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Marginal

  • MFA: Marginal Fisher Analysis

    MFA: Marginal Fisher Analysis

    标签: Analysis Marginal Fisher MFA

    上传时间: 2014-08-02

    上传用户:cuibaigao

  • Marginal Fisher Analysis算法

    Marginal Fisher Analysis算法,可用于降维,注释有使用说明!供大家学习交流!

    标签: Marginal Analysis Fisher 算法

    上传时间: 2013-12-25

    上传用户:天涯

  • This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise

    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.

    标签: instantaneous algorithm Bayesian Gaussian

    上传时间: 2013-12-19

    上传用户:jjj0202

  • sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a G

    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

    标签: Semiparametric estimation parameters estimates

    上传时间: 2016-04-15

    上传用户:talenthn

  • sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a G

    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

    标签: Semiparametric estimation parameters estimates

    上传时间: 2016-04-15

    上传用户:qilin

  • sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a G

    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

    标签: Semiparametric estimation parameters estimates

    上传时间: 2014-12-08

    上传用户:一诺88

  • gibbs抽样 matlab实现

    使用matlab实现gibbs抽样,MCMC: The Gibbs Sampler  多元高斯分布的边缘概率和条件概率  Marginal and conditional distributions of multivariate normal distribution

    标签: matlab gibbs 抽样

    上传时间: 2019-12-10

    上传用户:real_