/R-statmod, Miscellaneous biostatistical modeling functions
1.4.26, Package name:
R-statmod-1.4.26, Maintainer: pkgsrc-users
Various statistical modeling functions including growth curve
comparisons, limiting dilution analysis, mixed linear models,
heteroscedastic regression, Tweedie family generalized linear models,
the inverse-Gaussian distribution and Gauss quadrature.
Required to run:
] Required to build:
Master sites: (Expand)
Version history: (Expand)
- (2016-11-06) Updated to version: R-statmod-1.4.26
- (2016-04-09) Updated to version: R-statmod-1.4.24
- (2015-05-30) Updated to version: R-statmod-1.4.21
- (2014-07-13) Updated to version: R-statmod-1.4.20
- (2014-03-11) Updated to version: R-statmod-1.4.18
- (2013-07-07) Updated to version: R-statmod-1.4.17
CVS history: (Expand)
| 2016-11-06 03:54:08 by Wen Heping | Files touched by this commit (2) | |
Update to 1.4.26
28 August 2016: statmod 1.4.26
- Fortran function gaussq2 updated to Fortran 77.
5 August 2016: statmod 1.4.25
- Add CITATION file.
- pinvgauss() now uses an asymptotic approximation to compute right
tail probabilities for extreme large quantiles. This allows it to
give correct right tail probabilities for virtually any quantile.
- Fix to qinvgauss() to avoid NA values when computing extreme tail
quantiles where the inverse Gaussian density is subject to floating
- Bug fix to qresiduals() and qresid.invgauss() for the inverse
| 2016-04-09 10:36:34 by Wen Heping | Files touched by this commit (2) | |
Update to 1.4.24
2 February 2016: statmod 1.4.24
- speedup for rinvgauss() by replacing rchisq() with rnorm() and
rbinom() with runif().
- speedup for qinvgauss() by using qgamma as starting approximation
for very small right tail probabilities, and inverse chisq as
starting approximation for very small left tail probabilities.
- qinvgauss() now computes Newton step using log probabilities
and a Taylor series expansion for small steps. This improves
accuracy in extreme cases. The stopping criterion for the Newton
iteration has been revised.
- Bug fix to dinvgauss(), pinvgauss() and qinvgauss() which were not
preserving attributes of the first argument.
30 December 2015: statmod 1.4.23
- qinvgauss() has been improved to return best achievable machine
accuracy. It now checks for backtracking of the Newton iteration.
- dinvgauss() and pinvgauss() now check for a wider range of special
cases. This allows them to give valid results in some cases
for infinite or missing parameter values and for x outside the
support of the distribution.
26 October 2015: statmod 1.4.22
- Functions needed from the stats and graphics packages are now
explicitly imported into the package NAMESPACE.
| 2015-11-04 00:33:46 by Alistair G. Crooks | Files touched by this commit (262) |
Add SHA512 digests for distfiles for math category
Problems found locating distfiles:
Package dfftpack: missing distfile dfftpack-20001209.tar.gz
Package eispack: missing distfile eispack-20001130.tar.gz
Package fftpack: missing distfile fftpack-20001130.tar.gz
Package linpack: missing distfile linpack-20010510.tar.gz
Package minpack: missing distfile minpack-20001130.tar.gz
Package odepack: missing distfile odepack-20001130.tar.gz
Package py-networkx: missing distfile networkx-1.10.tar.gz
Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz
Package quadpack: missing distfile quadpack-20001130.tar.gz
Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden). All existing
SHA1 digests retained for now as an audit trail.
| 2015-05-30 12:50:34 by Wen Heping | Files touched by this commit (2) | |
Update to 1.4.21
30 March 2015: statmod 1.4.21
- qinvgauss() now treats input arguments of different lengths or NA
parameter values more carefully.
- elda() now gracefully removes structural zeros, i.e., rows where
the number of cells or the number of assays is zero.
- S3 print and plot methods for "limdil" class now registered.
- Use of require("tweedie") in the qres.tweedie() code replaced by
| 2014-07-13 14:47:38 by Wen Heping | Files touched by this commit (2) | |
Update to 1.4.20
30 May 2014: statmod 1.4.20
- Considerable work on the inverse Gaussian functions dinvgauss(),
pinvgauss(), qinvgauss() and rinvgauss(). The parameter arguments
are changed to mean, shape and dispersion instead of mu and lambda.
The functions now include arguments lower.tail and log.p, meaning
that right-tailed probabilities can be used and probabilities can
be specified on the log-scale. Good numerical precision is
maintained in these case. The functions now respect attributes,
so that a matrix argument for example will produce a matrix result.
Checking is now done for missing values and invalid parameter
values on an element-wise basis. A technical report has been
written to describe the methodology behind qinvgauss().
- This file has been renamed to NEWS instead of changelog.txt.
- The introductory help page previously called 1.Introduction is now
13 April 2014: statmod 1.4.19
- qinvgauss() now uses a globally convergent Newton iteration, which
produces accurate values for a greater range of parameter values.
- glmnb.fit() now supports weights.
| 2014-03-09 15:28:57 by Wen Heping | Files touched by this commit (2) | |
Update to 1.4.18
27 September 2013: statmod 1.4.18
- Update reference for permp().
- bug fix to elda() so that it returns NA for the tests instead of
giving an error when the Fisher information for the slope isNA.
- Exact roles of authors specified in DESCRIPTION file.
- All usage lines in help files wrapped at 90 characters to ensure
that code is not truncated in pdf manual.
| 2013-07-07 13:07:18 by Wen Heping | Files touched by this commit (2) | |
Update to 1.4.17
(No upstream changelog)
| 2012-11-30 14:55:48 by Wen Heping | Files touched by this commit (2) | |
Update to 1.4.16