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Description: 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
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Size: 5273 |
Author: 陈远 |
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Description: 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
Platform: |
Size: 40754 |
Author: 陈远 |
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Description: 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
Platform: |
Size: 94209 |
Author: 陈远 |
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Description: 一个很有用的EM算法程序包，可用于混合高斯模型，值得一看哦
Platform: |
Size: 18132 |
Author: 林枫 |
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Description: 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
Platform: |
Size: 5120 |
Author: cy |
Hits:
Description: 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
Platform: |
Size: 39936 |
Author: cy |
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Description: 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
Platform: |
Size: 94208 |
Author: cy |
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Description: 一个很有用的EM算法程序包，可用于混合高斯模型，值得一看哦-A useful package of the EM algorithm can be used in mixed-Gaussian model, see Oh
Platform: |
Size: 18432 |
Author: 林枫 |
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Description: 不完全数据分析MATLAB程序（部分信息重建）：最小均方估计、协方差矩阵、缺失值推测-Analysis of incomplete datasets: Estimation of mean values and covariance matrices and imputation of missing values
Platform: |
Size: 24576 |
Author: 邓玥琳 |
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Description: 预测单倍型根据基因型数据,根据已经知道的数据,预测未知的数据- The program PHASE implements methods for estimating haplotypes from population genotype data described in
Stephens, M., and Donnelly, P. (2003). A comparison of Bayesian methods for haplotype reconstruction from population genotype data. American Journal of Human Genetics, 73:1162-1169.
Stephens, M., Smith, N., and Donnelly, P. (2001). A new statistical method for haplotype reconstruction from population data. American Journal of Human Genetics, 68, 978--989.
Stephens, M., and Scheet, P. (2005). Accounting for Decay of Linkage Disequilibrium in Haplotype Inference and Missing-Data Imputation. American Journal of Human Genetics, 76:449-462.
The software also incorporates methods for estimating recombination rates, and identifying recombination hotspots:
Crawford et al (2004). Evidence for substantial fine-scale variation in recombination rates across the human genome. Nature Genetics,.
The software is free for non-commercial use, and may be licensed for commercial use
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Size: 246784 |
Author: zcrself |
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Description: paper describing successive imputation
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Size: 1804288 |
Author: Bimlesh |
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Description: 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.
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Size: 2048 |
Author: FOUFOU2 |
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Description: The Impact of Missing Values Imputation Methods in cDNA Microarrays on Downstream Data Analysis
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Size: 325632 |
Author: Mohammed Adel |
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Description: Imputation Report – HapMap 3 reference panel
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Size: 2561024 |
Author: sundari |
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Description: SOM toolbox used as an imputation method
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Size: 3072 |
Author: hell4all |
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Description: 缺失数据的填补函数，用来估计缺失的数据。
single and mutiple imputation-Solves approximation to one of several pdes to interpolate and extrapolate holes in an array
Platform: |
Size: 4096 |
Author: 王进 |
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Description: Matlab 工具箱，基于正则期望最大化方法(Regularied Expectation Maximization)的数据填充。-A Matlab toolbox based on the regularied expectation maximization (RegEM) based data imputation.
Platform: |
Size: 28672 |
Author: zxcvb |
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Description: 平均插补：对缺失的数据，用已记录数据的平均值进行填补-mean imputation
Platform: |
Size: 2048 |
Author: fan |
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Description: C语言实现的插补程序，用于数控开发，方便移植51或tsm32-C language implementation of the imputation procedure for numerical development, ease of porting 51 or tsm32
Platform: |
Size: 1024 |
Author: yelang |
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Description: tMissing data in large insurance datasets affects the learning and classification accuracies in predictivemodelling. Insurance datasets will continue to increase in size as more variables are added to aid inmanaging client risk and will therefore be even more vulnerable to missing data. This paper proposes ahybrid multi-layered artificial immune system and genetic algorithm for partial imputation of missingdata in datasets with numerous variables. The multi-layered artificial immune system creates and storesantibodies that bind to and annihilate an antigen. The genetic algorithm optimises the learning processof a stimulated antibody. The uation of the imputation is performed using the RIPPER, k-nearestneighbour-tMissing data in large insurance datasets affects the learning and classification accuracies in predictivemodelling. Insurance datasets will continue to increase in size as more variables are added to aid inmanaging client risk and will therefore be even more vulnerable to missing data. This paper proposes ahybrid multi-layered artificial immune system and genetic algorithm for partial imputation of missingdata in datasets with numerous variables. The multi-layered artificial immune system creates and storesantibodies that bind to and annihilate an antigen. The genetic algorithm optimises the learning processof a stimulated antibody. The uation of the imputation is performed using the RIPPER, k-nearestneighbour
Platform: |
Size: 1945600 |
Author: yangs |
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