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/469416/6976359
m errbayes.m
function [e, edata, eprior] = errbayes(net, edata)
%ERRBAYES Evaluate Bayesian error function for network.
%
% Description
% E = ERRBAYES(NET, EDATA) takes a network data structure NET together
www.eeworm.com/read/469416/6976401
m demhmc2.m
%DEMHMC2 Demonstrate Bayesian regression with Hybrid Monte Carlo sampling.
%
% Description
% The problem consists of one input variable X and one target variable
% T with data generated by samplin
www.eeworm.com/read/449504/7502056
m becmf.m
function ylevf = becmf(y,nlag,nfor,begf,tight,weight,decay,r);
% PURPOSE: estimates a Bayesian error correction model of order n
% and produces f-step-ahead forecasts
%-----------------------
www.eeworm.com/read/438244/7733581
cs corpus.cs
using System.Collections.Generic;
using System.IO;
using System.Text.RegularExpressions;
namespace Expat.Bayesian
{
///
/// This is just a list of words found in a bunch of text, a
www.eeworm.com/read/438239/7733602
cs corpus.cs
using System.Collections.Generic;
using System.IO;
using System.Text.RegularExpressions;
namespace Expat.Bayesian
{
///
/// This is just a list of words found in a bunch of text, a
www.eeworm.com/read/397122/8065750
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
%
%
www.eeworm.com/read/331336/12832399
m bay_optimize.m
function [model,A,B,C,D] = bay_optimize(model,level, type, nb, bay)
% Optimize the posterior probabilities of model (hyper-) parameters with respect to the different levels in Bayesian inference
%
%
www.eeworm.com/read/143706/12849572
m errbayes.m
function [e, edata, eprior] = errbayes(net, edata)
%ERRBAYES Evaluate Bayesian error function for network.
%
% Description
% E = ERRBAYES(NET, EDATA) takes a network data structure NET together
% the
www.eeworm.com/read/140851/13058940
m demhmc3.m
%DEMHMC3 Demonstrate Bayesian regression with Hybrid Monte Carlo sampling.
%
% Description
% The problem consists of one input variable X and one target variable
% T with data generated by samplin
www.eeworm.com/read/140851/13058991
m errbayes.m
function [e, edata, eprior] = errbayes(net, edata)
%ERRBAYES Evaluate Bayesian error function for network.
%
% Description
% E = ERRBAYES(NET, EDATA) takes a network data structure NET together