scispace - formally typeset
Open AccessBook

Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach

Reads0
Chats0
TLDR
The second edition of this book is unique in that it focuses on methods for making formal statistical inference from all the models in an a priori set (Multi-Model Inference).
Abstract
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

read more

Citations
More filters
Journal ArticleDOI

Bayes in the sky: Bayesian inference and model selection in cosmology

TL;DR: This review is an introduction to Bayesian methods in cosmology and astrophysics and recent results in the field, and presents Bayesian probability theory and its conceptual underpinnings, Bayes' Theorem and the role of priors.
Journal ArticleDOI

Decline of the North American avifauna

TL;DR: Using multiple and independent monitoring networks, population losses across much of the North American avifauna over 48 years are reported, including once-common species and from most biomes, demonstrating a continuing avifaunal crisis.
Journal ArticleDOI

Plant Species Richness and Ecosystem Multifunctionality in Global Drylands

Fernando T. Maestre, +53 more
- 13 Jan 2012 - 
TL;DR: A global empirical study relating plant species richness and abiotic factors to multifunctionality in drylands, which collectively cover 41% of Earth’s land surface and support over 38% of the human population, suggests that the preservation of plant biodiversity is crucial to buffer negative effects of climate change and desertification in dryland.
Journal ArticleDOI

Model Selection in Historical Biogeography Reveals that Founder-Event Speciation Is a Crucial Process in Island Clades

TL;DR: The re-implementing of the Dispersal-Extinction-Cladogenesis model of LAGRANGE is modified to create a new model, DEC + J, which adds founder-event speciation, the importance of which is governed by a new free parameter, and the results indicate that the assumptions of historical biogeography models can have large impacts on inference and require testing and comparison with statistical methods.
Journal ArticleDOI

How to fail at species delimitation.

TL;DR: Researchers should apply a wide range of species delimitation analyses to their data and place their trust in delimitations that are congruent across methods, for in most contexts it is better to fail to delimit species than it is to falsely delimit entities that do not represent actual evolutionary lineages.