<p>This book grew out of lectures delivered at the University of California, Berkeley, over many years. The subject is a part of asymptotics in statistics, organized around a few central ideas. The presentation proceeds from the general to the particular since this seemed the best way to emphasize t
From Finite Sample to Asymptotic Methods in Statistics
β Scribed by Pranab K. Sen, Julio M. Singer, Antonio C. Pedroso de Lima
- Publisher
- Cambridge University Press
- Year
- 2009
- Tongue
- English
- Leaves
- 400
- Series
- Cambridge Series in Statistical and Probabilistic Mathematics
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Exact statistical inference may be employed in diverse fields of science and technology. As problems become more complex and sample sizes become larger, mathematical and computational difficulties can arise that require the use of approximate statistical methods. Such methods are justified by asymptotic arguments but are still based on the concepts and principles that underlie exact statistical inference. With this in perspective, this book presents a broad view of exact statistical inference and the development of asymptotic statistical inference, providing a justification for the use of asymptotic methods for large samples. Methodological results are developed on a concrete and yet rigorous mathematical level and are applied to a variety of problems that include categorical data, regression, and survival analyses. This book is designed as a textbook for advanced undergraduate or beginning graduate students in statistics, biostatistics, or applied statistics but may also be used as a reference for academic researchers.
π SIMILAR VOLUMES
Experiments--decision spaces -- Some results form decision theory: deficiencies -- Likelihood ratios and conical measures -- Some basic inequalities -- Sufficiency and insufficiency -- Domination, compactness, contiguity -- Some limit theorems -- Invariance properties -- Infinitely divisible, Gaussi
<p>Traditions of the 150-year-old St. Petersburg School of Probability and StatisΒ tics had been developed by many prominent scientists including P. L. ChebyΒ chev, A. M. Lyapunov, A. A. Markov, S. N. Bernstein, and Yu. V. Linnik. In 1948, the Chair of Probability and Statistics was established at t
<p><b>A much-needed reference on survey sampling and its applications that presents the latest advances in the field</b></p> <p>Seeking to show that sampling theory is a living discipline with a very broad scope, this book examines the modern development of the theory of survey sampling and the foun
<B>Contents:</B> Decision Theoretic Foundations in Survey Sampling.- Minimax Solutions in Permutation Invariant Parameter Spaces.- The Cuboid as Parameter Space.- The HH-Space as Parameter Space.- The Generalized HH-Space as Parameter Space.- Bibliog- raphy.- List of Notation.- Subject Index.
The asymptotic properties of the likelihood ratio play an important part in solving problems in statistics for various schemes of observations. In this book, the author describes the asymptotic methods for parameter estimation and hypothesis testing based on asymptotic properties of the likelihood r