Saddlepoint Approximations Edgeworth Expansions And Normal Approximations
Download Saddlepoint Approximations Edgeworth Expansions And Normal Approximations full books in PDF, epub, and Kindle. Read online free Saddlepoint Approximations Edgeworth Expansions And Normal Approximations ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads.
Author |
: Jens Ledet Jensen |
Publisher |
: |
Total Pages |
: 106 |
Release |
: 1993 |
ISBN-10 |
: UOM:39015032187547 |
ISBN-13 |
: |
Rating |
: 4/5 (47 Downloads) |
Synopsis Saddlepoint Approximations, Edgeworth Expansions and Normal Approximations by : Jens Ledet Jensen
Author |
: Jens Ledet Jensen |
Publisher |
: Oxford University Press |
Total Pages |
: 348 |
Release |
: 1995 |
ISBN-10 |
: 0198522959 |
ISBN-13 |
: 9780198522959 |
Rating |
: 4/5 (59 Downloads) |
Synopsis Saddlepoint Approximations by : Jens Ledet Jensen
This book explains the ideas behind the saddlepoint approximations as well as giving a detailed mathematical description of the subject and many worked out examples.
Author |
: Ronald W. Butler |
Publisher |
: Cambridge University Press |
Total Pages |
: 548 |
Release |
: 2007-08-16 |
ISBN-10 |
: 9781139466516 |
ISBN-13 |
: 1139466518 |
Rating |
: 4/5 (16 Downloads) |
Synopsis Saddlepoint Approximations with Applications by : Ronald W. Butler
Modern statistical methods use complex, sophisticated models that can lead to intractable computations. Saddlepoint approximations can be the answer. Written from the user's point of view, this book explains in clear language how such approximate probability computations are made, taking readers from the very beginnings to current applications. The core material is presented in chapters 1-6 at an elementary mathematical level. Chapters 7-9 then give a highly readable account of higher-order asymptotic inference. Later chapters address areas where saddlepoint methods have had substantial impact: multivariate testing, stochastic systems and applied probability, bootstrap implementation in the transform domain, and Bayesian computation and inference. No previous background in the area is required. Data examples from real applications demonstrate the practical value of the methods. Ideal for graduate students and researchers in statistics, biostatistics, electrical engineering, econometrics, and applied mathematics, this is both an entry-level text and a valuable reference.
Author |
: Yue Kuen Kwok |
Publisher |
: Springer |
Total Pages |
: 134 |
Release |
: 2018-02-16 |
ISBN-10 |
: 9783319741017 |
ISBN-13 |
: 3319741012 |
Rating |
: 4/5 (17 Downloads) |
Synopsis Saddlepoint Approximation Methods in Financial Engineering by : Yue Kuen Kwok
This book summarizes recent advances in applying saddlepoint approximation methods to financial engineering. It addresses pricing exotic financial derivatives and calculating risk contributions to Value-at-Risk and Expected Shortfall in credit portfolios under various default correlation models. These standard problems involve the computation of tail probabilities and tail expectations of the corresponding underlying state variables. The text offers in a single source most of the saddlepoint approximation results in financial engineering, with different sets of ready-to-use approximation formulas. Much of this material may otherwise only be found in original research publications. The exposition and style are made rigorous by providing formal proofs of most of the results. Starting with a presentation of the derivation of a variety of saddlepoint approximation formulas in different contexts, this book will help new researchers to learn the fine technicalities of the topic. It will also be valuable to quantitative analysts in financial institutions who strive for effective valuation of prices of exotic financial derivatives and risk positions of portfolios of risky instruments.
Author |
: Anirban DasGupta |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 726 |
Release |
: 2008-03-07 |
ISBN-10 |
: 9780387759708 |
ISBN-13 |
: 0387759700 |
Rating |
: 4/5 (08 Downloads) |
Synopsis Asymptotic Theory of Statistics and Probability by : Anirban DasGupta
This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. The book is unique in its detailed coverage of fundamental topics. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. There is no other book in large sample theory that matches this book in coverage, exercises and examples, bibliography, and lucid conceptual discussion of issues and theorems.
Author |
: John E. Kolassa |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 162 |
Release |
: 2013-04-17 |
ISBN-10 |
: 9781475742756 |
ISBN-13 |
: 1475742754 |
Rating |
: 4/5 (56 Downloads) |
Synopsis Series Approximation Methods in Statistics by : John E. Kolassa
This book was originally compiled for a course I taught at the University of Rochester in the fall of 1991, and is intended to give advanced graduate students in statistics an introduction to Edgeworth and saddlepoint approximations, and related techniques. Many other authors have also written monographs on this subject, and so this work is narrowly focused on two areas not recently discussed in theoretical text books. These areas are, first, a rigorous consideration of Edgeworth and saddlepoint expansion limit theorems, and second, a survey of the more recent developments in the field. In presenting expansion limit theorems I have drawn heavily 011 notation of McCullagh (1987) and on the theorems presented by Feller (1971) on Edgeworth expansions. For saddlepoint notation and results I relied most heavily on the many papers of Daniels, and a review paper by Reid (1988). Throughout this book I have tried to maintain consistent notation and to present theorems in such a way as to make a few theoretical results useful in as many contexts as possible. This was not only in order to present as many results with as few proofs as possible, but more importantly to show the interconnections between the various facets of asymptotic theory. Special attention is paid to regularity conditions. The reasons they are needed and the parts they play in the proofs are both highlighted.
Author |
: John E. Kolassa |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 194 |
Release |
: 2013-04-17 |
ISBN-10 |
: 9781475742770 |
ISBN-13 |
: 1475742770 |
Rating |
: 4/5 (70 Downloads) |
Synopsis Series Approximation Methods in Statistics by : John E. Kolassa
This book was originally compiled for a course I taught at the University of Rochester in the fall of 1991, and is intended to give advanced graduate students in statistics an introduction to Edgeworth and saddlepoint approximations, and related techniques. Many other authors have also written monographs on this sub ject, and so this work is narrowly focused on two areas not recently discussed in theoretical text books. These areas are, first, a rigorous consideration of Edgeworth and saddlepoint expansion limit theorems, and second, a survey of the more recent developments in the field. In presenting expansion limit theorems I have drawn heavily on notation of McCullagh (1987) and on the theorems presented by Feller (1971) on Edgeworth expansions. For saddlepoint notation and results I relied most heavily on the many papers of Daniels, and a review paper by Reid (1988). Throughout this book I have tried to maintain consistent notation and to present theorems in such a way as to make a few theoretical results useful in as many contexts aS possible. This was not only in order to present as many results with as few proofs as possible, but more importantly to show the interconnections between the various facets of asymptotic theory. Special attention is paid to regularity conditions. The reasons they are needed and the parts they play in the proofs are both highlighted.
Author |
: Matthias Gundlach |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 376 |
Release |
: 2013-03-14 |
ISBN-10 |
: 9783662064276 |
ISBN-13 |
: 3662064278 |
Rating |
: 4/5 (76 Downloads) |
Synopsis CreditRisk+ in the Banking Industry by : Matthias Gundlach
CreditRisk+ is a widely implemented default-mode model of portfolio credit risk, based on a methodology borrowed from actuarial mathematics. This book gives an account of the status quo as well as of new and recent developments of the credit risk model CreditRisk+, which is widely used in the banking industry. It gives an introduction to the model itself and to its ability to describe, manage and price credit risk. This timely book will be an indispensable tool.
Author |
: Christopher A. Field |
Publisher |
: IMS |
Total Pages |
: 166 |
Release |
: 1990 |
ISBN-10 |
: 0940600188 |
ISBN-13 |
: 9780940600188 |
Rating |
: 4/5 (88 Downloads) |
Synopsis Small Sample Asymptotics by : Christopher A. Field
Author |
: Thomas A. Severini |
Publisher |
: Cambridge University Press |
Total Pages |
: 534 |
Release |
: 2005-08-08 |
ISBN-10 |
: 052184472X |
ISBN-13 |
: 9780521844727 |
Rating |
: 4/5 (2X Downloads) |
Synopsis Elements of Distribution Theory by : Thomas A. Severini
This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively.