NEWS	R Documentation

News for R Package rrcov

CHANGES in rrcov VERSION 1.6-2 (2022-02-08)

NEW FEATURES

• Examples for PCA/adjustment for skewed data and PCA/percentage of explained variance added

BUG FIXES

• minor differences in tests for PcaProj() on some platforms fixed

• scoreplot() corrected to show the labels of the samples

CHANGES in rrcov VERSION 1.6-1 (2022-01-21)

NEW FEATURES

• Data set Fruit added: fruit.rda

• URLs in Rd files replaced by DOIs to fix for the migration of the www.jstatsoft.org to a new editorial system (see mail from Achim Zeileis from 06.10.2021)

BUG FIXES

• Fixed a problem when showing the percentage of explained variance in summary() of all PCA functions when k is chosen to be less than the number of variables in the input data matrix (k < p). The returned object contains now additionally the rank of the input matrix, the original eigenvalues (of all variables) and the original total variance, if available.

CHANGES in rrcov VERSION 1.6-0 (2021-08-27)

NEW FEATURES

• PcaHubert: option for adjusted outlyingness for skewed data added

• Data set Computer Hardware added: machines.rda

• Data set Wolves added: wolves.rda

BUG FIXES

• Fixed some URLs, particularly the reference to javasoft.org

CHANGES in rrcov VERSION 1.5-5 (2020-07-31)

BUG FIXES

• PcaHubert will crash if X is 1-dimensional and mcd=FALSE: fixed.

• Fixed 'noLD' issues in tlda.R and okg4.R

• Fixed a problem with wrong scores in PcaProj() (reported by Matthieu Lesnoff <matthieu.lesnoff@gmail.com>)

• Fixed a problem with nsamp="exact" or nsamp="best" in CovMve(), CovSest() (reported by Claudio Agostinelli) - these functions, differently from CovMcd, should not take non-numeric 'nsamp'

CHANGES in rrcov VERSION 1.5-2 (2020-01-14)

NEW FEATURES

• Added parameter 'control' to Linda - to select the robust location and covariance estimator to use in LDA. Now any estimator derived from class 'Cov' can be used, even such that are not in 'rrcov'. Return this parameter in the returned S4 object.

• Linda returns now the location and covariance estimator used as 'covobj'. This is useful for controlling cross-validation, for example.

• Linda and LdaClassic use generalized inverse if the common covariance matrix is singular.

BUG FIXES

• Fixed an issue the 'predict' function.

• Removed the dependence on packages 'cluster' and 'ellipse'.

CHANGES in rrcov VERSION 1.4-9 (2019-11-25)

NEW FEATURES

• Added data set diabetes; data set soil from package rrcovHD moved here.

• Linear and quadratic discriminant analysis can use the MRCD estimates.

BUG FIXES

• Fixed an issue with CovControlMcd(nsamp="deterministic") - this would not work, because nsamp was defined in the class definition as "numeric". Now it is "Cnumeric" - union of "character" and "numeric'.

• Corrected the code for Minimum Regularized Covariance Determinant estimator (MRCD) - CovMrcd() - the step of adjusting the eignevalues in r6pack() is excluded now because it has no effect when n > p.

CHANGES in rrcov VERSION 1.4-7 (2018-11-14)

NEW FEATURES

• Added Minimum Regularized Covariance Determinant estimator (MRCD) (Boudt et al. 2018) - functions CovMrcd() and CovControlMrcd()

• Added data set octane; data set olitos from package rrcovHD moved here.

• The 'pairs' plot is now available for classical covariance matrix