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. The book is based on lecture notes prepared by the
first author, subsequently edited, expanded and updated by the
second author. 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 of 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.
General
Imprint: |
Productivity Press
|
Country of origin: |
United States |
Series: |
Chapman & Hall/CRC Texts in Statistical Science |
Release date: |
December 2023 |
Firstpublished: |
2023 |
Authors: |
W. Jackson Hall
• David Oakes
|
Dimensions: |
234 x 156mm (L x W) |
Format: |
Hardcover
|
Pages: |
280 |
ISBN-13: |
978-1-4987-2606-1 |
Categories: |
Books
|
LSN: |
1-4987-2606-2 |
Barcode: |
9781498726061 |
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