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Model Selection and Multi-Model Inference
Burnham, Kenneth P.; Anderson, David R.
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Description for Model Selection and Multi-Model Inference
Paperback. Num Pages: 488 pages, 51 black & white tables, biography. BIC Classification: PBWH; PDE; TBJ. Category: (P) Professional & Vocational. Dimension: 232 x 157 x 27. Weight in Grams: 742.
We wrote this book to introduce graduate students and research workers in various scienti?c disciplines to the use of information-theoretic approaches in the analysis of empirical data. These methods allow the data-based selection of a “best” model and a ranking and weighting of the remaining models in a pre-de?ned set. Traditional statistical inference can then be based on this selected best model. However, we now emphasize that information-theoretic approaches allow formal inference to be based on more than one model (m- timodel inference). Such procedures lead to more robust inferences in many cases, and we advocate these approaches throughout the ... Read more
We wrote this book to introduce graduate students and research workers in various scienti?c disciplines to the use of information-theoretic approaches in the analysis of empirical data. These methods allow the data-based selection of a “best” model and a ranking and weighting of the remaining models in a pre-de?ned set. Traditional statistical inference can then be based on this selected best model. However, we now emphasize that information-theoretic approaches allow formal inference to be based on more than one model (m- timodel inference). Such procedures lead to more robust inferences in many cases, and we advocate these approaches throughout the ... Read more
Product Details
Format
Paperback
Publication date
2010
Publisher
Springer-Verlag New York Inc. United States
Number of pages
488
Condition
New
Number of Pages
488
Place of Publication
New York, NY, United States
ISBN
9781441929730
SKU
V9781441929730
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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