£118.89

Springer Asymptotic Theory of Statistical Inference for Time Series

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Price range: £119 - £132

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Description

Asymptotic Theory of Statistical Inference for Time Series is an essential academic resource for those studying the statistical analysis of dependent observations. Published as part of the Springer Series in Statistics, this book addresses the growing demand for advanced techniques in fields such as economics, engineering, and the natural sciences. The text focuses on providing modern statistical techniques and theory for stochastic processes. Unlike many standard texts, this work is not limited to common autoregressive (AR), moving average (MA), or autoregressive moving average (ARMA) processes. Instead, it explores a wide variety of stochastic processes to give researchers and students a more comprehensive understanding of probability structures in dependent data series. This book serves as a deep dive into the mathematical foundations required to model and analyze complex time series data. Whether you are working in applied mathematics or specialized scientific research, this volume offers the theoretical depth needed to master the study of stochastic processes and their statistical inferences.

Key Features

Covers modern statistical techniques and theory specifically designed for the study of stochastic processes.

Extends beyond standard AR, MA, and ARMA models to include a wide variety of stochastic processes.

Provides necessary mathematical frameworks for analyzing dependent observations in various scientific fields.

Designed for applications in economics, engineering, and the natural sciences.

Part of the respected Springer Series in Statistics for academic and professional research.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
11 August 2000
Listed Since
16 December 2006

Barcode

No barcode data available

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