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
Authors | Song, Guofeng, Dong, Xiaogang, Wu, Jiafeng and Wang, You-Gan |
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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. |
Keywords | model selection; AIC; AICc; quasi-likelihood; environmental applications |
Year | 2017 |
Journal | Environmental Modeling and Assessment |
Journal citation | 22 (6), pp. 523-533 |
Publisher | Springer |
ISSN | 1420-2026 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/s10666-017-9552-8 |
Scopus EID | 2-s2.0-85014642980 |
Page range | 523-533 |
Funder | Australian 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 status | Published |
Publication dates | |
Online | 09 Mar 2017 |
Publication process dates | |
Accepted | 23 Feb 2017 |
Deposited | 08 Dec 2022 |
ARC Funded Research | This output has been funded, wholly or partially, under the Australian Research Council Act 2001 |
Grant ID | DP130100766 |
DP160104292 | |
11571051 |
https://acuresearchbank.acu.edu.au/item/8y8q5/blockwise-aicc-for-model-selection-in-generalized-linear-models
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