Overview
- The book deals with classical as well as most recent developments in the area of inference in discrete time stationary stochastic processes
- Topics discussed include Markov chains, non-Gaussian sequences, estimating function, density estimation and bootstrap for stationary observations and some of the results are available in a book form, most likely, for the first time
- The material is useful to research students and researchers working in the related areas
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
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Table of contents(6 chapters)
About this book
Authors and Affiliations
-
, Department of Statistics, University of Pune, Pune, India
M. B. Rajarshi
About the author
Bibliographic Information
Book Title: Statistical Inference for Discrete Time Stochastic Processes
Authors: M. B. Rajarshi
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-81-322-0763-4
Publisher: Springer New Delhi
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2013
Softcover ISBN: 978-81-322-0762-7Published: 05 October 2012
eBook ISBN: 978-81-322-0763-4Published: 08 July 2014
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: XI, 113