David R. Anderson

Kenneth P. Burnham

A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

A Practical Information-Theoretic Approach

Model Selection and Multimodel Inference

Henry L. Short

This paper describes a technique for ordering wildlife information according to physical strata and vegetative structure so that a variety of statistical analyses can be accomplished. Individual wildlife species are assigned to cells in a species-habitat matrix on the basis of feeding and breeding activities within physical strata in representative types of vegetative cover: the cells within the species-habitat matrix are assigned numeric values. The statistical analyses are thus based on the areas that individual species occupy within the species-habitat matrix. Computer graphics are used to represent the structure of wildlife communities and cluster analysis routines are used to describe the potential wildlife guilds that may exist in different vegetative communities. Different numbers of wildlife guilds will occur in species and presumably also of wildlife guilds present within a type of cover is modified by physical attributes of the vegetation within that cover type. The products of this analytical technique may be suitable for evaluating habitat quality, impact assessments, regional inventories and assessments of wildlife resources, and land-use planning activities.

Kenneth P. Burnham

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