micompr v1.1.0

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Multivariate Independent Comparison of Observations

A procedure for comparing multivariate samples associated with different groups. It uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using a number of statistical methods. The procedure is independent of the distributional properties of samples and automatically selects features that best explain their differences, avoiding manual selection of specific points or summary statistics. It is appropriate for comparing samples of time series, images, spectrometric measures or similar multivariate observations.

Readme

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Summary

The micompr R package implements a procedure for comparing multivariate samples associated with different groups. The procedure uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using a number of statistical methods. This technique is independent of the distributional properties of samples and automatically selects features that best explain their differences, avoiding manual selection of specific points or summary statistics. The procedure is appropriate for comparing samples of time series, images, spectrometric measures or similar multivariate observations.

How to install

Install the development version from GitHub with the following command (requires the devtools package):

devtools::install_github("fakenmc/micompr")

A stable version of the package is available on CRAN and can be installed with the following instruction:

install.packages("micompr")

Documentation

All methods and functions are fully documented and can be queried using the built-in help system. After installation, to access the man pages, invoke the micompr help page as follows:

help("micompr")

Additionally, the package contains two vignettes with a number of examples.

References

Practice

Theory

License

MIT License

Functions in micompr

Name Description
cmpoutput Compares output observations from two or more groups
concat_outputs Concatenate multiple outputs with multiple observations
plot.assumptions_paruv Plot p-values for testing the assumptions of the parametric tests used in output comparison
plot.cmpoutput Plot comparison of an output
pphpc_noshuff Data from two implementations of the PPHPC model, one of which has agent list shuffling deactivated
pphpc_ok Data from two similar implementations of the PPHPC model
summary.assumptions_cmpoutput Summary method for the assumptions of parametric tests used in a comparison of an output
summary.assumptions_micomp Summary method for the assumptions of parametric tests used in multiple comparisons of outputs
assumptions.micomp Get assumptions for parametric tests performed on each comparisons
assumptions_manova Determine the assumptions for the MANOVA test
plotcols Default colors for plots in micomp package
pphpc_diff Data from two implementations of the PPHPC model, one of which setup with a different parameter
print.assumptions_manova Print information about the assumptions of the MANOVA test
print.assumptions_micomp Print information about the assumptions concerning the parametric tests performed on multiple comparisons of outputs
grpoutputs Load and group outputs from files
micomp Multiple independent comparisons of observations
plot.assumptions_manova Plot p-values for testing the multivariate normality assumptions of the MANOVA test
pst Concatenate strings without any separator characters
plot.assumptions_micomp Plot p-values for testing the assumptions of the parametric tests used in multiple output comparison
pvalcol Associate colors to p-values
pphpc_testvlo Data for testing variable length outputs
toLatex.cmpoutput Convert cmpoutput object to LaTeX table
toLatex.micomp Convert micomp object to LaTeX table
print.assumptions_cmpoutput Print method for the assumptions of parametric tests used in a comparison of an output
summary.cmpoutput Summary method for comparison of an output
summary.grpoutputs Summary method for grouped outputs
assumptions Parametric tests assumptions
assumptions.cmpoutput Get assumptions for parametric tests performed on output comparisons
plot.grpoutputs Plot grouped outputs
plot.micomp Plot projection of output observations on the first two dimensions of the principal components space
print.assumptions_paruv Print information about the assumptions of the parametric test
print.cmpoutput Print information about comparison of an output
summary.micomp Summary method for multiple comparisons of outputs
tikzscat Simple TikZ scatter plot
assumptions_paruv Determine the assumptions for the parametric comparison test
print.grpoutputs Print information about grouped outputs
centerscale Center and scale vector
plot.assumptions_cmpoutput Plot p-values for testing the assumptions of the parametric tests used in output comparison
micompr micompr: multivariate independent comparison of observations
print.micomp Print information about multiple comparisons of outputs
pvalf Format p-values
pvalf.default Default p-value formatting method
tscat_apply Multiple TikZ 2D scatter plots for a list of output comparisons.
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Vignettes of micompr

Name
paper.Rnw
tolatex-examples.Rnw
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Details

Date 2018-03-09
License MIT + file LICENSE
URL https://github.com/fakenmc/micompr
BugReports https://github.com/fakenmc/micompr/issues
LazyData true
Encoding UTF-8
VignetteBuilder knitr
RoxygenNote 6.0.1
NeedsCompilation no
Packaged 2018-03-09 16:27:30 UTC; nfachada
Repository CRAN
Date/Publication 2018-03-09 16:36:22 UTC

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