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，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 [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 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 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 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
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
上传时间： 2019-12-10
上传用户：real_
