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/161855/10361049

1 mailinspect.1

\" t .TH MAILINSPECT 1 "Bayesian Text Classification Tools" "Version 1.3" "" .SH NAME mailinspect \- sort an mbox by category and pipe emails to a command. .SH SYNOPSIS .HP .B mailinspect [-zjiI] -c
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www.eeworm.com/read/449504/7502042

m rvarf_g.m

function ylevf = rvarf_g(y,nlag,nfor,begf,prior,ndraw,nomit,x); % PURPOSE: Gibbs forecasts for a Bayesian vector autoregressive % model using the random-walk averaging prior % y =
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www.eeworm.com/read/449504/7502057

m rvarb.m

function bmat = rvarb(y,nlag,w,freq,sig,tau,theta,x); % PURPOSE: Estimates a Bayesian vector autoregressive model % using the random-walk averaging prior, returning % bhat's only (
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www.eeworm.com/read/449504/7502060

m rvar_g.m

function results = rvar_g(y,nlag,prior,ndraw,nomit,x); % PURPOSE: Gibbs estimates for a Bayesian vector autoregressive % model using the random-walk averaging prior % y = A(L) Y +
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www.eeworm.com/read/449504/7502068

m bvarf.m

function ylevf = bvarf(y,nlag,nfor,begf,tight,weight,decay,x,transf); % PURPOSE: Estimates a Bayesian vector autoregression of order n % and produces f-step-ahead forecasts (Minnesota prior)
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www.eeworm.com/read/449504/7502860

m mess_g1.m

function results = mess_g1(y,x,options,ndraw,nomit,prior,start) % PURPOSE: Bayesian estimates of the matrix exponential spatial model (mess) % % [samples values of neighbors to produce a posterior dis
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www.eeworm.com/read/449504/7502861

m mess_g3.m

function results = mess_g3(y,x,options,ndraw,nomit,prior,start) % PURPOSE: Bayesian estimates of the matrix exponential spatial model (mess) % % [samples values of rho and #neighbors to produce a post
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www.eeworm.com/read/449504/7502867

m messv_g3.m

function results = messv_g3(y,x,options,ndraw,nomit,prior,start) % PURPOSE: Bayesian estimates of the matrix exponential spatial model (mess) % % [samples values of rho and #neighbors to produce a pos
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www.eeworm.com/read/449504/7502871

m mess_g.m

function results = mess_g(y,x,options,ndraw,nomit,prior,start) % PURPOSE: Bayesian estimates of the matrix exponential spatial model (mess) % [based on a given value of rho and # of neighbors] % S*y =
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www.eeworm.com/read/449504/7502879

m mess_g2.m

function results = mess_g2(y,x,options,ndraw,nomit,prior,start) % PURPOSE: Bayesian estimates of the matrix exponential spatial model (mess) % % [samples values of rho to produce a posterior distribut
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