dc.contributor.author |
Yee, Thomas |
en |
dc.date.accessioned |
2017-07-06T05:32:03Z |
en |
dc.date.issued |
2017-01-10 |
en |
dc.identifier.citation |
10 Jan 2017. Version: 1.0-3 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/34046 |
en |
dc.description.abstract |
An implementation of about 6 major classes of statistical regression models. At the heart of it are the vector generalized linear and additive model (VGLM/VGAM) classes, and the book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <doi:10.1007/978-1-4939-2818-7> gives details of the statistical framework and VGAM package. Currently only fixed-effects models are implemented, i.e., no random-effects models. Many (150+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE, using Fisher scoring. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs (i.e., with smoothing). The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)—these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.title |
VGAM 1.0-3 |
en |
dc.type |
Software |
en |
dc.rights.holder |
Copyright: The author |
en |
pubs.author-url |
https://cran.r-project.org/package=VGAM |
en |
pubs.version |
1.0-3 |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/RestrictedAccess |
en |
pubs.elements-id |
617205 |
en |
pubs.org-id |
Science |
en |
pubs.org-id |
Statistics |
en |
pubs.record-created-at-source-date |
2017-03-15 |
en |