Blockwise AICc for model selection in generalized linear models

Journal article

Song, Guofeng, Dong, Xiaogang, Wu, Jiafeng and Wang, You-Gan. (2017). Blockwise AICc for model selection in generalized linear models. Environmental Modeling and Assessment. 22(6), pp. 523-533. https://doi.org/10.1007/s10666-017-9552-8
AuthorsSong, Guofeng, Dong, Xiaogang, Wu, Jiafeng and Wang, You-Gan
Abstract

The corrected Akaike information criterion (AICc) is a widely used tool in analyzing environmental and ecological data, and it outperforms the Akaike information criterion (AIC), especially in small-size samples. To take advantage of this property, we propose a modified version of the AICc in a generalized linear model framework, referred to as the blockwise AICc (bAICc). Compared with some other information criteria, extensive simulation results show that the bAICc performs well. We also analyzed two environmental datasets, one for snail survival and the other for fish infection, to illustrate the usefulness of this new model selection criterion.

Keywordsmodel selection; AIC; AICc; quasi-likelihood; environmental applications
Year2017
JournalEnvironmental Modeling and Assessment
Journal citation22 (6), pp. 523-533
PublisherSpringer
ISSN1420-2026
Digital Object Identifier (DOI)https://doi.org/10.1007/s10666-017-9552-8
Scopus EID2-s2.0-85014642980
Page range523-533
FunderAustralian Research Council (ARC)
China Scholarship Council
National Natural Science Foundation of China (NSFC)
Publisher's version
License
All rights reserved
File Access Level
Controlled
Output statusPublished
Publication dates
Online09 Mar 2017
Publication process dates
Accepted23 Feb 2017
Deposited08 Dec 2022
ARC Funded ResearchThis output has been funded, wholly or partially, under the Australian Research Council Act 2001
Grant IDDP130100766
DP160104292
11571051
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Jones, Andy, Lavery, Shane D., Le Port, Agnès, Wang, You-Gan, Blower, Dean and Ovenden, Jennifer. (2019). Sweepstakes reproductive success is absent in a New Zealand snapper (Chrysophrus auratus) population protected from fishing despite “tiny” Ne/N ratios elsewhere. Molecular Ecology. 28(12), pp. 2986-2995. https://doi.org/10.1111/mec.15130
A review of the Behrens–Fisher problem and some of its analogs : Does the same size fit all?
Paul, Sudhir, Wang, You-Gan and Ullah, Insha. (2019). A review of the Behrens–Fisher problem and some of its analogs : Does the same size fit all? Revstat Statistical Journal. 17(4), p. 563–597.
Incorporating social objectives in evaluating sustainable fisheries harvest strategy
Wu, Jiafeng, Wang, Na, Hu, Zhi-Hua, Hong, Zhenjie and Wang, You-Gan. (2019). Incorporating social objectives in evaluating sustainable fisheries harvest strategy. Environmental Modeling and Assessment. 24(4), pp. 381-386. https://doi.org/10.1007/s10666-019-9651-9
Significance tests for analyzing gene expression data with small sample sizes
Ullah, Insha, Paul, Sudhir, Hong, Zhenjie and Wang, You-Gan. (2019). Significance tests for analyzing gene expression data with small sample sizes. Bioinformatics. 35(20), pp. 3996-4003. https://doi.org/10.1093/bioinformatics/btz189
Robust Estimation Using Modified Huber’s Functions With New Tails
Jiang, Yunlu, Wang, You-Gan, Fu, Liya and Wang, Xueqin. (2019). Robust Estimation Using Modified Huber’s Functions With New Tails. Technometrics. 61(1), pp. 111-122. https://doi.org/10.1080/00401706.2018.1470037
Variable selection in rank regression for analyzing longitudinal data
Fu, Liya and Wang, You-Gan. (2018). Variable selection in rank regression for analyzing longitudinal data. Statistical Methods in Medical Research. 27(8), pp. 2447-2458. https://doi.org/10.1177/0962280216681347
Assessing temporal variations of Ammonia Nitrogen concentrations and loads in the Huaihe River Basin in relation to policies on pollution source control
Xu, Jing, Jin, Guangqiu, Tang, Hongwu, Zhang, Pei, Wang, Shen, Wang, You-Gan and Li, Ling. (2018). Assessing temporal variations of Ammonia Nitrogen concentrations and loads in the Huaihe River Basin in relation to policies on pollution source control. Science of the Total Environment. 642, pp. 1386-1395. https://doi.org/10.1016/j.scitotenv.2018.05.395
Genomic prediction of breeding values using a subset of SNPs identified by three machine learning methods
Li, Bo, Zhang, Nanxi, Wang, You-Gan, George, Andrew W., Reverter, Antonio and Li, Yutao. (2018). Genomic prediction of breeding values using a subset of SNPs identified by three machine learning methods. Frontiers in Genetics. 9, p. Article 237. https://doi.org/10.3389/fgene.2018.00237
Dividend growth and equity premium predictability
Zhu, Min, Chen, Rui, Du, Ke and Wang, You-Gan. (2018). Dividend growth and equity premium predictability. International Review of Economics and Finance. 56, pp. 125-137. https://doi.org/10.1016/j.iref.2017.10.020
Robust Regression with Data-Dependent Regularization Parameters and Autoregressive Temporal Correlations
Wang, Na, Wang, You-Gan, Hu, Shuwen, Hu, Zhi-Hua, Xu, Jing, Tang, Hongwu and Jin, Guangqiu. (2018). Robust Regression with Data-Dependent Regularization Parameters and Autoregressive Temporal Correlations. Environmental Modeling and Assessment. 23(6), pp. 779-786. https://doi.org/10.1007/s10666-018-9605-7
Analysis of spatial data with a nested correlation structure
Adegboye, Oyelola, Leung, Denis and Wang, You-Gan. (2018). Analysis of spatial data with a nested correlation structure. Journal of the Royal Statistical Society Series C: Applied Statistics. 67(2), pp. 329-354. https://doi.org/10.1111/rssc.12230
Working correlation structure selection in generalized estimating equations
Fu, Liya, Hao, Yangyang and Wang, You-Gan. (2018). Working correlation structure selection in generalized estimating equations. Computational Statistics. 33(2), pp. 983-996. https://doi.org/10.1007/s00180-018-0800-4
Selection of working correlation structure in generalized estimating equations
Wang, You-Gan and Fu, Liya. (2017). Selection of working correlation structure in generalized estimating equations. Statistics in Medicine. 36(14), pp. 2206-2219. https://doi.org/10.1002/sim.7262
A comment on Koh’s “The optimal design of fallible organizations : Invariance of optimal decision threshold and uniqueness of hierarchy and polyarchy structures”
Zhu, Min, Liu, Chang and Wang, You-Gan. (2017). A comment on Koh’s “The optimal design of fallible organizations : Invariance of optimal decision threshold and uniqueness of hierarchy and polyarchy structures”. Social Choice and Welfare. 48(2), pp. 385-392. https://doi.org/10.1007/s00355-016-1009-5
The Buckley–James estimator and induced smoothing
Wang, You-Gan, Zhao, Yudong and Fu, Liya. (2016). The Buckley–James estimator and induced smoothing. Australian and New Zealand Journal of Statistics. 58(2), pp. 211-225. https://doi.org/10.1111/anzs.12155
Maximum likelihood estimation of natural mortality and quantification of temperature effects on catchability of brown tiger prawn (penaeus esculentus) in Moreton Bay (Australia) using logbook data
Kienzle, Marco, Sterling, David, Zhou, Shijie and Wang, You-Gan. (2016). Maximum likelihood estimation of natural mortality and quantification of temperature effects on catchability of brown tiger prawn (penaeus esculentus) in Moreton Bay (Australia) using logbook data. Ecological Modelling. 322, pp. 1-9. https://doi.org/10.1016/j.ecolmodel.2015.11.008
Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia : Species differentiation and prediction for fisheries monitoring and assessment
Zischke, Mitchell T., Litherland, Lenore, Tilyard, Benjamin R., Stratford, Nicholas J., Jones, Ebony L. and Wang, You-Gan. (2016). Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia : Species differentiation and prediction for fisheries monitoring and assessment. Fisheries Research. 176, pp. 39-47. https://doi.org/10.1016/j.fishres.2015.12.003
Efficient parameter estimation via Gaussian copulas for quantile regression with longitudinal data
Fu, Liya and Wang, You-Gan. (2016). Efficient parameter estimation via Gaussian copulas for quantile regression with longitudinal data. Journal of Multivariate Analysis. 143, pp. 492-502. https://doi.org/10.1016/j.jmva.2015.07.004
Mixture of time-dependent growth models with an application to blue swimmer crab length-frequency data
Lloyd-Jones, Luke R., Nguyen, Hien D., McLachlan, Geoffrey J., Sumpton, Wayne and Wang, You-Gan. (2016). Mixture of time-dependent growth models with an application to blue swimmer crab length-frequency data. Biometrics. 72(4), pp. 1255-1265. https://doi.org/10.1111/biom.12531
Movement and growth of the coral reef holothuroids Bohadschia argus and Thelenota ananas
Purcell, Steven W., Piddocke, Toby P., Dalton, Steven J. and Wang, You-Gan. (2016). Movement and growth of the coral reef holothuroids Bohadschia argus and Thelenota ananas. Marine Ecology Progress Series. 551, pp. 201-214. https://doi.org/10.3354/meps11720
Improved confidence intervals for the linkage disequilibrium method for estimating effective population size
Jones, A. T., Ovenden, J. R. and Wang, Y.-G.. (2016). Improved confidence intervals for the linkage disequilibrium method for estimating effective population size. Heredity. 117(4), pp. 217-223. https://doi.org/10.1038/hdy.2016.19