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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.rrpp
plot.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.rrpp
lm.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.comparison
plot.procD.lm
manova.update
functiontrajectory.analysis
functionreveal.model.designs
functionANOVA versus MANOVA in RRPP
pairwise
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.rrpp
coef.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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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