代码搜索：Bayesian

找到约 1,632 项符合「Bayesian」的源代码

代码结果 1,632
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www.eeworm.com/read/150905/12250116

htm gbayes.htm

Netlab Reference Manual gbayes gbayes Purpose Evaluate gradient of Bayesian error function for network. Synopsis
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www.eeworm.com/read/150905/12250284

htm demhmc2.htm

Netlab Reference Manual demhmc2 demhmc2 Purpose Demonstrate Bayesian regression with Hybrid Monte Carlo sampling. Synopsis
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www.eeworm.com/read/150905/12250336

htm demhmc3.htm

Netlab Reference Manual demhmc3 demhmc3 Purpose Demonstrate Bayesian regression with Hybrid Monte Carlo sampling. Synopsis
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www.eeworm.com/read/150905/12250365

htm hbayes.htm

Netlab Reference Manual hbayes hbayes Purpose Evaluate Hessian of Bayesian error function for network. Synopsis
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www.eeworm.com/read/470861/1443343

svn-base spm_ar.m.svn-base

function [ar] = spm_ar (Z,p,verbose) % Bayesian autoregressive modelling % FORMAT [ar] = spm_ar (Z,p,verbose) % % y_pred (t) = -\sum_{i=1}^p a_i y (t-i) + e (t) % Note the sign and ordering % % The n
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www.eeworm.com/read/449504/7502964

m sdm_g.m

function results = sdm_g(y,x,W,ndraw,nomit,prior) % PURPOSE: Bayesian estimates of the heteroscedastic spatial durbin model % (I-rho*W)y = a + X*B1 + W*X*B2 + e, e = N(0,sige*V), V = diag(v1
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www.eeworm.com/read/429878/8784081

htm demev2.htm

Netlab Reference Manual demev2 demev2 Purpose Demonstrate Bayesian classification for the MLP. Synopsis demev2
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www.eeworm.com/read/428451/8867265

m codedist_bay.m

function dist = codedist_bay(C1,C2,Py) % compute the distance using a Bayesian metric between 'C1' and 'C2' % % dist = codedist_bay(C1,C2,{Py}) % % 'C1' contains the result code, % 'C2' contains
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www.eeworm.com/read/427586/8932082

m codedist_bay.m

function dist = codedist_bay(C1,C2,Py) % compute the distance using a Bayesian metric between 'C1' and 'C2' % % dist = codedist_bay(C1,C2,{Py}) % % 'C1' contains the result code, % 'C2' contains
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www.eeworm.com/read/183445/9158716

m codedist_bay.m

function dist = codedist_bay(C1,C2,Py) % compute the distance using a Bayesian metric between 'C1' and 'C2' % % dist = codedist_bay(C1,C2,{Py}) % % 'C1' contains the result code, % 'C2' contains
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