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Some Contributions To Goodness Of Fit Tests And Nonparametric Estimation Of Variance Components
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Book Synopsis Some Contributions to Goodness of Fit Tests and Nonparametric Estimation of Variance Components by : M. Mahibbur Rahman
Download or read book Some Contributions to Goodness of Fit Tests and Nonparametric Estimation of Variance Components written by M. Mahibbur Rahman and published by . This book was released on 1992 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Some Contributions to the Theory of Non-negative Estimation of Variance Components, with Applications by : Shyamal Das Peddada
Download or read book Some Contributions to the Theory of Non-negative Estimation of Variance Components, with Applications written by Shyamal Das Peddada and published by . This book was released on 1983 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Goodness-of-fit Tests in Mixed Models by : Gerda Claeskens
Download or read book Goodness-of-fit Tests in Mixed Models written by Gerda Claeskens and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonparametric Goodness-of-Fit Testing Under Gaussian Models by : Yu. I. Ingster
Download or read book Nonparametric Goodness-of-Fit Testing Under Gaussian Models written by Yu. I. Ingster and published by Springer Science & Business Media. This book was released on 2003 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the modern theory of nonparametric goodness-of-fit testing. It fills the gap in modern nonparametric statistical theory by discussing hypothesis testing and addresses mathematical statisticians who are interesting in the theory of non-parametric statistical inference. It will be of interest to specialists who are dealing with applied non-parametric statistical problems relevant in signal detection and transmission and in technical and medical diagnostics among others.
Book Synopsis Nonparametric Smoothing and Lack-of-Fit Tests by : Jeffrey Hart
Download or read book Nonparametric Smoothing and Lack-of-Fit Tests written by Jeffrey Hart and published by Springer. This book was released on 2012-11-28 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: An exploration of the use of smoothing methods in testing the fit of parametric regression models. The book reviews many of the existing methods for testing lack-of-fit and also proposes a number of new methods, addressing both applied and theoretical aspects of the model checking problems. As such, the book is of interest to practitioners of statistics and researchers investigating either lack-of-fit tests or nonparametric smoothing ideas. The first four chapters introduce the problem of estimating regression functions by nonparametric smoothers, primarily those of kernel and Fourier series type, and could be used as the foundation for a graduate level course on nonparametric function estimation. The prerequisites for a full appreciation of the book are a modest knowledge of calculus and some familiarity with the basics of mathematical statistics.
Book Synopsis Goodness-of-Fit Tests and Model Validity by : C. Huber-Carol
Download or read book Goodness-of-Fit Tests and Model Validity written by C. Huber-Carol and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 37 expository articles in this volume provide broad coverage of important topics relating to the theory, methods, and applications of goodness-of-fit tests and model validity. The book is divided into eight parts, each of which presents topics written by expert researchers in their areas. Key features include: * state-of-the-art exposition of modern model validity methods, graphical techniques, and computer-intensive methods * systematic presentation with sufficient history and coverage of the fundamentals of the subject * exposure to recent research and a variety of open problems * many interesting real life examples for practitioners * extensive bibliography, with special emphasis on recent literature * subject index This comprehensive reference work will serve the statistical and applied mathematics communities as well as practitioners in the field.
Book Synopsis Testing for Goodness of Fit Using Nonparametric Techniques by : Maragatha N. Ramachandran
Download or read book Testing for Goodness of Fit Using Nonparametric Techniques written by Maragatha N. Ramachandran and published by . This book was released on 1992 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book NBS Special Publication written by and published by . This book was released on 1970 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Some Contributions to Nonnegative Estimation of Variance Components by : Anindita Niyogi
Download or read book Some Contributions to Nonnegative Estimation of Variance Components written by Anindita Niyogi and published by . This book was released on 1992 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis American Doctoral Dissertations by :
Download or read book American Doctoral Dissertations written by and published by . This book was released on 2000 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Goodness-of-fit Tests Based on Series Estimators in Nonparametric Instrumental Regression by : Christoph Breunig
Download or read book Goodness-of-fit Tests Based on Series Estimators in Nonparametric Instrumental Regression written by Christoph Breunig and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes several tests of restricted specification in nonparametric instrumental regression. Based on series estimators, test statistics are established that allow for tests of the general model against a parametric or nonparametric specification as well as a test of exogeneity of the vector of regressors. The tests are asymptotically normally distributed under correct specification and consistent against any alternative model. Under a sequence of local alternative hypotheses, the asymptotic distribution of the tests is derived. Moreover, uniform consistency is established over a class of alternatives whose distance to the null hypothesis shrinks appropriately as the sample size increases.
Book Synopsis Goodness-of-fit Tests in Nonparametric Regression by : Johannes Hubertus Jacob Einmahl
Download or read book Goodness-of-fit Tests in Nonparametric Regression written by Johannes Hubertus Jacob Einmahl and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Goodness-of-fit Tests in Measurement Error Models with Replications by : Weijia Jia
Download or read book Goodness-of-fit Tests in Measurement Error Models with Replications written by Weijia Jia and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, goodness-of-fit tests are proposed for checking the adequacy of parametric distributional forms of the regression error density functions and the error-prone predictor density function in measurement error models, when replications of the surrogates of the latent variables are available. In the first project, we propose goodness-of-fit tests on the density function of the regression error in the errors-in-variables model. Instead of assuming that the distribution of the measurement error is known as is done in most relevant literature, we assume that replications of the surrogates of the latent variables are available. The test statistic is based upon a weighted integrated squared distance between a nonparametric estimate and a semi-parametric estimate of the density functions of certain residuals. Under the null hypothesis, the test statistic is shown to be asymptotically normal. Consistency and local power results of the proposed test under fixed alternatives and local alternatives are also established. Finite sample performance of the proposed test is evaluated via simulation studies. A real data example is also included to demonstrate the application of the proposed test. In the second project, we propose a class of goodness-of-fit tests for checking the parametric distributional forms of the error-prone random variables in the classic additive measurement error models. We also assume that replications of the surrogates of the error-prone variables are available. The test statistic is based upon a weighted integrated squared distance between a non-parametric estimator and a semi-parametric estimator of the density functions of the averaged surrogate data. Under the null hypothesis, the minimum distance estimator of the distribution parameters and the test statistics are shown to be asymptotically normal. Consistency and local power of the proposed tests under fixed alternatives and local alternatives are also established. Finite sample performance of the proposed tests is evaluated via simulation studies.
Book Synopsis Bulletin - Institute of Mathematical Statistics by : Institute of Mathematical Statistics
Download or read book Bulletin - Institute of Mathematical Statistics written by Institute of Mathematical Statistics and published by . This book was released on 1996 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Author and Permuted Title Index to Selected Statistical Journals by : Brian L. Joiner
Download or read book An Author and Permuted Title Index to Selected Statistical Journals written by Brian L. Joiner and published by . This book was released on 1970 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: All articles, notes, queries, corrigenda, and obituaries appearing in the following journals during the indicated years are indexed: Annals of mathematical statistics, 1961-1969; Biometrics, 1965-1969#3; Biometrics, 1951-1969; Journal of the American Statistical Association, 1956-1969; Journal of the Royal Statistical Society, Series B, 1954-1969,#2; South African statistical journal, 1967-1969,#2; Technometrics, 1959-1969.--p.iv.
Book Synopsis Partially Linear Models by : Wolfgang Härdle
Download or read book Partially Linear Models written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics. Many methods and techniques have been proposed and studied. This monograph hopes to bring an up-to-date presentation of the state of the art of partially linear regression techniques. The emphasis is on methodologies rather than on the theory, with a particular focus on applications of partially linear regression techniques to various statistical problems. These problems include least squares regression, asymptotically efficient estimation, bootstrap resampling, censored data analysis, linear measurement error models, nonlinear measurement models, nonlinear and nonparametric time series models.
Book Synopsis Nonlinear Estimation by : Gavin J.S. Ross
Download or read book Nonlinear Estimation written by Gavin J.S. Ross and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-Linear Estimation is a handbook for the practical statistician or modeller interested in fitting and interpreting non-linear models with the aid of a computer. A major theme of the book is the use of 'stable parameter systems'; these provide rapid convergence of optimization algorithms, more reliable dispersion matrices and confidence regions for parameters, and easier comparison of rival models. The book provides insights into why some models are difficult to fit, how to combine fits over different data sets, how to improve data collection to reduce prediction variance, and how to program particular models to handle a full range of data sets. The book combines an algebraic, a geometric and a computational approach, and is illustrated with practical examples. A final chapter shows how this approach is implemented in the author's Maximum Likelihood Program, MLP.
