LIBERO WebOPAC Catalogue Display (W561)

Catalogue Information
Field name	Details
Dewey Class	519
Title	Non-standard parametric statistical inference / Russell Cheng ([Ebook])
Author	Cheng, Russell
Other name(s)	Oxford Scholarship Online
Publication	Oxford : Oxford University Press , 2017
Physical Details	1 online resource (xii, 417 pages : illustrations)
ISBN	9780191746390
Note	Print publication date: 2017. - Print ISBN-13: 9780198505044. - Published to Oxford Scholarship Online: September 2017
Summary Note	This book discusses the fitting of parametric statistical models to data samples. Emphasis is placed on (i) how to recognize situations where the problem is non-standard, when parameter estimates behave unusually, and (ii) the use of parametric bootstrap resampling methods in analysing such problems. Simple and practical model building is an underlying theme. A frequentist viewpoint based on likelihood is adopted, for which there is a well-established and very practical theory. The standard situation is where certain widely applicable regularity conditions hold. However, there are many apparently innocuous situations where standard theory breaks down, sometimes spectacularly. Most of the departures from regularity are described geometrically in the book, with mathematical detail only sufficient to clarify the non-standard nature of a problem and to allow formulation of practical solutions. The book is intended for anyone with a basic knowledge of statistical methods typically covered in a university statistical inference course who wishes to understand or study how standard methodology might fail. Simple, easy-to-understand statistical methods are presented which overcome these difficulties, and illustrated by detailed examples drawn from real applications. Parametric bootstrap resampling is used throughout for analysing the properties of fitted models, illustrating its ease of implementation even in non-standard situations. Distributional properties are obtained numerically for estimators or statistics not previously considered in the literature because their theoretical distributional properties are too hard to obtain theoretically. Bootstrap results are presented mainly graphically in the book, providing easy-to-understand demonstration of the sampling behaviour of estimators.:
Mode of acces to digital resource	Digital reproduction. Oxford : Oxford University Press, 2017. - Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in HTML format.
System details note	Online access to this digital book is restricted to subscribing institutions through IP address (only for SISSA internal users)
Internet Site	http://dx.doi.org/10.1093/oso/9780198505044.001.0001
Links to Related Works	Subject References: Estimation theory . Mathematical modelling . Probability & statistics . Statistics . Authors: Cheng, Russell . Corporate Authors: Oxford Scholarship Online . Classification: 519 . 519 (DDC 23) .

Catalogue Display

Non-standard parametric statistical inference

Reviews