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/428451/8867256
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/427586/8932070
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/183445/9158712
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/182197/9212150
h nbc.h
#ifndef NBC_TABLE_H
#define NBC_TABLE_H
#include "dataTab.h"
#include "rawDataTable.h"
#include "classInfo.h"
#include "attributeInfo.h"
// Naive Bayesian Classifier
// the class NBC_Table consist
www.eeworm.com/read/374698/9388896
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/165115/10076133
nex cynmix.nex
#NEXUS
[This is an example of a mixed data set]
[Data from Nylander, J., F. Ronquist, J. P. Huelsenbeck and J. L. Nieves-Aldrey. 2004. Bayesian phylogenetic analysis of combined data. Systematic
www.eeworm.com/read/278889/10490603
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/421949/10676147
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/449504/7503052
m semip_gc.m
function results = semip_gc(y,x,W,m,mobs,ndraw,nomit,prior)
% PURPOSE: C-MEX version of: Bayesian Probit with spatial individual effects:
% Y = (Yi, i=1,..,m) with each vector, Yi = (yij:j=1
www.eeworm.com/read/397122/8065848
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun