Technical Abstract Bulletin

Technical Abstract Bulletin PDF Author: Defense Documentation Center (U.S.)
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 784

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Technical Abstract Bulletin

Technical Abstract Bulletin PDF Author: Defense Documentation Center (U.S.)
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 784

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Book Description


Government-wide Index to Federal Research & Development Reports

Government-wide Index to Federal Research & Development Reports PDF Author:
Publisher:
ISBN:
Category : Government publications
Languages : en
Pages : 1078

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Government Reports Annual Index

Government Reports Annual Index PDF Author:
Publisher:
ISBN:
Category : Government reports announcements & index
Languages : en
Pages : 1018

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Statistical Analysis of Finite Mixture Distributions

Statistical Analysis of Finite Mixture Distributions PDF Author: D. M. Titterington
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 264

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Book Description
In this book, the authors give a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions.

Journal of the American Statistical Association

Journal of the American Statistical Association PDF Author:
Publisher:
ISBN:
Category : Electronic journals
Languages : en
Pages : 796

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An Introductory Guide to EC Competition Law and Practice

An Introductory Guide to EC Competition Law and Practice PDF Author: Valentine Korah
Publisher:
ISBN:
Category : Antitrust law
Languages : en
Pages : 2354

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Scientific and Technical Aerospace Reports

Scientific and Technical Aerospace Reports PDF Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 244

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Loss Models

Loss Models PDF Author: Stuart A. Klugman
Publisher: John Wiley & Sons
ISBN: 0470391332
Category : Business & Economics
Languages : en
Pages : 758

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Book Description
An update of one of the most trusted books on constructing and analyzing actuarial models Written by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk theory, loss distributions, and survival models. Random variables, basic distributional quantities, the recursive method, and techniques for classifying and creating distributions are also discussed. Both parametric and non-parametric estimation methods are thoroughly covered along with advice for choosing an appropriate model. Features of the Third Edition include: Extended discussion of risk management and risk measures, including Tail-Value-at-Risk (TVaR) New sections on extreme value distributions and their estimation Inclusion of homogeneous, nonhomogeneous, and mixed Poisson processes Expanded coverage of copula models and their estimation Additional treatment of methods for constructing confidence regions when there is more than one parameter The book continues to distinguish itself by providing over 400 exercises that have appeared on previous SOA and CAS examinations. Intriguing examples from the fields of insurance and business are discussed throughout, and all data sets are available on the book's FTP site, along with programs that assist with conducting loss model analysis. Loss Models, Third Edition is an essential resource for students and aspiring actuaries who are preparing to take the SOA and CAS preliminary examinations. It is also a must-have reference for professional actuaries, graduate students in the actuarial field, and anyone who works with loss and risk models in their everyday work. To explore our additional offerings in actuarial exam preparation visit www.wiley.com/go/actuarialexamprep.

Nonparametric Functional Estimation

Nonparametric Functional Estimation PDF Author: B. L. S. Prakasa Rao
Publisher: Academic Press
ISBN: 148326923X
Category : Mathematics
Languages : en
Pages : 539

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Book Description
Nonparametric Functional Estimation is a compendium of papers, written by experts, in the area of nonparametric functional estimation. This book attempts to be exhaustive in nature and is written both for specialists in the area as well as for students of statistics taking courses at the postgraduate level. The main emphasis throughout the book is on the discussion of several methods of estimation and on the study of their large sample properties. Chapters are devoted to topics on estimation of density and related functions, the application of density estimation to classification problems, and the different facets of estimation of distribution functions. Statisticians and students of statistics and engineering will find the text very useful.

Large Sample Techniques for Statistics

Large Sample Techniques for Statistics PDF Author: Jiming Jiang
Publisher: Springer Science & Business Media
ISBN: 144196827X
Category : Mathematics
Languages : en
Pages : 612

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Book Description
In a way, the world is made up of approximations, and surely there is no exception in the world of statistics. In fact, approximations, especially large sample approximations, are very important parts of both theoretical and - plied statistics.TheGaussiandistribution,alsoknownasthe normaldistri- tion,is merelyonesuchexample,dueto thewell-knowncentrallimittheorem. Large-sample techniques provide solutions to many practical problems; they simplify our solutions to di?cult, sometimes intractable problems; they j- tify our solutions; and they guide us to directions of improvements. On the other hand, just because large-sample approximations are used everywhere, and every day, it does not guarantee that they are used properly, and, when the techniques are misused, there may be serious consequences. 2 Example 1 (Asymptotic? distribution). Likelihood ratio test (LRT) is one of the fundamental techniques in statistics. It is well known that, in the 2 “standard” situation, the asymptotic null distribution of the LRT is?,with the degreesoffreedomequaltothe di?erencebetweenthedimensions,de?ned as the numbers of free parameters, of the two nested models being compared (e.g., Rice 1995, pp. 310). This might lead to a wrong impression that the 2 asymptotic (null) distribution of the LRT is always? . A similar mistake 2 might take place when dealing with Pearson’s? -test—the asymptotic distri- 2 2 bution of Pearson’s? -test is not always? (e.g., Moore 1978).