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Author: N. Balakrishnan Publisher: Springer Science & Business Media ISBN: 0387096140 Category : Mathematics Languages : en Pages : 714
Book Description
Along with a review of general developments relating to bivariate distributions, this volume also covers copulas, a subject which has grown immensely in recent years. In addition, it examines conditionally specified distributions and skewed distributions.
Author: Jagdish K. Patel Publisher: CRC Press ISBN: 9780824793425 Category : Mathematics Languages : en Pages : 452
Book Description
"Traces the historical development of the normal law. Second Edition offers a comprehensive treatment of the bivariate normal distribution--presenting entirely new material on normal integrals, asymptotic normality, the asymptotic properties of order statistics, and point estimation and statistical intervals."
Author: Aman Ullah Publisher: CRC Press ISBN: 9780824701291 Category : Mathematics Languages : en Pages : 650
Book Description
This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.
Author: John F. Monahan Publisher: Cambridge University Press ISBN: 1139498002 Category : Computers Languages : en Pages : 465
Book Description
This book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods. For mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book offers a basic background in numerical analysis that emphasizes issues important to statisticians. The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression. The author also treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. Each chapter contains exercises that range from simple questions to research problems. Most of the examples are accompanied by demonstration and source code available from the author's website. New in this second edition are demonstrations coded in R, as well as new sections on linear programming and the Nelder–Mead search algorithm.
Author: Abdelhak M. Zoubir Publisher: Cambridge University Press ISBN: 9781139452021 Category : Technology & Engineering Languages : en Pages : 238
Book Description
The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.
Author: American Statistical Association. Statistical Computing Section
Author: American Statistical Association. Statistical Computing Section
Author: United States. National Bureau of Standards
Author: American Statistical Association. Meeting
Author: N. Balakrishnan
Author: United States. Bureau of the Census
Author: Jagdish K. Patel
Author: Aman Ullah
Author: 
Author: John F. Monahan
Author: Abdelhak M. Zoubir