Asymptotic theory of statistical inference
Our rough guess is there are 109,500 words in this book.
At a pace averaging 250 words per minute, this book will take 7 hours and 18 minutes to read. With a half hour per day, this will take 15 days to read.
How long will it take you?
This book will take an estimated to read at a reading speed averaging words per minute. With 30 minutes per day, this will take to read.
Enter your reading speedYou can take one of our WPM reading speed tests to find your reading speed.
Create a free account to track your reading progress, build your reading list, and set reading goals.
We earn a commission on purchases
Word Count
109,500 words, Guess
Page Count
438 pages
Identifiers
- Open LibraryOL2722206M
- ISBN-100471843350
- OCLC Control Number13822533
- Library of Congress Control Number86015735
- LibraryThing1450099
and 1 more
- Goodreads2019868
Classifications
- DDC519.5/4
- LCCQA276 .P67 1987
Description
An up-to-date and concise description of recent results in probability theory and stochastic processes useful in the study of asymptotic theory of statistical inference. Brings together new material on the interplay between recent advances in probability theory and their applications to the asymptotic theory of statistical inference. Asymptotic theory of maximum likelihood and Bayes estimation, asymptotic properties of least squares estimators in nonlinear regression, and estimators of parameters for stable laws are dicussed from the point of view of stochastic processes. This leads to better results than the Taylor expansions approach used in the classical theory of maximum likelihood estimation.
Subjects
Series Statement
- Wiley series in probability and mathematical statistics.
Reader Reviews
No reviews yet for this book.
Be the first to share your thoughts!