Missing (Classic Reprint)

Language: English

Published by Forgotten Books, 2018

0365808954 / 9780365808954

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Seller: Forgotten Books, London, United KingdomForgotten Books

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Print on Demand. This book focuses on how to calculate maximum likelihood estimates of the parameters of a multivariate linear model with correlated errors when some of the dependent variates are not measured on some of the experimental units. The author presents a computer program that obtains these estimates and can also be used to solve several well-known statistical models, including the multivariate linear regression model. Providing definitions and notations used in incomplete multivariate models, the author delves into the subject of maximum likelihood estimates and how they are calculated. Practical examples demonstrate the program, and the author addresses sample problems, issues, warnings, and error messages that may occur. With its clear explanations and illustrative examples, this book is a valuable resource for researchers and practitioners in statistics, econometrics, and related fields, as well as students studying these disciplines. By providing a user-friendly tool for obtaining maximum likelihood estimates in incomplete multivariate linear models, this book makes complex statistical calculations more accessible and efficient. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book.…

Seller Inventory # 9780365808954_0

Title
Missing (Classic Reprint)
Author
Stanford L. Arner, Donald W. Seegrist
Publisher
Forgotten Books
Publication year
2018
Condition
New
Book Type
print-on-demand item
Binding
Paperback
Language
English
ISBN 10
0365808954
ISBN 13
9780365808954
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Forgotten Books

London, United Kingdom

5-star seller

AbeBooks seller since June 2, 2021

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Forgotten Books’ Classic Reprint Series utilizes the latest technology to regenerate facsimiles of historically important writings. Careful attention has been made to accurately preserve the original format of each page whilst digitally enhancing the quality of the aged text.

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FB &c Ltd

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