Statistical models for categorical data: Brief review for applications in ecology

M. Rosário Ramos, Manuela M. Oliveira, José G. Borges, Marc Eric McDill

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

A brief review of statistical models for prediction of categorical data is presented, with emphasis on the binary type. Several methods have been adopted to build predictive models for binary and other types of categorical data and response variables. The focus here is on generalized linear models and generalized additive models, widely applied in problems in Ecology, when the goal is to fit a model to data of presence/absence type or any other categorical response. The estimation methods used for generalized linear models and generalized additive models as well its statistical properties are discussed. Some examples in ecology are addressed.

Original languageEnglish (US)
Title of host publicationProceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014
EditorsTheodore E. Simos, Theodore E. Simos, Charalambos Tsitouras, Theodore E. Simos
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735412873
DOIs
StatePublished - Mar 10 2015
EventInternational Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014 - Rhodes, Greece
Duration: Sep 22 2014Sep 28 2014

Publication series

NameAIP Conference Proceedings
Volume1648
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Other

OtherInternational Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014
CountryGreece
CityRhodes
Period9/22/149/28/14

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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    Ramos, M. R., Oliveira, M. M., Borges, J. G., & McDill, M. E. (2015). Statistical models for categorical data: Brief review for applications in ecology. In T. E. Simos, T. E. Simos, C. Tsitouras, & T. E. Simos (Eds.), Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014 [840015] (AIP Conference Proceedings; Vol. 1648). American Institute of Physics Inc.. https://doi.org/10.1063/1.4913055