Software Map
Tag cloud  Project Tree  Project List
ANOVA Bayesian Bioinformatics Bioinformatics & Biostatistics Biostatistics C++ Cancer Chemoinformatics Classification Clustering Copynumber DNA Ecology Economics Finance GUI Genetic Algorithms Genetics HTML Machine Learning Machine learning Mixture Multiple Comparisons Multivariate Analysis Multivariate Regression Multivariate Techniques Next generation Sequencing ODE Phylogeny R RForge Rcmdr Regression SNP Statistics Time series Visualization Wholegenome bioinformatics biostatistics break detection categorical change detection classification clustering community ecology data mining database datasets dissimilarity distance distributions diversity dynamic systems ecological models ecology econometrics economics epidemiology finance gene expression generalized linear models genetics graphics high dimentional data likelihood linear models linear programming machine learning microarray missing data missing values mixed effect models mixed model model comparison model estimation model selection movement multivariate multivariate regression multivariate statistics nonparametrics nonlinear models nonparametric optimization parametric model permutation tests phylogeny plotting political analysis prediction psychology raster regression remote sensing reporting robust robust statistics simulation soil spatial spatial autocorrelation spatial classes spatial data spatial methods spatial point patterns spatial regression spatiotemporal species distribution models survival teaching text mining time series visualization
3 projects in result set.
MAMI  MAMI: An Rpackage which performs model selection/averaging on multiply imputed datasets and combines the resulting estimates. The package also provides access to less frequently used model averaging techniques and offers integrated bootstrap estimation.  
Tags: imputation, missing data, model averaging, model selection, multiple imputation  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20151102 12:40 
Statistical Data Preparation Indicators  During the statistical data preparation process stages of the data are archived (at least raw and the final data). Indicators on missing values, imputations and their impact help to judge the effect of the process and the quality of the final data.  
Tags: missing values, imputation, flags, data quality, process quality  

Activity Percentile: 0 Activity Ranking: 0 Registered: 20170121 14:39 
missForest  The missForest package enables the user to perform straightforward missing value imputation on basically any kind of data. Additionally, the algorithm supplies the user with an outofbag imputation error estimate.  
Tags: imputation, random forest, missing, missing data, missing values, missingness, outofbag, Bioinformatics, Classification, Multivariate Regression, Multivariate Techniques, R  

Activity Percentile: 0 Activity Ranking: 0 Registered: 20110518 08:28 