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
12 projects in result set.
Clusterwise Effect Regression  This software implements an algorithm that proposes variable clustering within high dimensional linear and probit regression models. The estimation strategy is based on mixed Gibbs Sampling and Stochastic EM algorithm.  
Tags: C++, Clustering, biostatistics, high dimentional data, multivariate regression, regression  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20130820 09:47 
Fast Regularized Canonical Correlation  This R package implements the Fast Regularized Canonical Correlation method.  
Tags: Bioinformatics, data mining, high dimentional data, regularization  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20120910 18:11 
HighDimensional Metrics  This package provides the implementation of selected highdimensional statistical and econometric methods which enable estimation and valid postselection inference on treatment and structural parameters in a highdimensional setting.  
Tags: Treatment Effects, Causal effects, Machine Learning, Multivariate Regression, Structural Equation Modelling, Instrumental Variables, high dimentional data, lasso  

Activity Percentile: 0 Activity Ranking: 0 Registered: 20150524 13:36 
Joint segmentation [MOVED TO GITHUB]  This package implements functions to quickly segment multivariate signals into piecewise constant profiles. Typical application: joint segmentation of DNA copy number signals obtained from Single Nucleotide Polymorphism microarrays in cancer studies.  
Tags: Bioinformatics, CNV, Cancer, Copynumber, biostatistics, break detection, high dimentional data  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20130104 20:37 
MPAgenomics  This package contains an implementation of the lars algorithm for the lasso and fusion penalization. It works even if the number of covariate is greater than the number of individuals.  
Tags: lasso, lars, sparse linear model, C++, genomic, Bioinformatics, Multivariate Analysis, Multivariate Regression, high dimentional data, low sample size high dimensional data, penalized regression  

Activity Percentile: 0 Activity Ranking: 0 Registered: 20130418 16:20 
OOMPA  OOMPA is a suite of R packages for the analysis of gene expression (RNA), proteomics profiling , and other high throughput molecular biology data. OOMPA uses S4 classes to construct objectoriented tools with a consistent user interface.  
Tags: Bioinformatics, Clustering, Differential expression analysis, Gene expression, Multiple Comparisons, Multivariate Analysis, bioinformatics, clustering, false discovery rate, gene expression, high dimentional data, microarray, multivariate, permutation tests  

Activity Percentile: 0 Activity Ranking: 0 Registered: 20130829 17:48 
RNetCDF  R Interface to NetCDF Datasets  
Tags: ncdf files, API, datasets, high dimentional data, large data, metadata, missing data, spatial data  

Activity Percentile: 29 Activity Ranking: 30 Registered: 20141230 23:43 
concurrence topology  Concurrence topology is a method for analyzing the dependence structure in multivariate binary data. It is particularly well suited for describing highorder dependence.  
Tags: Multivariate Analysis, categorical, fMRI, high dimentional data, low sample size high dimensional data, multivariate, multivariate statistics, nonparametrics, nonparametric, time series  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20130220 19:07 
flip: Multivariate Permutation Tests  A collection of Univariate and multivariate (i.e. overall and multiplicity control) permutation and rotation tests. dev page at https://github.com/livioivil/flip  
Tags: ANOVA, Multiple Comparisons, Multivariate Analysis, Multivariate Regression, Multivariate Techniques, R, RForge, biostatistics, bivariate, bivariate analysis, categorical, conditional inference, high dimentional data, missing, missing data, missing values, mixed model, mixture model, mixture modelling, multi, multidimensions, multivariate, multivariate regression, multivariate statistics, nonparametric, nonparametric anova, permutation test, permutation tests, statistical inference  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20131016 19:04 
general multipletable data management  Our objective is to develop classes of objects that (1) make handling multipletable data sets easier and (2) seamlessly integrate with existing R plotting and modelfitting functions; our philosophy is to keep data management and data analysis separate.  
Tags: Ecology, community ecology, database, ecology, high dimentional data  

Activity Percentile: 0 Activity Ranking: 0 Registered: 20110727 02:07 
penalizedSVM  Feature selection for SVM classification in high dimensions using penalty functions L1, SCAD, Elastic Net (L1+L2) and Elastic SCAD (SCAD+L2) SVM. Choice of datadependent tuning parameters: beside the standard fixed grid an interval search is implemented  
Tags: Classification, feature selection, machine learning, tuning parameters, penalty functions, high dimentional data, low sample size high dimensional data, Bioinformatics, Machine Learning  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20120619 15:40 
pi0 estimators  Estimation of the proportion of true null hypotheses (pi0) from a large number of hypothesis tests; Non/parametric recovery of noncentrality parameter distribution; False discovary rates (FDR) computation.  
Tags: Multiple Comparisons, dissimilarity, distance, high dimentional data, microarray, multidimensional scaling, multiplicity, permutation tests, semiparametric model, spline, variable selection  

Activity Percentile: 0 Activity Ranking: 0 Registered: 20100321 02:01 