Skip to content

Booksellers & Trade Customers: Sign up for online bulk buying at trade.atlanticbooks.com for wholesale discounts

Booksellers: Create Account on our B2B Portal for wholesale discounts

Non-Standard Parametric Statistical Inference

by Russell Cheng
Save 17% Save 17%
Current price ₹19,020.00
Original price ₹22,824.00
Original price ₹22,824.00
Original price ₹22,824.00
(-17%)
₹19,020.00
Current price ₹19,020.00

Imported Edition - Ships in 18-21 Days

Free Shipping in India on orders above Rs. 500

Request Bulk Quantity Quote
+91
Book cover type: Hardcover
  • ISBN13: 9780198505044
  • Binding: Hardcover
  • Subject: N/A
  • Publisher: Oxford University Press (UK)
  • Publisher Imprint: Oxford University Press (UK)
  • Publication Date:
  • Pages: 430
  • Original Price: USD 175.0
  • Language: English
  • Edition: N/A
  • Item Weight: 862 grams
  • BISAC Subject(s): Probability & Statistics / General

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 analyzing such problems. A frequentist likelihood-based viewpoint 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, with only sufficient mathematical detail 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, as is typically covered in a university statistical inference course, wishing to understand or study how standard methodology might fail. Easy to understand statistical methods are presented which overcome these difficulties, and demonstrated by detailed examples drawn from real applications. Simple and practical model-building is an underlying theme. Parametric bootstrap resampling is used throughout for analyzing 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 an accessible demonstration of the sampling behaviour of estimators.

Russell C.H Cheng, University of Southampton

Russell Cheng is Emeritus Professor of Operational Research at the University of Southampton. He has an M.A. and a Diploma in Mathematical Statistics from Cambridge University, and obtained his Ph.D. from Bath University. He is a former Chairman of the U.K. Simulation Society, a former Fellow of the Royal Statistical Society, and Fellow of the Institute of Mathematics and Its Applications. His research interests include: design and analysis of simulation experiments and parametric estimation methods. He founded and was Joint Editor of the IMA Journal of Management Mathematics.

Trusted for over 49 years

Family Owned Company

Secure Payment

All Major Credit Cards/Debit Cards/UPI & More Accepted

New & Authentic Products

India's Largest Distributor

Need Support?

Whatsapp Us