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Nonparametric Independence Screening And Test Based Screening Via The Variance Of The Regression Function
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Book Synopsis Nonparametric Independence Screening And Test-based Screening Via The Variance Of The Regression Function by : Won Song
Download or read book Nonparametric Independence Screening And Test-based Screening Via The Variance Of The Regression Function written by Won Song and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation develops procedures for screening variables, in ultrahigh-dimensional settings, based on their predictive significance. First, we review existing literature on the sure screening procedures for analyzing ultrahigh-dimensional data. Second, we develop a screening procedure by ranking the variables, according to the variance of their respective marginal regression functions (RV-SIS). This is in sharp contrast with existing literature on feature screening, which ranks the variables according to some correlation measures with the response, and hence select variables with no predictive power (e.g., variables that influence aspects of the conditional distribution of the response other than the regression function). The RV-SIS is easy to implement and does not require any model specification for the regression functions (such as linear or other semi-parametric modeling). We show that, under some mild technical conditions, the RV-SIS possesses a sure independence property, which is defined by Fan and Lv (2008). Numerical comparisons suggest that RV-SIS has competitive performance compared to other screening procedure and outperforms them in many different model settings. Third, we develop a test procedure for the hypothesis of a constant regression function, and also a test-based variable screening procedure. We study the asymptotic theory for the variance of the regression function and use it to introduce a new test procedure for testing the significance of a predictor. Using the set of p-values, we introduce a variable screening procedure with a specified desirable false discovery rate by using Benjamini and Hochberg (1995) approach.
Book Synopsis Adequacy Checking for the Variance Function in Nonparametric Regression by : Jia Liang
Download or read book Adequacy Checking for the Variance Function in Nonparametric Regression written by Jia Liang and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Correctly specifying the parametric form of the variance function in regression models can help us make more efficient statistical inferences. Many existing Lack-of-fit testing procedures have already been proposed to decide the proper forms of the variance function, however, most of them are either checking the homoscedasticity, that is, to see if the variance function is a constant, or checking a pre-specified parametric forms of the variance function under the assumption of the mean regression function being known. In this report, we would like to construct some formal testing procedure to check the appropriateness of certain parametric forms for the variance function when the mean regression function is unknown. The report consists of two parts. In the first part, we propose a minimum distance-based test to check the forms of the variance function. The test statistics is a modified L2-distance between a nonparametric estimate and a parametric estimate of the variance function under the null hypothesis. The Nadaraya-Watson kernel regression function estimator is used to estimate the regression function. The large sample properties, including the consistency and asymptotic normality, of the minimum distance estimate for the parameters in the variance function are discussed; the asymptotic distribution of the test statistics under the null hypothesis is established, as well as the consistency of the test and the power under local alternative hypotheses. Simulation studies, comparison studies, as well as some applications to the real data sets, are carried out to evaluate the finite sample performance of the proposed test. In the second part, we proposed a computationally efficient test procedure for checking the parametric forms of the variance function. The test is based on an empirical smoothing of the fitted residuals by replacing the mean regression function with the Nadaraya-Watson estimator and a pre-obtained root-n consistent estimate of the parameter in the variance function. By multiplying the kernel density estimate at each individual sample points to the fitted residual, we successfully remove the constraint of compact support for design variables assumed in some existing work. Large sample properties of the proposed test under the null hypothesis is discussed alongside with consistency of the test and the power under local alternatives. Finally, some simulation studies are carried out showing the performance of the test under finite population.
Book Synopsis Testing for No Effect when Estimating a Smooth Function by Nonparametric Regression by : Jonathan Alan Raz
Download or read book Testing for No Effect when Estimating a Smooth Function by Nonparametric Regression written by Jonathan Alan Raz and published by . This book was released on 1988 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Tests for Independence in Nonparametric Regression by : Johannes Hubertus Jacob Einmahl
Download or read book Tests for Independence in Nonparametric Regression written by Johannes Hubertus Jacob Einmahl and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonparametric Tests for Complete Data by : Vilijandas Bagdonavicius
Download or read book Nonparametric Tests for Complete Data written by Vilijandas Bagdonavicius and published by John Wiley & Sons. This book was released on 2013-02-04 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concerns testing hypotheses in non-parametric models. Classical non-parametric tests (goodness-of-fit, homogeneity, randomness, independence) of complete data are considered. Most of the test results are proved and real applications are illustrated using examples. Theories and exercises are provided. The incorrect use of many tests applying most statistical software is highlighted and discussed.
Book Synopsis A Contingency Table Approach to Nonparametric Testing by : J.C.W. Rayner
Download or read book A Contingency Table Approach to Nonparametric Testing written by J.C.W. Rayner and published by CRC Press. This book was released on 2000-12-07 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most texts on nonparametric techniques concentrate on location and linear-linear (correlation) tests, with less emphasis on dispersion effects and linear-quadratic tests. Tests for higher moment effects are virtually ignored. Using a fresh approach, A Contingency Table Approach to Nonparametric Testing unifies and extends the popular, standard test
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 Nonparametric Lack-of-fit Tests in Presence of Heteroscedastic Variances by : Mohammed Mahmoud Gharaibeh
Download or read book Nonparametric Lack-of-fit Tests in Presence of Heteroscedastic Variances written by Mohammed Mahmoud Gharaibeh and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: It is essential to test the adequacy of a specified regression model in order to have correct statistical inferences. In addition, ignoring the presence of heteroscedastic errors of regression models will lead to unreliable and misleading inferences. In this dissertation, we consider nonparametric lack-of-fit tests in presence of heteroscedastic variances. First, we consider testing the constant regression null hypothesis based on a test statistic constructed using a k-nearest neighbor augmentation. Then a lack-of-fit test of nonlinear regression null hypothesis is proposed. For both cases, the asymptotic distribution of the test statistic is derived under the null and local alternatives for the case of using fixed number of nearest neighbors. Numerical studies and real data analyses are presented to evaluate the performance of the proposed tests. Advantages of our tests compared to classical methods include: (1) The response variable can be discrete or continuous and can have variations depend on the predictor. This allows our tests to have broad applicability to data from many practical fields. (2) Using fixed number of k-nearest neighbors avoids slow convergence problem which is a common drawback of nonparametric methods that often leads to low power for moderate sample sizes. (3) We obtained the parametric standardizing rate for our test statistics, which give more power than smoothing based nonparametric methods for intermediate sample sizes. The numerical simulation studies show that our tests are powerful and have noticeably better performance than some well known tests when the data were generated from high frequency alternatives. Based on the idea of the Least Squares Cross-Validation (LSCV) procedure of Hardle and Mammen (1993), we also proposed a method to estimate the number of nearest neighbors for data augmentation that works with both continuous and discrete response variable.
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:
Book Synopsis Variance function estimation in nonparametric regression model by :
Download or read book Variance function estimation in nonparametric regression model written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Variance function estimation in nonparametric regression model.
Book Synopsis Nonparametric Tests for Regression Models by : Shishirkumar Shreedhar Jogdeo
Download or read book Nonparametric Tests for Regression Models written by Shishirkumar Shreedhar Jogdeo and published by . This book was released on 1962 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Nonparametric Analysis of Plot Basal Area Growth Using Tree Based Models by : Gary L. Gadbury
Download or read book A Nonparametric Analysis of Plot Basal Area Growth Using Tree Based Models written by Gary L. Gadbury and published by . This book was released on 1998 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tree based statistical models can be used to investigate data structure and predict future observations. We used nonparametric and nonlinear models to reexamine the data sets on tree growth used by Bechtold et al. (1991) and Ruark et al. (1991). The growth data were collected by Forest Inventory and Analysis (FIA) teams from 1962 to 1972 (4th cycle) and 1972 to 1982 (5th cycle). We used tree based models to group observations into clusters that were specified by covariate values. Next, we performed a permutation test on the grouped data to test for a change in tree growth rates from the 4th cycle to the 5th cycle. Our techniques differed from those used by Bechtold et al. (1991) and Ruark et al. (1991). The data was not assumed to follow any parametric distribution, the relation between response and covariates was not assumed to be linear, and the test for a change in tree growth did not require any parametric assumptions. The methodology presented here is general and applicable to other situations where the significance of a specific covariate is in question. Despite these relaxed constraints of analysis, our results generally agreed with those of Bechtold et al. and Ruark et al.
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 1997-07-31 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 A New Test for the Parametric Form of the Variance Function in Nonparametric Regression by : Holger Dette
Download or read book A New Test for the Parametric Form of the Variance Function in Nonparametric Regression written by Holger Dette and published by . This book was released on 2005 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Parasiticide Screening by : Alan A. Marchiondo
Download or read book Parasiticide Screening written by Alan A. Marchiondo and published by Academic Press. This book was released on 2019-06-08 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parasiticide Discovery: In Vitro and In Vivo Tests with Relevant Parasite Rearing and Host Infection/Infestation Methods, Volume Two presents valuable screening methods that have led to the discovery of the majority of parasiticides commercialized in the animal health industry. As much of the knowledge of parasiticide discovery methods is being lost in the animal health industry as seasoned parasitologists retire, this book serves to preserve valuable methods that have led to the discovery of the majority of parasiticides commercialized in animal health, also giving insights into the in vitro and in vivo methods used to identify the parasiticide activity of compounds. Addresses current issues of resistance, along with combination uses for resistant parasites Presents useful, authoritative information (chemical, pharmaceutical, clinical, etc.) for the pyrantel family of compounds Includes a discussion on screening methods in combination therapies Provides cutting-edge material for an evolving area of scientific discussion Includes in vitro and in vivo screens and parasite maintenance and culture methods
Book Synopsis A Simple Test for the Parametric Form of the Variance Function in Nonparametric Regression by : Holger Dette
Download or read book A Simple Test for the Parametric Form of the Variance Function in Nonparametric Regression written by Holger Dette and published by . This book was released on 2006 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1982 with total page 1282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
