Fundamentals Of Statistics With Fuzzy Data PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Fundamentals Of Statistics With Fuzzy Data PDF full book. Access full book title Fundamentals Of Statistics With Fuzzy Data.

Fundamentals of Statistics with Fuzzy Data

Fundamentals of Statistics with Fuzzy Data
Author: Hung T. Nguyen
Publisher: Springer
Total Pages: 196
Release: 2009-09-02
Genre: Mathematics
ISBN: 9783540819981

Download Fundamentals of Statistics with Fuzzy Data Book in PDF, ePub and Kindle

This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The book aims at motivating statisticians to examine fuzzy statistics to enlarge the domain of applicability of statistics in general.


Statistical Methods for Fuzzy Data

Statistical Methods for Fuzzy Data
Author: Reinhard Viertl
Publisher: John Wiley & Sons
Total Pages: 199
Release: 2011-01-25
Genre: Mathematics
ISBN: 0470974567

Download Statistical Methods for Fuzzy Data Book in PDF, ePub and Kindle

Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information. Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data. This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.


Fundamentals of Statistics with Fuzzy Data

Fundamentals of Statistics with Fuzzy Data
Author: Hung T. Nguyen
Publisher: Springer
Total Pages: 0
Release: 2006-02-28
Genre: Mathematics
ISBN: 3540316973

Download Fundamentals of Statistics with Fuzzy Data Book in PDF, ePub and Kindle

This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The book aims at motivating statisticians to examine fuzzy statistics to enlarge the domain of applicability of statistics in general.


Fuzzy Data Analysis

Fuzzy Data Analysis
Author: Hans Bandemer
Publisher: Springer Science & Business Media
Total Pages: 351
Release: 2012-12-06
Genre: Mathematics
ISBN: 9401125066

Download Fuzzy Data Analysis Book in PDF, ePub and Kindle

Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.


Fuzzy Statistical Decision-Making

Fuzzy Statistical Decision-Making
Author: Cengiz Kahraman
Publisher: Springer
Total Pages: 358
Release: 2016-07-15
Genre: Technology & Engineering
ISBN: 3319390147

Download Fuzzy Statistical Decision-Making Book in PDF, ePub and Kindle

This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas and developments.


Statistical Modeling, Analysis and Management of Fuzzy Data

Statistical Modeling, Analysis and Management of Fuzzy Data
Author: Carlo Bertoluzza
Publisher: Physica
Total Pages: 315
Release: 2012-11-02
Genre: Computers
ISBN: 3790818003

Download Statistical Modeling, Analysis and Management of Fuzzy Data Book in PDF, ePub and Kindle

The contributions in this book state the complementary rather than competitive relationship between Probability and Fuzzy Set Theory and allow solutions to real life problems with suitable combinations of both theories.


Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas

Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas
Author: Vladik Kreinovich
Publisher: Springer Nature
Total Pages: 271
Release: 2020-06-19
Genre: Technology & Engineering
ISBN: 3030456196

Download Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas Book in PDF, ePub and Kindle

Mainly focusing on processing uncertainty, this book presents state-of-the-art techniques and demonstrates their use in applications to econometrics and other areas. Processing uncertainty is essential, considering that computers – which help us understand real-life processes and make better decisions based on that understanding – get their information from measurements or from expert estimates, neither of which is ever 100% accurate. Measurement uncertainty is usually described using probabilistic techniques, while uncertainty in expert estimates is often described using fuzzy techniques. Therefore, it is important to master both techniques for processing data. This book is highly recommended for researchers and students interested in the latest results and challenges in uncertainty, as well as practitioners who want to learn how to use the corresponding state-of-the-art techniques.


Fuzzy Statistics

Fuzzy Statistics
Author: James J. Buckley
Publisher: Springer
Total Pages: 166
Release: 2013-11-11
Genre: Technology & Engineering
ISBN: 3540399194

Download Fuzzy Statistics Book 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 Probability and Statistics

Fuzzy Probability and Statistics
Author: James J. Buckley
Publisher: Springer
Total Pages: 262
Release: 2008-09-12
Genre: Computers
ISBN: 3540331905

Download Fuzzy Probability and Statistics Book 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.