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/159921/10587832

m bayesdemo3.m

% BAYESDEMO3 Bayesian risk and minimax strategy. % % Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac % (c) Czech Technical University Prague, http://cmp.felk.cvut.cz %
www.eeworm.com/read/159921/10587853

m contents.m

% Bayes Classification. % % bayeserr - Computes the Bayesian risk for optimal classifier. % bayescln - Classifier based on Bayes decision rule for Gaussians. % bayesnd - Discrim. function, dic
www.eeworm.com/read/421949/10676522

m bayesdemo3.m

% BAYESDEMO3 Bayesian risk and minimax strategy. % % Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac % (c) Czech Technical University Prague, http://cmp.felk.cvut.cz %
www.eeworm.com/read/421949/10676542

m contents.m

% Bayes Classification. % % bayeserr - Computes the Bayesian risk for optimal classifier. % bayescln - Classifier based on Bayes decision rule for Gaussians. % bayesnd - Discrim. function, dic
www.eeworm.com/read/103989/7119195

html index.html

Bayes++ Bayesian Filtering Classes: Main Page
www.eeworm.com/read/449504/7502104

m rvar_d.m

% PURPOSE: An example of using rvar() function % to estimate a var model % (based on Bayesian Spatial contiguity prior) %
www.eeworm.com/read/449504/7502515

m empquant.m

function y = empquant(runs,q) % PURPOSE: function called by raftery.m % % ------------------------------------------------ % SEE ALSO: coda(), prt() % ------------------------------------------------
www.eeworm.com/read/449504/7502803

m contents.m

% spatial error model estimation functions % % compare_models : An example of using sar_g() sem_g() Gibbs sampling % compare_models2 : An example of using sar_g() sem_g() Gibbs sampling % compa
www.eeworm.com/read/449504/7503072

m contents.m

% spatial autoregressive model estimation functions % % beta_prior : construct beta-prior for rho over -1,1 interval % compare_models : An example of model comparison using log marginal poster
www.eeworm.com/read/299459/7849087

html contents.html

Contents.m