代码搜索：Bayesian
找到约 1,632 项符合「Bayesian」的源代码
代码结果 1,632
www.eeworm.com/read/374698/9388956
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,
www.eeworm.com/read/278889/10490771
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,
www.eeworm.com/read/421949/10676321
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,
www.eeworm.com/read/449504/7502080
m rvarf.m
function ylevf = rvarf(y,nlag,w,freq,nfor,begf,sig,tau,theta,x);
% PURPOSE: Estimates a Bayesian autoregressive model of order n
% using Random-Walk averaging prior and produces f-step-ahead
www.eeworm.com/read/449504/7502801
m semp_g.m
function results = sem_g(y,x,W,ndraw,nomit,prior)
% PURPOSE: Bayesian estimates of the spatial probit error model
% y = XB + u, u = rho*W + e
% y = binary, 0,1 variable
%
www.eeworm.com/read/440842/7680292
m contents.m
%Write text describing the m-files in this directory
%
% ar1_like : evaluate ols model with AR1 errors log-likelihood
% ar_g : MCMC estimates Bayesian heteroscedastic AR(k) mode
www.eeworm.com/read/433808/7908115
m bvsgs_sp.m
function [Gamma, GammaD, logProb, logProbD, PostGamD, MargGam, SWITCH]= ...
bvsgs_sp(gamprec,X,Y, delta,k, w, v1)
%bvsgs_sp: Bayesian Variable Selection - Gibbs Sampler - Main Program
% Selection
www.eeworm.com/read/397122/8065933
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,
www.eeworm.com/read/331336/12832671
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,
www.eeworm.com/read/324303/13273915
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,