Fuzzy Probability and Statistics

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Release : 2008-09-12
Genre : Computers
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Book Rating : 905/5 ( reviews)

Fuzzy Probability and Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Probability and Statistics write by James J. Buckley. This book was released on 2008-09-12. Fuzzy Probability and Statistics available in PDF, EPUB and Kindle. This book combines material from our previous books FP (Fuzzy Probabilities: New Approach and Applications,Physica-Verlag, 2003) and FS (Fuzzy Statistics, Springer, 2004), plus has about one third new results. From FP we have material on basic fuzzy probability, discrete (fuzzy Poisson,binomial) and continuous (uniform, normal, exponential) fuzzy random variables. From FS we included chapters on fuzzy estimation and fuzzy hypothesis testing related to means, variances, proportions, correlation and regression. New material includes fuzzy estimators for arrival and service rates, and the uniform distribution, with applications in fuzzy queuing theory. Also, new to this book, is three chapters on fuzzy maximum entropy (imprecise side conditions) estimators producing fuzzy distributions and crisp discrete/continuous distributions. Other new results are: (1) two chapters on fuzzy ANOVA (one-way and two-way); (2) random fuzzy numbers with applications to fuzzy Monte Carlo studies; and (3) a fuzzy nonparametric estimator for the median.

Fuzzy Probabilities

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Release : 2012-12-06
Genre : Computers
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Book Rating : 863/5 ( reviews)

Fuzzy Probabilities - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Probabilities write by James J. Buckley. This book was released on 2012-12-06. Fuzzy Probabilities available in PDF, EPUB and Kindle. In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals. In probability calculations we apply constrained fuzzy arithmetic because probabilities must add to one. Fuzzy random variables have fuzzy distributions. A fuzzy normal random variable has the normal distribution with fuzzy number mean and variance. Applications are to queuing theory, Markov chains, inventory control, decision theory and reliability theory.

Fuzzy Statistics

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Release : 2013-11-11
Genre : Technology & Engineering
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Book Rating : 194/5 ( reviews)

Fuzzy Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Statistics write by James J. Buckley. This book was released on 2013-11-11. Fuzzy Statistics available in PDF, EPUB and Kindle. 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.

Fuzzy Logic and Probability Applications

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Release : 2002-01-01
Genre : Mathematics
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Book Rating : 253/5 ( reviews)

Fuzzy Logic and Probability Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Logic and Probability Applications write by Timothy J. Ross. This book was released on 2002-01-01. Fuzzy Logic and Probability Applications available in PDF, EPUB and Kindle. Shows both the shortcomings and benefits of each technique, and even demonstrates useful combinations of the two.

Fuzzy Statistical Inferences Based on Fuzzy Random Variables

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Release : 2022-02-24
Genre : Mathematics
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Book Rating : 776/5 ( reviews)

Fuzzy Statistical Inferences Based on Fuzzy Random Variables - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Statistical Inferences Based on Fuzzy Random Variables write by Gholamreza Hesamian. This book was released on 2022-02-24. Fuzzy Statistical Inferences Based on Fuzzy Random Variables available in PDF, EPUB and Kindle. This book presents the most commonly used techniques for the most statistical inferences based on fuzzy data. It brings together many of the main ideas used in statistical inferences in one place, based on fuzzy information including fuzzy data. This book covers a much wider range of topics than a typical introductory text on fuzzy statistics. It includes common topics like elementary probability, descriptive statistics, hypothesis tests, one-way ANOVA, control-charts, reliability systems and regression models. The reader is assumed to know calculus and a little fuzzy set theory. The conventional knowledge of probability and statistics is required. Key Features: Includes example in Mathematica and MATLAB. Contains theoretical and applied exercises for each section. Presents various popular methods for analyzing fuzzy data. The book is suitable for students and researchers in statistics, social science, engineering, and economics, and it can be used at graduate and P.h.D level.