A First Course On Parametric Inference


A First Course On Parametric Inference
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A First Course On Parametric Inference


A First Course On Parametric Inference
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Author : Balvant Keshav Kale
language : en
Publisher: Alpha Science Int'l Ltd.
Release Date : 2005

A First Course On Parametric Inference written by Balvant Keshav Kale and has been published by Alpha Science Int'l Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Business & Economics categories.


"After a brief historical perspective, A First Course on Parametric Inference, discusses the basic concept of sufficient statistic and the classical approach based on minimum variance unbiased estimator. There is a separate chapter on simultaneous estimation of several parameters. Large sample theory of estimation, based on consistent asymptotically normal estimators obtained by method of moments, percentile and the method of maximum likelihood is also introduced. The tests of hypotheses for finite samples with classical Neyman-Pearson theory is developed pointing out its connection with Bayesian approach. The hypotheses testing and confidence interval techniques are developed leading to likelihood ratio tests, score tests and tests based on maximum likelihood estimators."--BOOK JACKET.



A First Course In Parametric Inference


A First Course In Parametric Inference
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Author : B. K. Kale
language : en
Publisher:
Release Date : 1998-02-28

A First Course In Parametric Inference written by B. K. Kale and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-02-28 with Mathematical statistics categories.


Starting with the basic concept of sufficient statistics, the classical approach based on minimum variance, unbiased estimation is presented in this text.



Parametric Inference


Parametric Inference
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Author : Balvant Keshav Kale
language : en
Publisher:
Release Date : 2015

Parametric Inference written by Balvant Keshav Kale and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Parameter estimation categories.




Examples In Parametric Inference With R


Examples In Parametric Inference With R
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Author : Ulhas Jayram Dixit
language : en
Publisher: Springer
Release Date : 2016-05-20

Examples In Parametric Inference With R written by Ulhas Jayram Dixit and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-20 with Mathematics categories.


This book discusses examples in parametric inference with R. Combining basic theory with modern approaches, it presents the latest developments and trends in statistical inference for students who do not have an advanced mathematical and statistical background. The topics discussed in the book are fundamental and common to many fields of statistical inference and thus serve as a point of departure for in-depth study. The book is divided into eight chapters: Chapter 1 provides an overview of topics on sufficiency and completeness, while Chapter 2 briefly discusses unbiased estimation. Chapter 3 focuses on the study of moments and maximum likelihood estimators, and Chapter 4 presents bounds for the variance. In Chapter 5, topics on consistent estimator are discussed. Chapter 6 discusses Bayes, while Chapter 7 studies some more powerful tests. Lastly, Chapter 8 examines unbiased and other tests. Senior undergraduate and graduate students in statistics and mathematics, and those who have taken an introductory course in probability, will greatly benefit from this book. Students are expected to know matrix algebra, calculus, probability and distribution theory before beginning this course. Presenting a wealth of relevant solved and unsolved problems, the book offers an excellent tool for teachers and instructors who can assign homework problems from the exercises, and students will find the solved examples hugely beneficial in solving the exercise problems.



All Of Statistics


All Of Statistics
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Author : Larry Wasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-11

All Of Statistics written by Larry Wasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-11 with Mathematics categories.


Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.



Statistical Inference


Statistical Inference
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Author : Michael J. Panik
language : en
Publisher: John Wiley & Sons
Release Date : 2012-06-06

Statistical Inference written by Michael J. Panik and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-06 with Mathematics categories.


A concise, easily accessible introduction to descriptive and inferential techniques Statistical Inference: A Short Course offers a concise presentation of the essentials of basic statistics for readers seeking to acquire a working knowledge of statistical concepts, measures, and procedures. The author conducts tests on the assumption of randomness and normality, provides nonparametric methods when parametric approaches might not work. The book also explores how to determine a confidence interval for a population median while also providing coverage of ratio estimation, randomness, and causality. To ensure a thorough understanding of all key concepts, Statistical Inference provides numerous examples and solutions along with complete and precise answers to many fundamental questions, including: How do we determine that a given dataset is actually a random sample? With what level of precision and reliability can a population sample be estimated? How are probabilities determined and are they the same thing as odds? How can we predict the level of one variable from that of another? What is the strength of the relationship between two variables? The book is organized to present fundamental statistical concepts first, with later chapters exploring more advanced topics and additional statistical tests such as Distributional Hypotheses, Multinomial Chi-Square Statistics, and the Chi-Square Distribution. Each chapter includes appendices and exercises, allowing readers to test their comprehension of the presented material. Statistical Inference: A Short Course is an excellent book for courses on probability, mathematical statistics, and statistical inference at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for researchers and practitioners who would like to develop further insights into essential statistical tools.



A First Course In Order Statistics


A First Course In Order Statistics
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Author : Barry C. Arnold
language : en
Publisher: SIAM
Release Date : 2008-09-25

A First Course In Order Statistics written by Barry C. Arnold and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-25 with Mathematics categories.


This updated classic text will aid readers in understanding much of the current literature on order statistics: a flourishing field of study that is essential for any practising statistician and a vital part of the training for students in statistics. Written in a simple style that requires no advanced mathematical or statistical background, the book introduces the general theory of order statistics and their applications. The book covers topics such as distribution theory for order statistics from continuous and discrete populations, moment relations, bounds and approximations, order statistics in statistical inference and characterisation results, and basic asymptotic theory. There is also a short introduction to record values and related statistics. The authors have updated the text with suggestions for further reading that may be used for self-study. Written for advanced undergraduate and graduate students in statistics and mathematics, practising statisticians, engineers, climatologists, economists, and biologists.



Parametric Inference


Parametric Inference
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Author : B K Kale
language : en
Publisher:
Release Date : 2015

Parametric Inference written by B K Kale and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.




A First Course In Multivariate Statistics


A First Course In Multivariate Statistics
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Author : Bernard Flury
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

A First Course In Multivariate Statistics written by Bernard Flury and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.


A comprehensive and self-contained introduction to the field, carefully balancing mathematical theory and practical applications. It starts at an elementary level, developing concepts of multivariate distributions from first principles. After a chapter on the multivariate normal distribution reviewing the classical parametric theory, methods of estimation are explored using the plug-in principles as well as maximum likelihood. Two chapters on discrimination and classification, including logistic regression, form the core of the book, followed by methods of testing hypotheses developed from heuristic principles, likelihood ratio tests and permutation tests. Finally, the powerful self-consistency principle is used to introduce principal components as a method of approximation, rounded off by a chapter on finite mixture analysis.



Parametric Statistical Inference


Parametric Statistical Inference
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Author : Shelemyahu Zacks
language : en
Publisher: Elsevier
Release Date : 2014-05-20

Parametric Statistical Inference written by Shelemyahu Zacks and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-20 with Mathematics categories.


Parametric Statistical Inference: Basic Theory and Modern Approaches presents the developments and modern trends in statistical inference to students who do not have advanced mathematical and statistical preparation. The topics discussed in the book are basic and common to many fields of statistical inference and thus serve as a jumping board for in-depth study. The book is organized into eight chapters. Chapter 1 provides an overview of how the theory of statistical inference is presented in subsequent chapters. Chapter 2 briefly discusses statistical distributions and their properties. Chapter 3 is devoted to the problem of sufficient statistics and the information in samples, and Chapter 4 presents some basic results from the theory of testing statistical hypothesis. In Chapter 5, the classical theory of estimation is developed. Chapter 6 discusses the efficiency of estimators and some large sample properties, while Chapter 7 studies the topics on confidence intervals. Finally, Chapter 8 is about decision theoretic and Bayesian approach in testing and estimation. Senior undergraduate and graduate students in statistics and mathematics, and those who have taken an introductory course in probability will highly benefit from this book.