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matthias-da

robCompositions:Compositional Data Analysis

Methods for analysis of compositional data including robust methods (<doi:10.1007/978-3-319-96422-5>), imputation of missing values (<doi:10.1016/j.csda.2009.11.023>), methods to replace rounded zeros (<doi:10.1080/02664763.2017.1410524>, <doi:10.1016/j.chemolab.2016.04.011>, <doi:10.1016/j.csda.2012.02.012>), count zeros (<doi:10.1177/1471082X14535524>), methods to deal with essential zeros (<doi:10.1080/02664763.2016.1182135>), (robust) outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) factor analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors, functional data analysis (<doi:10.1016/j.csda.2015.07.007>) and p-splines (<doi:10.1016/j.csda.2015.07.007>), contingency (<doi:10.1080/03610926.2013.824980>) and compositional tables (<doi:10.1111/sjos.12326>, <doi:10.1111/sjos.12223>, <doi:10.1080/02664763.2013.856871>) and (robust) Anderson-Darling normality tests for compositional data as well as popular log-ratio transformations (addLR, cenLR, isomLR, and their inverse transformations). In addition, visualisation and diagnostic tools are implemented as well as high and low-level plot functions for the ternary diagram.

Maintained by Matthias Templ. Last updated 1 months ago.

cpp

11 stars 9.21 score 226 scripts 2 dependents

cran

compositions:Compositional Data Analysis

Provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations) in the way proposed by J. Aitchison and V. Pawlowsky-Glahn.

Maintained by K. Gerald van den Boogaart. Last updated 1 years ago.

openblas

1 stars 6.35 score 36 dependents

tesselle

nexus:Sourcing Archaeological Materials by Chemical Composition

Exploration and analysis of compositional data in the framework of Aitchison (1986, ISBN: 978-94-010-8324-9). This package provides tools for chemical fingerprinting and source tracking of ancient materials.

Maintained by Nicolas Frerebeau. Last updated 25 days ago.

archaeologyarchaeological-sciencearchaeometrycompositional-dataprovenance-studies

5.21 score 26 scripts 1 dependents

bioc

geva:Gene Expression Variation Analysis (GEVA)

Statistic methods to evaluate variations of differential expression (DE) between multiple biological conditions. It takes into account the fold-changes and p-values from previous differential expression (DE) results that use large-scale data (*e.g.*, microarray and RNA-seq) and evaluates which genes would react in response to the distinct experiments. This evaluation involves an unique pipeline of statistical methods, including weighted summarization, quantile detection, cluster analysis, and ANOVA tests, in order to classify a subset of relevant genes whose DE is similar or dependent to certain biological factors.

Maintained by Itamar José Guimarães Nunes. Last updated 5 months ago.

classificationdifferentialexpressiongeneexpressionmicroarraymultiplecomparisonrnaseqsystemsbiologytranscriptomics

2 stars 4.30 score 4 scripts

sigbertklinke

exams.forge:Support for Compiling Examination Tasks using the 'exams' Package

The main aim is to further facilitate the creation of exercises based on the package 'exams' by Grün, B., and Zeileis, A. (2009) <doi:10.18637/jss.v029.i10>. Creating effective student exercises involves challenges such as creating appropriate data sets and ensuring access to intermediate values for accurate explanation of solutions. The functionality includes the generation of univariate and bivariate data including simple time series, functions for theoretical distributions and their approximation, statistical and mathematical calculations for tasks in basic statistics courses as well as general tasks such as string manipulation, LaTeX/HTML formatting and the editing of XML task files for 'Moodle'.

Maintained by Sigbert Klinke. Last updated 9 months ago.

2.70 score 1 scripts

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