Course Large Sample Theory by Hall Jackson (23 results)

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Hardback. Condition: New. This book provides an accessible but rigorous introduction to asymptotic theory in parametric statistical models. Asymptotic results for estimation and testing are derived using the "moving alternative" formulation due to R. A. Fisher and L. Le Cam. Later chapters include discussions of linear rank statistics and of chi-squared tests for contingency table analysis, including situations where parameters are estimated from the complete ungrouped data. This book is based on lecture notes prepared by the first author, subsequently edited, expanded and updated by the second author.Key features:Succinct account of the concept of "asymptotic linearity" and its usesSimplified derivations of the major results, under an assumption of joint asymptotic normalityInclusion of numerical illustrations, practical examples and adviceHighlighting some unexpected consequences of the theoryLarge number of exercises, many with hints to solutionsSome facility with linear algebra and with real analysis including 'epsilon-delta' arguments is required. Concepts and results from measure theory are explained when used. Familiarity with undergraduate probability and statistics including basic concepts of estimation and hypothesis testing is necessary, and experience with applying these concepts to data analysis would be very helpful.…

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Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Hardcover. Condition: Brand New. 400 pages. 9.25x6.14x0.94 inches. In Stock.

Hardback. Condition: New. This book provides an accessible but rigorous introduction to asymptotic theory in parametric statistical models. Asymptotic results for estimation and testing are derived using the "moving alternative" formulation due to R. A. Fisher and L. Le Cam. Later chapters include discussions of linear rank statistics and of chi-squared tests for contingency table analysis, including situations where parameters are estimated from the complete ungrouped data. This book is based on lecture notes prepared by the first author, subsequently edited, expanded and updated by the second author.Key features:Succinct account of the concept of "asymptotic linearity" and its usesSimplified derivations of the major results, under an assumption of joint asymptotic normalityInclusion of numerical illustrations, practical examples and adviceHighlighting some unexpected consequences of the theoryLarge number of exercises, many with hints to solutionsSome facility with linear algebra and with real analysis including 'epsilon-delta' arguments is required. Concepts and results from measure theory are explained when used. Familiarity with undergraduate probability and statistics including basic concepts of estimation and hypothesis testing is necessary, and experience with applying these concepts to data analysis would be very helpful.…

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides an accessible but rigorous introduction to asymptotic theory in parametric statistical models. Asymptotic results for estimation and testing are derived using the 'moving alternative' formulation due to R. A. Fisher and L. Le Cam. Later chapters include discussions of linear rank statistics and of chi-squared tests for contingency table analysis, including situations where parameters are estimated from the complete ungrouped data. This book is based on lecture notes prepared by the first author, subsequently edited, expanded and updated by the second author.Key features: Succinct account of the concept of 'asymptotic linearity' and its uses Simplified derivations of the major results, under an assumption of joint asymptotic normality Inclusion of numerical illustrations, practical examples and advice Highlighting some unexpected consequences of the theory Large number of exercises, many with hints to solutions Some facility with linear algebra and with real analysis including 'epsilon-delta' arguments is required. Concepts and results from measure theory are explained when used. Familiarity with undergraduate probability and statistics including basic concepts of estimation and hypothesis testing is necessary, and experience with applying these concepts to data analysis would be very helpful. 322 pp. Englisch. …

HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides an accessible but rigorous introduction to asymptotic theory in parametric statistical models. Asymptotic results for estimation and testing are derived using the 'moving alternative' formulation due to R. A. Fisher and L. Le Cam. Later chapters include discussions of linear rank statistics and of chi-squared tests for contingency table analysis, including situations where parameters are estimated from the complete ungrouped data. This book is based on lecture notes prepared by the first author, subsequently edited, expanded and updated by the second author.Key features: Succinct account of the concept of 'asymptotic linearity' and its uses Simplified derivations of the major results, under an assumption of joint asymptotic normality Inclusion of numerical illustrations, practical examples and advice Highlighting some unexpected consequences of the theory Large number of exercises, many with hints to solutions Some facility with linear algebra and with real analysis including 'epsilon-delta' arguments is required. Concepts and results from measure theory are explained when used. Familiarity with undergraduate probability and statistics including basic concepts of estimation and hypothesis testing is necessary, and experience with applying these concepts to data analysis would be very helpful.…