Statistical Inference in Stochastic Processes
1st Edition
Published on 13. August 2020
288 pages
978-1-000-10453-0 (ISBN)
Description
Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and statistical techniques in image analysis and processing, develops likelihood methods for inference about parameters that determine the drift and the jump mechanism of a di
More details
Series
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
File size
11,78 MB
ISBN-13
978-1-000-10453-0 (9781000104530)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
N.U. Prabhu
Statistical Inference in Stochastic Processes
Book
10/2019
1st Edition
CRC Press
€101.10
Shipment within 15-20 days
Book
12/1990
1st Edition
CRC Press
€166.20
Shipment within 15-20 days
Person
N. U. Prabhu, I. V. Basawa
Content
Preface -- 1 Statistical Models and Methods in Image Analysis: A Survey /Alan F. Karr -- 2 Edge-Preserving Smoothing and the Assessment of Point Process Models for GATE Rainfall Fields /Colin R. Goodall and Michael J. Phelan -- 3 Likelihood Methods for Diffusions with Jumps /Michael SVJrensen -- 4 Efficient Estimating Equations for Nonparametric Filtered Models /P. E. Greenwood and W. Wefelmeyer -- 5 Nonparametric Estimation of Trends in Linear Stochastic Systems /Jan W. McKeague and Tiziano Tofani -- 6 Weak Convergence of Two-Sided Stochastic Integrals, with an Application to Models for Left Truncated Survival Data /Michael Davidsen and Martin Jacobsen -- 7 Asymptotic Theory of Weighted Maximum Likelihood Estimation for Growth Models /B. L. S. Prakasa Rao -- 8 Markov Chain Models for Type-Token Relationships /D. J. Daley, J. M. Gani, and D. A. Ratkowsky -- 9 A State-Space Approach to Transfer-Function Modeling /P. J. Brockwell, R. A. Davis, and H. Salehi -- 10 Shrinkage Estimation for a Dynamic Input-Output Linear Model /Young-Won Kim, David M. Nickerson, and I. V. Basawa -- 11 Maximum Probability Estimation for an Autoregressive Process /Lionel Weiss -- Index.
