[R-pkgs] New versions of heplots, candisc, mvinfluence and matlib on CRAN

Michael Friendly friendly at yorku.ca
Wed Jun 8 16:58:49 CEST 2016

# 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 
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 
designs for all factors in a multivariate linear model, computing canonical
scores and vectors for each term. The graphic functions provide low-rank 
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 
     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 
   o Added ellipses to plot.candisc(); enhanced candisc.Rd documentation
   o Added varOrder() for effect ordering in MLMs-- permutations of 
     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 
the function call or name is not obvious. In other cases, functions are 
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 
for vector diagrams for the vector space representation of a 
two-variable regression
model, plotEqn() and plotEqn3d() for diagrams of linear equations of the 
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

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