Statistical inference for engineers and data scientists

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"Statistical Inference for Engineers and Data Scientists A mathematically accessible and up-to-date introduction to the tools needed to address modern inference problems in engineering and data science, ideal for graduate students taking courses on statistical inference and detection and estimation, and an invaluable reference for researchers and professionals"--

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Title Statements

Full title :Statistical inference for engineers and data scientists / Pierre Moulin, Venugopal V. Veeravalli.

Summary

Edition Statements

Publication Date:cop.2019.

Publication Statements

Publisher(s):Cambridge University Press
Place of Publication:Cambridge
Language:eng
Publication Date:cop.2019.

Notes

Incluye referencias bibliográficas e indice.

The Physical Object

Description:xxi, 399 p. : 26 cm.

Edition Identifiers

ISBN:9781107185920, 1107185920
oclc:on1224155238
LC Classification:QA276

Introduction -- Binary hypothesis testing -- Multiple hypothesis testing -- Composite hypothesis testing -- Signal detection -- Convex statistical distances -- Performance bounds for hypothesis testing -- Large deviations and error exponents for hypothesis testing -- Sequential and quickest change detection -- Detection of random processes -- Bayesian parameter estimation -- Minimum variance unbiased estimation -- Information Inequality and Cramér-Rao lower bounds -- Maximum likelihood estimation -- Signal estimation.