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Statistical Inferences on Odd Frechet Power Function Distribution

Statistical Inferences on Odd Frechet Power Function Distribution PDF Author: Muhammad Ahsan ul Haq
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 32

Book Description
This article introduces a new unit distribution namely odd Frechet power (OFrPF) distribution. Numerous properties of the proposed model including reliability analysis, moments, and Renyi Entropy for the proposed distribution. The parameters of the OFrPF distribution are obtained using different approaches such as maximum likelihood, least squares, weighted least squares, percentile, Cramer-von Mises, Anderson-Darling.

Statistical Inferences on Odd Frechet Power Function Distribution

Statistical Inferences on Odd Frechet Power Function Distribution PDF Author: Muhammad Ahsan ul Haq
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 32

Book Description
This article introduces a new unit distribution namely odd Frechet power (OFrPF) distribution. Numerous properties of the proposed model including reliability analysis, moments, and Renyi Entropy for the proposed distribution. The parameters of the OFrPF distribution are obtained using different approaches such as maximum likelihood, least squares, weighted least squares, percentile, Cramer-von Mises, Anderson-Darling.

Statistical Inference Based on Kernel Distribution Function Estimators

Statistical Inference Based on Kernel Distribution Function Estimators PDF Author: Rizky Reza Fauzi
Publisher: Springer Nature
ISBN: 9819918626
Category : Mathematics
Languages : en
Pages : 103

Book Description
This book presents a study of statistical inferences based on the kernel-type estimators of distribution functions. The inferences involve matters such as quantile estimation, nonparametric tests, and mean residual life expectation, to name just some. Convergence rates for the kernel estimators of density functions are slower than ordinary parametric estimators, which have root-n consistency. If the appropriate kernel function is used, the kernel estimators of the distribution functions recover the root-n consistency, and the inferences based on kernel distribution estimators have root-n consistency. Further, the kernel-type estimator produces smooth estimation results. The estimators based on the empirical distribution function have discrete distribution, and the normal approximation cannot be improved—that is, the validity of the Edgeworth expansion cannot be proved. If the support of the population density function is bounded, there is a boundary problem, namely the estimator does not have consistency near the boundary. The book also contains a study of the mean squared errors of the estimators and the Edgeworth expansion for quantile estimators.

The Fundamentals of Heavy Tails

The Fundamentals of Heavy Tails PDF Author: Jayakrishnan Nair
Publisher: Cambridge University Press
ISBN: 1009062964
Category : Mathematics
Languages : en
Pages : 266

Book Description
Heavy tails –extreme events or values more common than expected –emerge everywhere: the economy, natural events, and social and information networks are just a few examples. Yet after decades of progress, they are still treated as mysterious, surprising, and even controversial, primarily because the necessary mathematical models and statistical methods are not widely known. This book, for the first time, provides a rigorous introduction to heavy-tailed distributions accessible to anyone who knows elementary probability. It tackles and tames the zoo of terminology for models and properties, demystifying topics such as the generalized central limit theorem and regular variation. It tracks the natural emergence of heavy-tailed distributions from a wide variety of general processes, building intuition. And it reveals the controversy surrounding heavy tails to be the result of flawed statistics, then equips readers to identify and estimate with confidence. Over 100 exercises complete this engaging package.

Extreme Value Distributions

Extreme Value Distributions PDF Author: Samuel Kotz
Publisher: World Scientific
ISBN: 1860944027
Category : Mathematics
Languages : en
Pages : 195

Book Description
This important book provides an up-to-date comprehensive and down-to-earth survey of the theory and practice of extreme value distributions OCo one of the most prominent success stories of modern applied probability and statistics. Originated by E J Gumbel in the early forties as a tool for predicting floods, extreme value distributions evolved during the last 50 years into a coherent theory with applications in practically all fields of human endeavor where maximal or minimal values (the so-called extremes) are of relevance. The book is of usefulness both for a beginner with a limited probabilistic background and to expert in the field. Sample Chapter(s). Chapter 1.1: Historical Survey (139 KB). Chapter 1.2: The Three Types of Extreme Value Distributions (146 KB). Chapter 1.3: Limiting Distributions and Domain of Attraction (210 KB). Chapter 1.4: Distribution Function and Moments of Type 1 Distribution (160 KB). Chapter 1.5: Order Statistics, Record Values and Characterizations (175 KB). Contents: Univariate Extreme Value Distributions; Generalized Extreme Value Distributions; Multivariate Extreme Value Distributions. Readership: Applied probabilists, applied statisticians, environmental scientists, climatologists, industrial engineers and management experts."

Probability Theory and Statistical Inference

Probability Theory and Statistical Inference PDF Author: Aris Spanos
Publisher: Cambridge University Press
ISBN: 1107185149
Category : Business & Economics
Languages : en
Pages : 787

Book Description
This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.

Field Guide to Continuous Probability Distributions

Field Guide to Continuous Probability Distributions PDF Author: Gavin E Crooks
Publisher:
ISBN: 9781733938105
Category :
Languages : en
Pages : 210

Book Description
A common problem is that of describing the probability distribution of a single, continuous variable. A few distributions, such as the normal and exponential, were discovered in the 1800's or earlier. But about a century ago the great statistician, Karl Pearson, realized that the known probability distributions were not sufficient to handle all of the phenomena then under investigation, and set out to create new distributions with useful properties. During the 20th century this process continued with abandon and a vast menagerie of distinct mathematical forms were discovered and invented, investigated, analyzed, rediscovered and renamed, all for the purpose of describing the probability of some interesting variable. There are hundreds of named distributions and synonyms in current usage. The apparent diversity is unending and disorienting. Fortunately, the situation is less confused than it might at first appear. Most common, continuous, univariate, unimodal distributions can be organized into a small number of distinct families, which are all special cases of a single Grand Unified Distribution. This compendium details these hundred or so simple distributions, their properties and their interrelations.

Introduction to Probability and Statistics Using R

Introduction to Probability and Statistics Using R PDF Author: G. Jay Kerns
Publisher: Lulu.com
ISBN: 0557249791
Category : Education
Languages : en
Pages : 388

Book Description
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.

Optimal Decision Making in Operations Research and Statistics

Optimal Decision Making in Operations Research and Statistics PDF Author: Irfan Ali
Publisher: CRC Press
ISBN: 1000404722
Category : Business & Economics
Languages : en
Pages : 434

Book Description
The book provides insights in the decision-making for implementing strategies in various spheres of real-world issues. It integrates optimal policies in various decision­making problems and serves as a reference for researchers and industrial practitioners. Furthermore, the book provides sound knowledge of modelling of real-world problems and solution procedure using the various optimisation and statistical techniques for making optimal decisions. The book is meant for teachers, students, researchers and industrialists who are working in the field of materials science, especially operations research and applied statistics.

Foundations of Statistical Inference

Foundations of Statistical Inference PDF Author: Yoel Haitovsky
Publisher: Springer Science & Business Media
ISBN: 3642574106
Category : Mathematics
Languages : en
Pages : 227

Book Description
This volume is a collection of papers presented at a conference held in Shoresh Holiday Resort near Jerusalem, Israel, in December 2000 organized by the Israeli Ministry of Science, Culture and Sport. The theme of the conference was "Foundation of Statistical Inference: Applications in the Medical and Social Sciences and in Industry and the Interface of Computer Sciences". The following is a quotation from the Program and Abstract booklet of the conference. "Over the past several decades, the field of statistics has seen tremendous growth and development in theory and methodology. At the same time, the advent of computers has facilitated the use of modern statistics in all branches of science, making statistics even more interdisciplinary than in the past; statistics, thus, has become strongly rooted in all empirical research in the medical, social, and engineering sciences. The abundance of computer programs and the variety of methods available to users brought to light the critical issues of choosing models and, given a data set, the methods most suitable for its analysis. Mathematical statisticians have devoted a great deal of effort to studying the appropriateness of models for various types of data, and defining the conditions under which a particular method work. " In 1985 an international conference with a similar title* was held in Is rael. It provided a platform for a formal debate between the two main schools of thought in Statistics, the Bayesian, and the Frequentists.

Stochastic Orders

Stochastic Orders PDF Author: Moshe Shaked
Publisher: Springer Science & Business Media
ISBN: 0387346759
Category : Mathematics
Languages : en
Pages : 482

Book Description
This reference text presents comprehensive coverage of the various notions of stochastic orderings, their closure properties, and their applications. Some of these orderings are routinely used in many applications in economics, finance, insurance, management science, operations research, statistics, and various other fields. And the value of the other notions of stochastic orderings needs further exploration. This book is an ideal reference for those interested in decision making under uncertainty and interested in the analysis of complex stochastic systems. It is suitable as a text for advanced graduate course on stochastic ordering and applications.