Mathematical statistics and statistics of processes. (Q2898496)

This is an introductory textbook covering the areas of statistical inference and inference for stochastic processes. The author discusses the concepts of decision theory, conditional expectations, sufficient statistics, point estimation, tests of hypotheses, confidence regions, asymptotic properties of maximum likelihood estimators and nonparametric methods in the first eight chapters of the book under the title ``Mathematical statistics''.NEWLINENEWLINE The second part of the book deals with ``Statistics for processes''. The class of processes studied include weakly stationary processeses in discrete time, Poisson processes, second order (square integrable) processes in continuous time, diffusion processes and ARMA processes. Prediction theory for ARIMA models and for processes in continuous time are investigated in the second part of the book. The third part of the book contains a brief survey of elements of the theory of probability.NEWLINENEWLINE The book is well written and it is an interesting note that the author was able to cover a vast amount of material in a book of size 288 pages in great detail. Each chapter has many examples and ends with exercises useful for the reader to get a better understanding of the material discussed in that chapter. I recommend this book for any serious student learning basic ideas of statistical inference and inference for stochastic processes.