Ebooks News

Statistical Inference for Discrete Time Stochastic Processes

16 View(s), published at 2014-07-08, written by M. B. Rajarshi, published by Springer Science & Business Media
Statistical Inference for Discrete Time Stochastic Processes

Statistical inference for discrete time stochastic processes by M. B. Rajarshi 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 n.... Published date on: 2014-07-08 with total page: 113 pages. Publisher of Statistical Inference for Discrete Time Stochastic Processes is Springer Science & Business Media.

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 martingales and strong mixing sequences, which enable us to generate various classes of CAN estimators in the case of dependent observations. Topics discussed include inference in Markov chains and extension of Markov chains such as Raftery's Mixture Transition Density model and Hidden Markov chains and extensions of ARMA models with a Binomial, Poisson, Geometric, Exponential, Gamma, Weibull, Lognormal, Inverse Gaussian and Cauchy as stationary distributions. It further discusses applications of semi-parametric methods of estimation such as conditional least squares and estimating functions in stochastic models. Construction of confidence intervals based on estimating functions is discussed in some detail. Kernel based estimation of joint density and conditional expectation are also discussed. Bootstrap and other resampling procedures for dependent sequences such as Markov chains, Markov sequences, linear auto-regressive moving average sequences, block based bootstrap for stationary sequences and other block based procedures are also discussed in some detail. This work can be useful for researchers interested in knowing developments in inference in discrete time stochastic processes. It can be used as a material for advanced level research students.

Are you want to read online this ebook statistical inference for discrete time stochastic processes? If you have read an ebook before don't be hasitate to leave review about the book statistical inference for discrete time stochastic processes. But otherwise, you can registar/sign up before downloding this pdf book. We have huge database of ebooks in our library. If you bought an ebook than you want another ebook we suggest you to become our library member.

What do you get from becoming member in our library? 1.You can read free a lot of books from our database. 2.You can use any kind of ebook reader available on market, because our book available in various format. 3.You able to find your ebook fastly through our library because we put ebooks based on categories such as adventure, art, law, social, health, medical, science, romance, fiction, non-fiction and etc.

Tags: