MASS, pbivnorm, stats, optimx, mnormt, numDeriv, Matrix

minqa, BB, ucminf, dfoptim, R (>= 3.1.0)

A flexible framework for fitting multivariate
ordinal regression models with composite likelihood methods. Methodological details are given in Hirk, Hornik, Vana (2020) <doi:10.18637/jss.v093.i04>.

R (>= 3.5.0), minqa, BB, ucminf, dfoptim

minqa, BB, ucminf, dfoptim, R (>= 3.5.0)

Multivariate outlier detection based on robust methods
Moritz Gschwandtner <e0125439@student.tuwien.ac.at> and
Peter Filzmoser <P.Filzmoser@tuwien.ac.at>
This packages was made for outlier detection using robust estimations
of location and covariance structure.

This packages was made for multivariate outlier detection.

Moritz Gschwandtner <e0125439@student.tuwien.ac.at> and Peter
Filzmoser <P.Filzmoser@tuwien.ac.at>

Peter Filzmoser <P.Filzmoser@tuwien.ac.at> and Moritz
Gschwandtner <e0125439@student.tuwien.ac.at>
R (>= 2.10), robustbase, compositions, robCompositions

robustbase, compositions, robCompositions, R (>= 2.10)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at> and
Moritz Gschwandtner <e0125439@student.tuwien.ac.at>

robustbase, compositions, robCompositions, sgeostat, R (>=
2.10)

robustbase, compositions, robCompositions, sgeostat, R (>=
2.15.1)

robustbase, compositions, robCompositions, sgeostat, R (>=
2.14)

various methods for multivariate outlier detection.

Multivariate Outlier Detection Based on Robust Methods
Various Methods for Multivariate Outlier Detection.

Various methods for multivariate outlier detection: arw, a Mahalanobis-type method with an adaptive outlier cutoff value; locout, a method incorporating local neighborhood; pcout, a method for high-dimensional data; mvoutlier.CoDa, a method for compositional data. References are provided in the corresponding help files.

Fast manipulation of symbolic multivariate polynomials
using the 'Map' class of the Standard Template Library.  The package
uses print and coercion methods from the 'mpoly' package (Kahle 2013,
"Multivariate polynomials in R".  The R Journal, 5(1):162), but offers
speed improvements.  It is comparable in speed to the 'spray' package
for sparse arrays, but retains the symbolic benefits of 'mpoly'.