MFA: Marginal Fisher Analysis
標(biāo)簽： Analysis Marginal Fisher MFA
上傳時(shí)間： 2014-08-02
上傳用戶：cuibaigao
Marginal Fisher Analysis算法，可用于降維，注釋有使用說明！供大家學(xué)習(xí)交流！
標(biāo)簽： Marginal Analysis Fisher 算法
上傳時(shí)間： 2013-12-25
上傳用戶：天涯
This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the Marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equations are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the number of time samples and M the number of sources.
標(biāo)簽： instantaneous algorithm Bayesian Gaussian
上傳時(shí)間： 2013-12-19
上傳用戶：jjj0202
sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a Gaussian copula, treating the univariate Marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data. Version: 0.95 Date: 2007-03-09 Author: Peter Hoff Maintainer: Peter Hoff <hoff at stat.washington.edu> License: GPL Version 2 or later URL: http://www.stat.washington.edu/hoff CRAN checks: sbgcop results Downloads: Package source: sbgcop_0.95.tar.gz MacOS X binary: sbgcop_0.95.tgz Windows binary: sbgcop_0.95.zip Reference manual: sbgcop.pdf
標(biāo)簽： Semiparametric estimation parameters estimates
上傳時(shí)間： 2016-04-15
上傳用戶：talenthn
sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a Gaussian copula, treating the univariate Marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data. Version: 0.95 Date: 2007-03-09 Author: Peter Hoff Maintainer: Peter Hoff <hoff at stat.washington.edu> License: GPL Version 2 or later URL: http://www.stat.washington.edu/hoff CRAN checks: sbgcop results Downloads: Windows binary: sbgcop_0.95.zip
標(biāo)簽： Semiparametric estimation parameters estimates
上傳時(shí)間： 2016-04-15
上傳用戶：qilin
sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a Gaussian copula, treating the univariate Marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data. Version: 0.95 Date: 2007-03-09 Author: Peter Hoff Maintainer: Peter Hoff <hoff at stat.washington.edu> License: GPL Version 2 or later URL: http://www.stat.washington.edu/hoff CRAN checks: sbgcop results Downloads: Reference manual: sbgcop.pdf
標(biāo)簽： Semiparametric estimation parameters estimates
上傳時(shí)間： 2014-12-08
上傳用戶：一諾88
使用matlab實(shí)現(xiàn)gibbs抽樣，MCMC: The Gibbs Sampler 多元高斯分布的邊緣概率和條件概率 Marginal and conditional distributions of multivariate normal distribution
上傳時(shí)間： 2019-12-10
上傳用戶：real_
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