covariance function
%
% Description
% GPCF = GPCF_LINEAR('PARAM1',VALUE1,'PARAM2,VALUE2,...) creates
% a linear (dot product) covariance function structure in which
% the named parameters have the specified values. Any
% unsp... |
github | surban/DeepBraille-master | lik_weibull.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_weibull.m | 23,464 | windows_1250 | 8bba00cdbd8e0845f3124c369d8dce69 | function lik = lik_weibull(varargin)
%LIK_WEIBULL Create a right censored Weibull likelihood structure
%
% Description
% LIK = LIK_WEIBULL('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a likelihood structure for a right censored Weibull
% survival model in which the named parameters have the specified
% ... |
github | surban/DeepBraille-master | lik_inputdependentweibull.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_inputdependentweibull.m | 16,216 | windows_1250 | 93f379c1009319041b215b2626a55439 | function lik = lik_inputdependentweibull(varargin)
%LIK_INPUTDEPENDENTWEIBULL Create a (right censored) input dependent Weibull likelihood structure
%
% Description
% LIK = LIK_INPUTDEPENDENTWEIBULL('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a likelihood structure for a right censored input dependent
% ... |
github | surban/DeepBraille-master | gp_predcm.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gp_predcm.m | 17,308 | utf_8 | 285c6a665928cfa46271691fe1c5d9c4 | function [pc, fvecm2, p, c] = gp_predcm(gp,x,y,varargin)
%GP_PREDCM Corrections for latent marginal posterior
%
% Description
% [PC, FVEC, P, C] = GP_PREDCM(GP, X, Y, XT, OPTIONS) Evaluates the
% corrected marginal posterior of latent variable at given indices
% of XT or X if XT is empty or not given. Margin... |
github | surban/DeepBraille-master | gpep_pred.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpep_pred.m | 34,823 | utf_8 | d3c9abc7ed6c13033a73d28061342604 | function [Eft, Varft, lpyt, Eyt, Varyt] = gpep_pred(gp, x, y, varargin)
%GPEP_PRED Predictions with Gaussian Process EP approximation
%
% Description
% [EFT, VARFT] = GPEP_PRED(GP, X, Y, XT, OPTIONS)
% takes a GP structure together with matrix X of training
% inputs and vector Y of training targets, and eval... |
github | surban/DeepBraille-master | gpcf_constant.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_constant.m | 21,048 | utf_8 | 1a5c65079883f03a444c16f2c3a0ebec | function gpcf = gpcf_constant(varargin)
%GPCF_CONSTANT Create a constant covariance function
%
% Description
% GPCF = GPCF_CONSTANT('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a constant covariance function structure in which the
% named parameters have the specified values. Any unspecified
% parameter... |
github | surban/DeepBraille-master | lik_gaussiansmt.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_gaussiansmt.m | 11,370 | utf_8 | 0b1c967f60512e391f3fbd739d22946c | function lik = lik_gaussiansmt(varargin)
%LIK_GAUSSIANSMT Create a Gaussian scale mixture likelihood structure
% with priors producing approximation of the Student's t
%
% Description
% LIK = LIK_GAUSSIANSMT('ndata',N,'PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a scale mixture noise covarianc... |
github | surban/DeepBraille-master | lik_t.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_t.m | 37,086 | utf_8 | 811bda1da7f669085fbdb3a8c09eed98 | function lik = lik_t(varargin)
%LIK_T Create a Student-t likelihood structure
%
% Description
% LIK = LIK_T('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates Student-t likelihood structure in which the named
% parameters have the specified values. Any unspecified
% parameters are set to default values.
%
% ... |
github | surban/DeepBraille-master | gpcf_rq.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_rq.m | 32,717 | utf_8 | cd8b221fa9654cf68f412cfc6bb9c370 | function gpcf = gpcf_rq(varargin)
%GPCF_RQ Create a rational quadratic covariance function
%
% Description
% GPCF = GPCF_RQ('PARAM1',VALUE1,'PARAM2,VALUE2,...) creates
% rational quadratic covariance function structure in which the
% named parameters have the specified values. Any unspecified
% parameters... |
github | surban/DeepBraille-master | gpep_predgrad.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpep_predgrad.m | 9,958 | utf_8 | 2892946a4d23da6fc296e8a7f984f1fb | function [Eft, Varft, lpyt, Eyt, Varyt] = gpep_predgrad(gp, x, y, varargin)
%GPEP_PRED Predictions with Gaussian Process EP approximation
%
% Description
% [EFT, VARFT] = GPEP_PREDGRAD(GP, X, Y, XT, OPTIONS)
% takes a GP structure together with matrix X of training
% inputs and vector Y of training targets, ... |
github | surban/DeepBraille-master | lgcp.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lgcp.m | 7,611 | utf_8 | e95b6cfc142c5457f944c2c08559a1bd | function [l,lq,xt,gp] = lgcp(x,varargin)
% LGCP - Log Gaussian Cox Process intensity estimate for 1D and 2D data
%
% LGCP(X)
% [P,PQ,XT,GP] = LGCP(X,XT,OPTIONS)
%
% X is 1D or 2D point data
% XT is optional test points
% OPTIONS are optional parameter-value pairs
% 'gridn' is optional number ... |
github | surban/DeepBraille-master | gpep_e.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpep_e.m | 210,495 | utf_8 | 3aec3987ab9ec70e7d4d36e577614a68 | function [e, edata, eprior, param] = gpep_e(w, gp, varargin)
%GPEP_E Do Expectation propagation and return marginal log posterior estimate
%
% Description
% E = GPEP_E(W, GP, X, Y, OPTIONS) takes a GP structure GP
% together with a matrix X of input vectors and a matrix Y of
% target vectors, and finds the E... |
github | surban/DeepBraille-master | lik_gaussian.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_gaussian.m | 13,064 | utf_8 | 2dff42c3f59cf628c81f0b133822ec79 | function lik = lik_gaussian(varargin)
%LIK_GAUSSIAN Create a Gaussian likelihood structure
%
% Description
% LIK = LIK_GAUSSIAN('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a Gaussian likelihood structure in which the named
% parameters have the specified values. Any unspecified
% parameters are set to ... |
github | surban/DeepBraille-master | lik_epgaussian.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_epgaussian.m | 47,189 | utf_8 | f04e1e2e2e2e9e77ef0ebba4ac19c54d | function lik = lik_epgaussian(varargin)
%LIK_EPGAUSSIAN Create a EP-Gaussian likelihood structure
%
% Description
% LIK = LIK_EPGAUSSIAN creates EP-Gaussian likelihood structure used
% in models with input dependent noise/magnitude.
%
% See also
% GP_SET, LIK_*
%
% Copyright (c) 2013 Ville Tolvanen
% Thi... |
github | surban/DeepBraille-master | surrogate_sls.m | .m | DeepBraille-master/Matlab/GPstuff/gp/surrogate_sls.m | 21,376 | utf_8 | 92a87164fc807a9f5faeea47d496deb6 | function [samples,samplesf,diagn] = surrogate_sls(f, x, opt, gp, xx, yy, z, varargin)
%SURROGATE_SLS Markov Chain Monte Carlo sampling using Surrogate data Slice Sampling
%
% Description
% SAMPLES = SURROGATE_SLS(F, X, OPTIONS) uses slice sampling to sample
% from the distribution P ~ EXP(-F), where F is the ... |
github | surban/DeepBraille-master | lik_lgpc.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_lgpc.m | 9,180 | windows_1250 | 18e3409f79ef94150ca0005e4d64ebeb | function lik = lik_lgpc(varargin)
%LIK_LGPC Create a logistic Gaussian process likelihood structure for
% conditional density estimation
%
% Description
% LIK = LIK_LGPC creates a logistic Gaussian process likelihood
% structure for conditional density estimation
%
% The likelihood contribution for ... |
github | surban/DeepBraille-master | gpcf_squared.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_squared.m | 33,999 | windows_1250 | 99c8c3daa8d20aa2ea72caaaf2fb6dc0 | function gpcf = gpcf_squared(varargin)
%GPCF_SQUARED Create a squared (dot product) covariance function
%
% Description
% GPCF = GPCF_SQUARED('PARAM1',VALUE1,'PARAM2,VALUE2,...) creates
% a squared (dot product) covariance function structure in which
% the named parameters have the specified values. Any unsp... |
github | surban/DeepBraille-master | lik_softmax.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_softmax.m | 10,862 | utf_8 | 07ac231a80cb80acc574eec45e47f7df | function lik = lik_softmax(varargin)
%LIK_SOFTMAX Create a softmax (multinomial logit) likelihood structure
%
% Description
% LIK = LIK_SOFTMAX creates softmax (multinomial logit) likelihood
% for multi-class classification problem. The observed class label
% with C classes is given as 1xC vector where C-1 ... |
github | surban/DeepBraille-master | gpcf_noise.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_noise.m | 13,390 | utf_8 | 7932fa93596a9f12bbb41b927db60554 | function gpcf = gpcf_noise(varargin)
%GPCF_NOISE Create a independent noise covariance function
%
% Description
% GPCF = GPCF_NOISE('PARAM1',VALUE1,'PARAM2,VALUE2,...) creates
% independent noise covariance function structure in which the
% named parameters have the specified values. Any unspecified
% par... |
github | surban/DeepBraille-master | gpcf_scaled.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_scaled.m | 14,416 | utf_8 | 7abb3c95f4abc716646780c95c247917 | function gpcf = gpcf_scaled(varargin)
%GPCF_SCALED Create a scaled covariance function
%
% Description
% GPCF = GPCF_SCALED('cf', {GPCF_1, GPCF_2, ...})
% creates a scaled version of a covariance function as follows
% GPCF_SCALED = diag(x(:,scaler))*GPCF*diag(x(:,scaler))
% where x is the matrix of... |
github | surban/DeepBraille-master | gpcf_ppcs2.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_ppcs2.m | 39,575 | utf_8 | a7d322d473ff523db51fe04375ee5d33 | function gpcf = gpcf_ppcs2(varargin)
%GPCF_PPCS2 Create a piece wise polynomial (q=2) covariance function
%
% Description
% GPCF = GPCF_PPCS2('nin',nin,'PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates piece wise polynomial (q=2) covariance function
% structure in which the named parameters have the specifie... |
github | surban/DeepBraille-master | gpcf_sum.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_sum.m | 14,946 | utf_8 | f3f7cf46b91f3a12b74a9ab6018fdc89 | function gpcf = gpcf_sum(varargin)
%GPCF_SUM Create a sum form covariance function
%
% Description
% GPCF = GPCF_SUM('cf', {GPCF_1, GPCF_2, ...})
% creates a sum form covariance function
% GPCF = GPCF_1 + GPCF_2 + ... + GPCF_N
%
% See also
% GP_SET, GPCF_*
%
% Copyright (c) 2009-2010 Jarno Vanhata... |
github | surban/DeepBraille-master | gpcf_matern32.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_matern32.m | 29,553 | utf_8 | d9a9f1779bbb5ec428e8a2a28fee5289 | function gpcf = gpcf_matern32(varargin)
%GPCF_MATERN32 Create a Matern nu=3/2 covariance function
%
% Description
% GPCF = GPCF_MATERN32('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates Matern nu=3/2 covariance function structure in which
% the named parameters have the specified values. Any
% unspecified p... |
github | surban/DeepBraille-master | lik_logit.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_logit.m | 18,580 | utf_8 | 47e8cf9a36bd19866d155d2d75f6ded7 | function lik = lik_logit(varargin)
%LIK_LOGIT Create a Logit likelihood structure
%
% Description
% LIK = LIK_LOGIT creates Logit likelihood for classification
% problem with class labels {-1,1}.
%
% The likelihood is defined as follows:
% __ n
% p(y|f) = || i=1 1/(1 + exp(-y_i*f_i... |
github | surban/DeepBraille-master | lik_laplace.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_laplace.m | 18,990 | utf_8 | 44e74b6296437f26513d06be5e07d346 | function lik = lik_laplace(varargin)
%LIK_Laplace Create a Laplace likelihood structure
%
% Description
% LIK = LIK_LAPLACE('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a laplace likelihood structure in which the named
% parameters have the specified values. Any unspecified
% parameters are set to defau... |
github | surban/DeepBraille-master | lik_loggaussian.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_loggaussian.m | 28,893 | utf_8 | 762916094c4c0fcd72fbeef814a8c5b7 | function lik = lik_loggaussian(varargin)
%LIK_LOGGAUSSIAN Create a right censored log-Gaussian likelihood structure
%
% Description
% LIK = LIK_LOGGAUSSIAN('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a likelihood structure for right censored log-Gaussian
% survival model in which the named parameters hav... |
github | surban/DeepBraille-master | gpmf_constant.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpmf_constant.m | 8,500 | utf_8 | 218139811870eb65016feaa1c844aac3 | function gpmf = gpmf_constant(varargin)
%GPMF_CONSTANT Create a constant mean function
%
% Description
% GPMF = GPMF_CONSTANT('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates constant mean function structure in which the named
% parameters have the specified values. Any unspecified
% parameters are set to d... |
github | surban/DeepBraille-master | gpla_loopred.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpla_loopred.m | 10,855 | UNKNOWN | 9da4f1cba2861c677fa1f8e2bd0720da | function [Eft, Varft, lpyt, Eyt, Varyt] = gpla_loopred(gp, x, y, varargin)
%GPLA_LOOPRED Leave-one-out predictions with Laplace approximation
%
% Description
% [EFT, VARFT, LPYT, EYT, VARYT] = GPLA_LOOPRED(GP, X, Y, OPTIONS)
% takes a Gaussian process structure GP together with a matrix X
% of training input... |
github | surban/DeepBraille-master | gpsvi_predgrad.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpsvi_predgrad.m | 7,399 | utf_8 | 21670029f90d5ab3150800aebcc53c94 | function [Eft, Varft, lpyt, Eyt, Varyt] = gpsvi_predgrad(gp,x,y,varargin)
%GPSVI_PREDGRAD Make predictions with SVI GP
%
% Description
% [EFT, VARFT] = GPSVI_PREDGRAD(GP, X, Y, XT, OPTIONS)
% takes a GP structure together with matrix X of training inputs and
% vector Y of training targets, and evaluates the ... |
github | surban/DeepBraille-master | lgpdens.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lgpdens.m | 38,620 | windows_1250 | b9047de35b3031952595b32f7d2e53b3 | function [p,pq,xx,pjr,gp,ess,eig,q,r] = lgpdens(x,varargin)
%LGPDENS Logistic-Gaussian Process density estimate for 1D and 2D data
%
% Description
% LGPDENS(X,OPTIONS) Compute and plot LGP density estimate. X is
% 1D or 2D point data. For 1D data plot the mean and 95% region.
% For 2D data plot the densit... |
github | surban/DeepBraille-master | gp_waic.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gp_waic.m | 23,847 | utf_8 | 9d50d4ee06eb8a684098eedc2b0ee674 | function waic = gp_waic(gp, x, y, varargin)
%GP_WAIC The widely applicable information criterion (WAIC) for GP model
%
% Description
% WAIC = GP_WAIC(GP, X, Y, OPTIONS) evaluates WAIC defined by
% Watanabe (2010) given a Gaussian process model GP, training
% inputs X and training outputs Y. Instead of Bayes ... |
github | surban/DeepBraille-master | cf_sum_to_ss.m | .m | DeepBraille-master/Matlab/GPstuff/gp/cf_sum_to_ss.m | 3,060 | utf_8 | c4e5b7423a68468f4709cf850e588730 | function [F,L,Qc,H,Pinf,dF,dQc,dPinf,params] = cf_sum_to_ss(cf2ss)
%% CF_SUM_TO_SS - Sum of several state space models
%
% Syntax:
% [F,L,Qc,H,Pinf,dF,dQc,dPinf,params] = cf_sum_to_ss(cf2ss)
%
% In:
% cf2ss - Cell vector of function handles (see below)
%
% Out:
% F - Feedback matrix
% L ... |
github | surban/DeepBraille-master | cf_rq_to_ss.m | .m | DeepBraille-master/Matlab/GPstuff/gp/cf_rq_to_ss.m | 9,092 | utf_8 | c5be40ca7e24ac38b2d0c3d728b78a1b | function [F,L,Qc,H,Pinf,dF,dQc,dPinf,params] = cf_rq_to_ss(magnSigma2, lengthScale, alpha, N, NSE)
% CF_RQ_TO_SS - Rational quadratic covariance functions to state space
%
% Syntax:
% [F,L,Qc,H,Pinf,dF,dQc,dPinf,params] = cf_rq_to_ss(magnSigma2, lengthScale, alpha, N, NSE)
%
% In:
% magnSigma2 - Magnitude scale pa... |
github | surban/DeepBraille-master | gpcf_ppcs0.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_ppcs0.m | 37,714 | utf_8 | 28df6f1f48f796902749c196f0e82b42 | function gpcf = gpcf_ppcs0(varargin)
%GPCF_PPCS0 Create a piece wise polynomial (q=0) covariance function
%
% Description
% GPCF = GPCF_PPCS0('nin',nin,'PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates piece wise polynomial (q=0) covariance function
% structure in which the named parameters have the specified
... |
github | surban/DeepBraille-master | lik_probit.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_probit.m | 11,517 | windows_1250 | c199a8c3ea4e70a8d6f6da520a936199 | function lik = lik_probit(varargin)
%LIK_PROBIT Create a Probit likelihood structure
%
% Description
% LIK = LIK_PROBIT creates Probit likelihood for classification
% problem with class labels {-1,1}.
%
% The likelihood is defined as follows:
% __ n
% p(y|f, z) = || i=1 normcdf(y_i *... |
github | surban/DeepBraille-master | lik_negbin.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_negbin.m | 23,818 | utf_8 | 54c66e1cfdd1235fc5432d8ccddf18f5 | function lik = lik_negbin(varargin)
%LIK_NEGBIN Create a Negative-binomial likelihood structure
%
% Description
% LIK = LIK_NEGBIN('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates Negative-binomial likelihood structure in which the
% named parameters have the specified values. Any unspecified
% parameters ... |
github | surban/DeepBraille-master | gpcf_cat.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_cat.m | 11,687 | windows_1250 | d51c7548635b4a71e508d3c0a33bcb88 | function gpcf = gpcf_cat(varargin)
%GPCF_CAT Create a categorical covariance function
%
% Description
% GPCF = GPCF_CAT('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a categorical covariance function structure in
% which the named parameters have the specified values. Any
% unspecified parameters are set... |
github | surban/DeepBraille-master | gp_install.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gp_install.m | 14,890 | utf_8 | 81cb8c038250482de318faa3050b6a48 | function gp_install(suiteSparse)
% Matlab function to compile all the c-files to mex in the GPstuff/gp
% folder. The function is called from GPstuff/matlab_install.m but
% can be run separately also.
%
% If you want to use GPstuff without compactly supported (CS)
% covariance functions run as gp_install([]). If y... |
github | surban/DeepBraille-master | lik_poisson.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_poisson.m | 16,685 | utf_8 | e6423144f0121f83e9906fecd1456400 | function lik = lik_poisson(varargin)
%LIK_POISSON Create a Poisson likelihood structure
%
% Description
% LIK = LIK_POISSON creates Poisson likelihood structure
%
% The likelihood is defined as follows:
% __ n
% p(y|f, z) = || i=1 Poisson(y_i|z_i*exp(f_i))
%
% where z is a vector of... |
github | surban/DeepBraille-master | gpcf_additive.m | .m | DeepBraille-master/Matlab/GPstuff/gp/gpcf_additive.m | 30,872 | utf_8 | 0d687e9b2b178e5f4b36fe2bb1107990 | function gpcf = gpcf_additive(varargin)
%GPCF_ADDITIVE Create a mixture over products of kernels for each dimension
%
% Description
% GPCF = GPCF_ADDITIVE('PARAM1',VALUE1, 'PARAM2,VALUE2, ...)
% creates a mixture over all possible product combinations of given
% covariance functions for each input dimension ... |
github | surban/DeepBraille-master | lik_coxph.m | .m | DeepBraille-master/Matlab/GPstuff/gp/lik_coxph.m | 50,495 | windows_1250 | 525c99c25a3f520ece852d6f80243e7f | function lik = lik_coxph(varargin)
%LIK_COXPH Create a Cox proportional hazard likelihood structure
%
% Description
% LIK = LIK_COXPH('PARAM1',VALUE1,'PARAM2,VALUE2,...)
% creates a proportional hazard model where a piecewise log-constant
% baseline hazard is assumed.
%
% The likelihood contribut... |
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