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 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 stochastic processes survival teaching text mining time series visualization
2 projects in result set.
Compositional Data Analysis in Practice  easyCODA is an R package for analysing compositional data, based on the logratio transformation. The package includes some basic plotting functions as well as the multivariate methods of logratio analysis, correspondence analysis and redundancy analysis.  
Tags: principal component analysis, logratio transformation, Multivariate Analysis, dimension reduction, multidimensional scaling, correspondence analysis  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20180501 16:26 
Thresher  Thresher is a comprehensive, statistical approach to class discovery combining PCA with hierarchical clustering. It can (1) identify outliers, (2) estimate the number of subgroups, and (3) automate the selection of metrics and linkage rules.  
Tags: Bioinformatics, Clustering, Mixture, PCA, bioinformatics, clustering, dimension reduction  

Activity Percentile: 69 Activity Ranking: 17 Registered: 20140508 14:18 