QRforX, which produces consistent QR
decomposition results despite differences betweenbase::qr
and Matrix::qr functions.removeRedundant and
getRank to properly remove axes based on a
base::qr pivot strategy, but still avoiding the making of
large, dense matrices before using base::qr.R-dependency to >= 4.4.0checkers function that
assumed sparse-matrix (Matrix) format of an object without
coercing this format.predict.lm.rrpp and made the code more universal for
different model formulae..coef.lm.rrpp..lm.rrpp associated
with covariance matrices (causing non-adjusted matrices).subTest output from lm.rrpp.ws.anova.multi.model and
logL related to missing Pcov when GLS models
are used.lm.rrpp
and predict.lm.rrpp, and permutation of full model
residuals (with restrictions) to lm.rrpp.measurement.error.lm.rrpp.ws.verbose arguments to most analytical functions to
reduce dense results.getANOVAStats,
getPermInfo, getTerms, and
getModels) to accommodate verbose function
choices, plus allow users to easily extract objects as output.ICCstats, for calculating ICC
statistics for lm.rrpp fits.measurement.error, but
also added a plot utility function, focusMEonSubjects,
which builds off of plot.measurement.error, to focus
attention on specific plot details.interSubVar, a utility function to use
along with measurement.error, to visualize how variation
between replicate measures, within subjects, can affect inter-subject
variation.summary.lm.rrpp that produces
matrices of 0s. The issue was inherent to lm.rrpp, from
erroneous assignment of models, only for output (not for
mechanics).predict.lm.rrpp for QR-truncated
design matrices.print.progess conditions in
pairwise.Matrix::qrQ,
using rather, Matrix::qr.Q.pairwise.SE added to coef.lm.rrpp for
calculating bootstrap standard error.plot.lm.rrppplot.ordinate to better work with
plot.default.plot.lm.rrpp diagnostic
plots.logLik.lm.rrpp to obtain
log-likelihood from an lm.rrpp object.scaleCov to scale covariance matrices
with linear or exponential scalars.model.comparison to include Z scores calculated
from log-likelihoods.predict.lm.rrpp for new data frames with
only one observation.SS.iter.main that incidentally wrapped
RSS.model by rows rather than columns.summary.lm.rrpp that did not properly
index a matrix of RSS.model.plot.lm.rrpp for diagnostic plots,
which forced an error.Matrix class
matrices for more efficient computation, when needed.checkers function to use better algorithms to
switch among different class matrices, to better save memory and
increase computation time efficiency.anc.BM for singleton nodes.lm.rrpp to have less detritus during use. Also
adjusted/updated support functions to work with updates.data.frame objects.lm.args.from.formula for intercept only
models with covariance matrices.lm.rrpp support functions.logL support function for non-full rank
design matrices.na.omit.rrpp.data.frame added for handling missing
data.looCV function added as diagnostic tool.coef.lm.rrpp updated to provide results based on
SS.type, rather than type III SS, only.R.coef.lm.rrpplm.rrpp (passed onto
lm).as.matrix names dropping in support
code.lm.rrpp using
Matrix package and sparse matrix calculations. This speeds
up computation time and requires far less memory allocation.lm.rrpp function now has a an argument,
turbo, which can suppress calculating coefficients in
random permutations, if unneeded, which can speed up analysis of large
data sets.convert2ggplot, for coercing
RRPP plots into ggplot objects.plot.predict.lm.rrpp.effect.size.plot.ordinate.predict.lm.rrpp so that functions in formulae
are permissible.summary.pairwise to perform degree
transformations rather than print.summary.pairwise, so that
objects saved are the same as objects printed.model.comparison.manova.update pc dimension issue (output)xlim and ylim to be adjustable in
plot.ordinate.manova.update to have more efficient code and
better notes.summary.manova.lm.rrpp that mixed up
rows and columns of a matrix of random stats.lm.rrpp data
when converting a vector of data to a matrix.rrpp.data.frame to prevent downstream issues.trajectory.analysis with
univariate response data, omitting vector correlations output.ordinate function.summary.ordinate and plot.ordinate S3
functionsadd.tree function (for plotting with
plot.ordinate)lm.rrpp to provide better
flexibility for different formulas.$LM$data in lm.rrpp to be a model
frame rather than a data frame, consistent with $model from
lm.prep.lda A new function to generate arguments for
lda in the MASS library.classify deprecated (in favor of
prep.lda)verbose option with
manova.update. The function was optimized to provide
verbose output without having to slow down computation time.SS.iter (produced incorrect RSS).trajectoty.analysis.lm.rrpp function.tol and pc.no arguments to
model.comparison (were fixed before) so that users have
more control of the analysis.prcomp.lm.rrpp to work better with
missing data frames.trajectory.analysis traj.list issue, to not use
grep for sorting trajectories. (Now lexical ordering of interactions is
used.)det to determinant in all needing
functions, to use modulus for near-singular matricesplot.lm.rrpp (code lines out of
order)model.comparisonplot.procD.lmmanova.update functiontrajectory.analysis functionreveal.model.designs functionANOVA versus MANOVA in RRPPpairwise
function.procD.lm to better work with data in the global
environment rather than a data frame.print.summary.pairwise.model.comparison function.classify.pairwise.anova.lm.rrpp, related to GLS permutations and intercept
only models.anova.lm.rrpp, so that it can be called by other
functions/packages.pairwise function: allows pairwise comparison of means
or slopes for a lm.rrpp fit.anova.lm.rrppcoef.lm.rrpp tests when type II or type
III SS is chosen, to make sure that appropriate coefficients are
used.anova.lm.rrpp.r
coef.lm.rrpp.r
lm.rrpp.r
predict.lm.rrpp.r
RRPP.support.code.r
RRPP.utils.r
Added a NEWS.md file to track changes to the
package.