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Model selection and multimodel inference: a practical information-theoretic approach.
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Introduction * Information and Likelihood Theory: A Basis for Model Selection and Inference * Basic Use of the Information-Theoretic Approach * Formal Inference From More Than One Model: Multi-Model Inference (MMI) * Monte Carlo Insights and Extended Examples * Statistical Theory and Numerical Results * Summary
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“Ranking these models using the sample-size-corrected Akaike Information Criterion (AICc) [29] revealed that the number of geckos on a tree was principally a function of the tree's size (estimated surface area of the main stem) and its proximity to the nearest termite mound (Table S1).”
From Spatial Pattern Enhances Ecosystem Functioning in an African Savanna (2010) · cites this paper as [29]
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Metadata
- Authors
- Guthery, F. S., Burnham, K. P., & Anderson, D. R.
- Venue
- The Journal of Wildlife Management
- Publisher
- JSTOR
- Published
- 2003-07
- Volume
- 67
- Issue
- 3
- Pages
- 655
- ISSN
- 0022-541X (ISSN-L)
- OpenAlex
- W2009435671
- Cited by
- 41,495
- References
- 0
- Citations by year
- 2026: 22 · 2025: 843 · 2024: 1223 · 2023: 1355 · 2022: 1673 · 2021: 2532 · 2020: 2605 · 2019: 2743 · 2018: 2552 · 2017: 2708 · 2016: 2821 · 2015: 2984 · 2014: 2929 · 2013: 2592 · 2012: 2272
- FWCI
- 648.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Journal of Wildlife Management (publishedVersion, cc-by)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- model selection, multi-model inference, information theory, likelihood theory, Akaike information criterion, AICc, model averaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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