Minimax Linear Predictor Under Lipschitz' Type Conditions for the Regression
Language: English
Published by Forgotten Books, 2024
- Softcover
- New
Seller: Forgotten Books, London, United KingdomForgotten Books
AbeBooks seller since June 2, 2021
Condition: New
£ 13.52
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Print on Demand. This book concentrates on a highly specialized problem in statistical data analysis: how to use linear functions to model relationships when the shape of those relationships is not known. The author approaches this through a mathematical theory he devises to solve a common but poorly understood pitfall in the statistical process: how to avoid getting paradoxical results when using a linear predictor function with insufficient or ambiguous data. The techniques and theoretical framework he develops will be of great value to experienced statisticians and data modelers working within a wide range of disciplines and fields. 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 # 9781333294625_0
- Title
- Minimax Linear Predictor Under Lipschitz' Type Conditions for the Regression
- Author
- Kei Takeuchi
- Publisher
- Forgotten Books
- Publication year
- 2024
- Condition
- New
- Book Type
- print-on-demand item
- Binding
- Paperback
- Language
- English
- ISBN 10
- 133329462X
- ISBN 13
- 9781333294625
- Seller catalogs
- Statistics
Regression analysis is the most (or at least one of the most) popular and most often used techniques in various fields of statistical data analysis. In some cases, how ever, regression analysis is very dangerous, and sometimes gives awkward results. Such dangers, which are inherent in regression techniques, are well known, at least well perceived by experienced applied statisticians. But theoretical analysis of such a situation that yields some pitfalls to the careless application of regression analysis is far from satisfactory. Though well trained statisticians can evade such a danger by their good judgment, there is no formal well established technique that may be applied. The purpose of this paper is to derive some method to treat one such difficulty, i.e. The problem of the functional form of the regression.
Suppose that we have a quantity or response Y, which is influenced by some quantity or explanatory variable x.
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Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com
This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
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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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Forgotten Books publishes hundreds of thousands of rare and classic books.
This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
This text has been digitally restored from a historical edition. Some errors may persist, however we consider it worth publishing due to the work's historical value.
The digital edition of all books may be viewed before purchase if you request a sample.
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