Fuzzy Statistics (Hardcover, 2004 ed.)

1. 1 Introduction This book is written in four major divisions. The first part is the introductory chapters consisting of Chapters 1 and 2. In part two, Chapters 3-11, we develop fuzzy estimation. For example, in Chapter 3 we construct a fuzzy estimator for the mean of a normal distribution assuming the variance is known. More details on fuzzy estimation are in Chapter 3 and then after Chapter 3, Chapters 4-11 can be read independently. Part three, Chapters 12- 20, are on fuzzy hypothesis testing. For example, in Chapter 12 we consider the test Ho : /1 = /10 verses HI : /1 f=- /10 where /1 is the mean of a normal distribution with known variance, but we use a fuzzy number (from Chapter 3) estimator of /1 in the test statistic. More details on fuzzy hypothesis testing are in Chapter 12 and then after Chapter 12 Chapters 13-20 may be read independently. Part four, Chapters 21-27, are on fuzzy regression and fuzzy prediction. We start with fuzzy correlation in Chapter 21. Simple linear regression is the topic in Chapters 22-24 and Chapters 25-27 concentrate on multiple linear regression. Part two (fuzzy estimation) is used in Chapters 22 and 25; and part 3 (fuzzy hypothesis testing) is employed in Chapters 24 and 27. Fuzzy prediction is contained in Chapters 23 and 26. A most important part of our models in fuzzy statistics is that we always start with a random sample producing crisp (non-fuzzy) data.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Studies in Fuzziness and Soft Computing, 149
Release date:	April 2004
First published:	April 2004
Authors:	James J Buckley
Dimensions:	235 x 155 x 11mm (L x W x T)
Format:	Hardcover
Pages:	168
Edition:	2004 ed.
ISBN-13:	978-3-540-21084-9
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics
LSN:	3-540-21084-9
Barcode:	9783540210849

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