Mathematical Statistics and Stochastic Processes

Nonfiction, Science & Nature, Mathematics, Applied
Cover of the book Mathematical Statistics and Stochastic Processes by Denis Bosq, Wiley
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Author: Denis Bosq ISBN: 9781118586273
Publisher: Wiley Publication: February 4, 2013
Imprint: Wiley-ISTE Language: English
Author: Denis Bosq
ISBN: 9781118586273
Publisher: Wiley
Publication: February 4, 2013
Imprint: Wiley-ISTE
Language: English

Generally, books on mathematical statistics are restricted to the case of independent identically distributed random variables. In this book however, both this case AND the case of dependent variables, i.e. statistics for discrete and continuous time processes, are studied. This second case is very important for today’s practitioners.
Mathematical Statistics and Stochastic Processes is based on decision theory and asymptotic statistics and contains up-to-date information on the relevant topics of theory of probability, estimation, confidence intervals, non-parametric statistics and robustness, second-order processes in discrete and continuous time and diffusion processes, statistics for discrete and continuous time processes, statistical prediction, and complements in probability.
This book is aimed at students studying courses on probability with an emphasis on measure theory and for all practitioners who apply and use statistics and probability on a daily basis.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Generally, books on mathematical statistics are restricted to the case of independent identically distributed random variables. In this book however, both this case AND the case of dependent variables, i.e. statistics for discrete and continuous time processes, are studied. This second case is very important for today’s practitioners.
Mathematical Statistics and Stochastic Processes is based on decision theory and asymptotic statistics and contains up-to-date information on the relevant topics of theory of probability, estimation, confidence intervals, non-parametric statistics and robustness, second-order processes in discrete and continuous time and diffusion processes, statistics for discrete and continuous time processes, statistical prediction, and complements in probability.
This book is aimed at students studying courses on probability with an emphasis on measure theory and for all practitioners who apply and use statistics and probability on a daily basis.

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