Statistical Inference for Discrete Time Stochastic Processes

• Main Author: Rajarshi, M. B. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: India : Springer India : Imprint: Springer, 2013.
• Series: SpringerBriefs in Statistics,
• Subjects: Statistics.; Mathematical statistics.; Statistical Theory and Methods.; Statistics, general.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-81-322-0763-4

This work is an overview of statistical inference in stationary, discrete time stochastic processes.� Results in the last fifteen years, particularly on non-Gaussian sequences and semi-parametric and non-parametric analysis have been reviewed. The first chapter gives a background of results on marti...

Table of Contents:

• CAN Estimators from dependent observations
• Markov chains and their extensions
• Non-Gaussian ARMA models
• Estimating Functions
• Estimation of joint densities and conditional expectation
• Bootstrap and other resampling procedures
• Index.