R-VGAM-1.0.5.tgz


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Description

R-VGAM - Vector Generalized Linear and Additive Models

Property Value
Distribution NetBSD 7.1
Repository NetBSD amd64
Package filename R-VGAM-1.0.5.tgz
Package name R-VGAM
Package version 1.0.5
Package release -
Package architecture amd64
Package type tgz
Category math
Homepage http://www.stat.auckland.ac.nz/~yee/VGAM/
License gnu-gpl-v2
Maintainer -
Download size 7.00 MB
Installed size 7.93 MB
Vector generalized linear and additive models, and associated models
(Reduced-Rank VGLMs, Quadratic RR-VGLMs, Reduced-Rank VGAMs). This
package fits many models and distribution by maximum likelihood
estimation (MLE) or penalized MLE. Also fits constrained ordination
models in ecology.

Alternatives

Package Version Architecture Repository
R-VGAM-1.0.5.tgz 1.0.5 i386 NetBSD
R-VGAM - - -

Requires

Name Value
R >= 3.4.0
g95 >= 0.91

Download

Type URL
Mirror ftp.netbsd.org
Binary Package R-VGAM-1.0.5.tgz
Source Package R-VGAM

Install Howto

Install R-VGAM tgz package:

# pkg_add R-VGAM

Files

Path
/usr/pkg/lib/R/library/VGAM/libs/VGAM.so

See Also

Package Description
R-XML-3.98.1.9.tgz Tools for parsing and generating XML within R
R-abind-1.4.5.tgz Combine multi-dimensional arrays
R-akima-0.6.2.tgz Linear or cubic spline interpolation for irregular gridded data
R-aplpack-1.3.0.tgz Functions for drawing special plots
R-assertthat-0.2.0.tgz Easy pre and post assertions
R-base64enc-0.1.3.tgz Tools for base64 encoding
R-bbmle-1.0.20.tgz Tools for general maximum likelihood estimation
R-bindr-0.1.1.tgz Parametrized Active Bindings
R-bit-1.1.14.tgz Class for vectors of 1-bit booleans
R-bitops-1.0.6.tgz Functions for Bitwise operations on integer vectors
R-blob-1.1.1.tgz Simple S3 Class for Representing Vectors of Binary Data ('BLOBS')
R-car-2.1.6.tgz Accompanies An R Companion to Applied Regression, 2nd Edition
R-carData-3.0.2.tgz Companion to Applied Regression Data Sets
R-chron-2.3.47.tgz Chronological objects which can handle dates and times
R-circular-0.4.93.tgz Circular Statistics, from "Topics in circular Statistics"
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