Cargando…

A simple function for full‐subsets multiple regression in ecology with R

Full‐subsets information theoretic approaches are becoming an increasingly popular tool for exploring predictive power and variable importance where a wide range of candidate predictors are being considered. Here, we describe a simple function in the statistical programming language R that can be us...

Descripción completa

Detalles Bibliográficos
Autores principales:	Fisher, Rebecca, Wilson, Shaun K., Sin, Tsai M., Lee, Ai C., Langlois, Tim J.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	John Wiley and Sons Inc. 2018
Materias:	Original Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024142/ https://www.ncbi.nlm.nih.gov/pubmed/29988441 http://dx.doi.org/10.1002/ece3.4134

Ejemplares similares

Subset selection in regression
por: Miller, Alan
Publicado: (2002)

Optimal subset selection: multiple regression, interdependence and optimal network algorithms
por: Boyce, David E, et al.
Publicado: (1974)

Functional and phylogenetic ecology in R
por: Swenson, Nathan G
Publicado: (2014)

Statistical notes for clinical researchers: simple linear regression 2 – evaluation of regression line
por: Kim, Hae-Young
Publicado: (2018)

Regression Models, Fantastic Beasts, and Where to Find Them: A Simple Tutorial for Ecologists Using R
por: Corlatti, Luca
Publicado: (2021)

A hierarchical study for urban statistical indicators on the prevalence of COVID-19 in Chinese city clusters based on multiple linear regression (MLR) and polynomial best subset regression (PBSR) analysis
por: Cheshmehzangi, Ali, et al.
Publicado: (2022)

Computational Ecology: From the Complex to the Simple and Back
por: Pascual, Mercedes
Publicado: (2005)

Semiparametric regression with R
por: Harezlak, Jaroslaw, et al.
Publicado: (2018)

Régression avec R
por: Cornillon, Pierre-André, et al.
Publicado: (2019)

Nonlinear Regression with R
por: Ritz, Christian, et al.
Publicado: (2009)

Régression avec R
por: Cornillon, Pierre-André, et al.
Publicado: (2011)

Usefulness of Hamilton rating scale for depression subset scales and full versions for electroconvulsive therapy
por: Fenton, Caoimhe, et al.
Publicado: (2021)

Non-Full House Membranous Lupus Nephritis Represents a Clinically Distinct Subset
por: Ye, Julia, et al.
Publicado: (2023)

Robust Multiple Regression
por: Scott, David W., et al.
Publicado: (2021)

%svy_logistic_regression: A generic SAS macro for simple and multiple logistic regression and creating quality publication-ready tables using survey or non-survey data
por: Muthusi, Jacques, et al.
Publicado: (2019)

Simple Bayesian testing of scientific expectations in linear regression models
por: Mulder, J., et al.
Publicado: (2019)

A Simple and Adaptive Dispersion Regression Model for Count Data
por: Klakattawi, Hadeel S., et al.
Publicado: (2018)

RRegrs: an R package for computer-aided model selection with multiple regression models
por: Tsiliki, Georgia, et al.
Publicado: (2015)

Ecologic regression analysis and the study of the influence of air quality on mortality.
por: Selvin, S, et al.
Publicado: (1984)

The Extraction of Simple Relationships in Growth Factor-Specific Multiple-Input and Multiple-Output Systems in Cell-Fate Decisions by Backward Elimination PLS Regression
por: Akimoto, Yuki, et al.
Publicado: (2013)

A Simple Method to Identify the Dominant Fouling Mechanisms during Membrane Filtration Based on Piecewise Multiple Linear Regression
por: Xu, Hao, et al.
Publicado: (2020)

Fear of Darkness, the Full Moon and the Nocturnal Ecology of African Lions
por: Packer, Craig, et al.
Publicado: (2011)

Beyond pathogenesis: Detecting the full spectrum of ecological interactions in the virosphere
por: Jurburg, Stephanie D., et al.
Publicado: (2023)

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits
por: Zhang, Futao, et al.
Publicado: (2016)

A Simple Regression-Based Method to Map Quantitative Trait Loci Underlying Function-Valued Phenotypes
por: Kwak, Il-Youp, et al.
Publicado: (2014)

Multiple imputation in Cox regression when there are time‐varying effects of covariates
por: Keogh, Ruth H., et al.
Publicado: (2018)

A simple method for estimating relative risk using logistic regression
por: Diaz-Quijano, Fredi A
Publicado: (2012)

Sample Size Calculations in Simple Linear Regression: A New Approach
por: Guan, Tianyuan, et al.
Publicado: (2023)

CARRoT: R-package for predictive modelling by means of regression, adjusted for multiple regularisation methods
por: Bazarova, Alina, et al.
Publicado: (2023)

GATA3 Regulates the Development and Functions of Innate Lymphoid Cell Subsets at Multiple Stages
por: Zhu, Jinfang
Publicado: (2017)

Counting using deep learning regression gives value to ecological surveys
por: Hoekendijk, Jeroen P. A., et al.
Publicado: (2021)

Numerical ecology with R
por: Borcard, Daniel, et al.
Publicado: (2018)

Numerical Ecology with R
por: Borcard, Daniel, et al.
Publicado: (2011)

A genetic algorithm to find optimal reading test word subsets for estimating full-scale IQ
por: van der Linde, Ian, et al.
Publicado: (2018)

Multiple imputation of multiple multi-item scales when a full imputation model is infeasible
por: Plumpton, Catrin O., et al.
Publicado: (2016)

Statistical notes for clinical researchers: simple linear regression 1 – basic concepts
por: Kim, Hae-Young
Publicado: (2018)

Statistical notes for clinical researchers: simple linear regression 3 – residual analysis
por: Kim, Hae-Young
Publicado: (2019)

Multiple regression in behavioral research : explanation and prediction /
por: Pedhazur, Elazar J.
Publicado: (1982)

Comparison of subset selection methods in linear regression in the context of health-related quality of life and substance abuse in Russia
por: Morozova, Olga, et al.
Publicado: (2015)

OSCAR: Optimal subset cardinality regression using the L0-pseudonorm with applications to prognostic modelling of prostate cancer
por: Halkola, Anni S., et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_k78t3kkdvd0kt43q114p7fg86m