Model selection and multimodel inference : a practical information-theoretic approach
著者
書誌事項
Model selection and multimodel inference : a practical information-theoretic approach
Springer, c2002
2nd ed
- : [hardcover]
- : softcover
- タイトル別名
-
Model selection and inference : a practical information-theoretic approach
大学図書館所蔵 件 / 全48件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references (p. [455]-484) and index
Rev. ed. of: Model selection and inference. c1988. <BA39047527>
Softcover reprint of the hardcover 2nd edition 2002
内容説明・目次
内容説明
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.
目次
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
「Nielsen BookData」 より