Michael Friendly
2016-Jun-08 14:58 UTC
[R-pkgs] New versions of heplots, candisc, mvinfluence and matlib on CRAN
# New versions of heplots, candisc, mvinfluence and matlib on CRAN
# ----------------------------------------------------------------
New versions of my packages designed for visualization of multivariate
linear models have recently been submitted to CRAN. The matlib package
also contains some plot methods for vector diagrams representing linear
algebra concepts in multivariate statistical methods.
## heplots
## -------
Devel URL: https://r-forge.r-project.org/projects/heplots/
Issue tracker: https://r-forge.r-project.org/tracker/?group_id=24
Provides HE plot and other functions for visualizing hypothesis
tests in multivariate linear models. HE plots represent sums-of-squares-and-
products matrices for linear hypotheses and for error using ellipses (in two
dimensions) and ellipsoids (in three dimensions).
Version 1.3-0 (2016-06-03)
o In cqplot(), pch, col, and cex can now be vectors
o Bump version, prepare for release
Version 1.2-1 (2016-05-19)
o in coefplot.mlm(), now pass `label.pos` to label.ellipse()
o added Mahalanobis() for classical and robust squared distances; handles
missing data gracefully and provides a confidence envelope
o added SocialCog data [Thx: Leah Hartman]
o added cqplot() of Mahalanobis distances as a plot method for an mlm
and for multivariate data
Version 1.2-0 (2016-04-27)
o covEllipses() extended to more than two variables, giving a
scatterplot matrix plot
o plot.boxM() now can plot other measures of the eigenvalues of the
covariance matrices,
useful for understanding the properties of the test.
o added bartlettTests() for a collection of univariate Bartlett tests
o added leveneTests() for a collection of univariate Levene tests
o added NeuroCog data, a simple one-way MANOVA [Thx: Leah Hartman]
o label.ellipse() now uses a much more flexible `label.pos` argument for
positioning the
text labels used in heplot() and friends.
## candisc
## -------
Devel URL: https://r-forge.r-project.org/projects/candisc/
Functions for computing and visualizing generalized canonical discriminant
analyses and canonical correlation analysis for a multivariate linear model.
Traditional canonical discriminant analysis is restricted to a one-way
'MANOVA'
design and is equivalent to canonical correlation analysis between a set of
quantitative response variables and a set of dummy variables coded from the
factor variable. The 'candisc' package generalizes this to higher-way
'MANOVA'
designs for all factors in a multivariate linear model, computing canonical
scores and vectors for each term. The graphic functions provide low-rank
(1D,
2D, 3D) visualizations of terms in an 'mlm' via the
'plot.candisc' and
'heplot.candisc' methods. Related plots are now provided for canonical
correlation analysis when all predictors are quantitative.
Changes in version 0.7-1 (2016-05-23)
o respect var.lwd in 2D plot.candisc()
o heplot.candisc() gets a rev.axes argument to reverse the axes and a
var.pos
argument to position variable labels
o vectors() now produces nicer arrow head a la matlib::vectors()
o added var.pos argument to plot.candisc
o allow to suppress likelihood ratio tests in print.candisc
Changes in version 0.7-0 (2016-04-25)
o Added Wine data -- three cultivars with a very simple canonical
structure
o Added ellipses to plot.candisc(); enhanced candisc.Rd documentation
o Added varOrder() for effect ordering in MLMs-- permutations of
variables
according to various criteria for scatterplot matrices, etc.
o plot.candisc() gets a var.labels argument
o added method="colmean" and descending=T/F to varOrder()
o plot.candisc() gets a rev.axes argument
o fixed imports() in NAMESPACE for CRAN checks
## mvinfluence
## -----------
Devel URL: https://r-forge.r-project.org/projects/mvinfluence/
Computes regression deletion diagnostics for multivariate linear models and
provides some associated diagnostic plots. The diagnostic measures
include hat-
values (leverages), generalized Cook's distance, and generalized squared
'studentized' residuals. Several types of plots to detect influential
observations are provided.
Version 0.8 (2016-06-02)
o Fixed problems for CRAN: NAMESPACE, Rd files
o Added more examples to Rd files
o Added infIndexPlot for index plots of diagnostic measures
o Fixed buglet in influencePlot re: rownames of result
## matlib
## ------
Devel URL: https://github.com/friendly/matlib
Issue tracker: https://github.com/friendly/matlib/issues
A collection of matrix functions for teaching and learning matrix
linear algebra as used in multivariate statistical methods. These
functions are
mainly for tutorial purposes in learning matrix algebra ideas using R.
In some
cases, functions are provided for concepts available elsewhere in R, but
where
the function call or name is not obvious. In other cases, functions are
provided
to show or demonstrate an algorithm. In addition, a collection of
functions are
provided for drawing vector diagrams in 2D and 3D, e.g., regvec() and
regvec2d()
for vector diagrams for the vector space representation of a
two-variable regression
model, plotEqn() and plotEqn3d() for diagrams of linear equations of the
form
A x = b.
matlib 0.7.3
- Changed gaussianElimination() by defining local ERO functions to make
the algorithm clearer;
in verbose mode, show each ERO.
- Added a draw argument to `vectors3d()` and `arrows3d()`, which
defaults to TRUE.
If FALSE, just returns returns the "reg.length" to help in scaling.
- Small cosmetic changes to regvec3d().
- Added a `showEig` function to draw eigenvectors superimposed on a
dataEllipse [MF]
matlib 0.7.2
- added argument `error.sphere` to `plot.regvec3d()` [JF]
- remove use of `lengths()` in `corner()` to avoid R version dependency
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept. & Chair, Quantitative Methods
York University Voice: 416 736-2100 x66249 Fax: 416 736-5814
4700 Keele Street Web:http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA