VGAMdata 1.0-2

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dc.contributor.author Yee, Thomas en
dc.contributor.author Gray, J en
dc.date.accessioned 2017-07-06T05:37:01Z en
dc.date.issued 2016-05-31 en
dc.identifier.citation 31 May 2016. Version: 1.0-2 en
dc.identifier.uri http://hdl.handle.net/2292/34047 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 VGAMdata 1.0-2 en
dc.type Software en
dc.rights.holder Copyright: The author en
pubs.author-url https://cran.r-project.org/package=VGAMdata en
pubs.version 1.0-2 en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.elements-id 617768 en
pubs.org-id Faculty of Science en
pubs.org-id Statistics en
pubs.record-created-at-source-date 2017-03-20 en


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