In all likelihood : statistical modelling and inference using likelihood / Yudi Pawitan.

By:

Pawitan, Yudi [Author]

Material type: Text

text

Media type:

computer

Carrier type:

online resource

ISBN:

9780191650574

Subject(s):

Mathematical statistics

Genre/Form:

Electronic Books.

LOC classification:

QA276 .I535 2013

Online resources:

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Available additional physical forms:

Subject: Based on a course in the theory of statistics this text concentrates on what can be achieved using the likelihood/Fisherian method of taking account of uncertainty when studying a statistical problem. It takes the concept of the likelihood as providing the best methods for unifying the demands of statistical modelling and the theory of inference. Every likelihood concept is illustrated by realistic examples, which are not compromised by computational problems. Examples range from a simile comparison of two accident rates, to complex studies that require generalised linear or semi parametric modelling. The emphasis is that the likelihood is not simply a device to produce an estimate, but an important tool for modelling. The book generally takes an informal approach, where most important results are established using heuristic arguments and motivated with realistic examples. With the currently available computing power, examples are not contrived to allow a closed analytical solution, and the book can concentrate on the statistical aspects of the data modelling.

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Item type	Current library	Collection	Call number	URL	Status	Date due	Barcode
Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD)	G. Allen Fleece Library ONLINE	Non-fiction	QA276 (Browse shelf(Opens below))	Link to resource	Available		ocn859537368

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Originally published: Oxford : Clarendon Press, 2001.

Previously published in 2008 as corrected edition.

Includes bibliographies and index.

Based on a course in the theory of statistics this text concentrates on what can be achieved using the likelihood/Fisherian method of taking account of uncertainty when studying a statistical problem. It takes the concept of the likelihood as providing the best methods for unifying the demands of statistical modelling and the theory of inference. Every likelihood concept is illustrated by realistic examples, which are not compromised by computational problems. Examples range from a simile comparison of two accident rates, to complex studies that require generalised linear or semi parametric modelling. The emphasis is that the likelihood is not simply a device to produce an estimate, but an important tool for modelling. The book generally takes an informal approach, where most important results are established using heuristic arguments and motivated with realistic examples. With the currently available computing power, examples are not contrived to allow a closed analytical solution, and the book can concentrate on the statistical aspects of the data modelling.

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