Download or read book PMC optimal Nonparametric Quantile Estimator written by Ryszard Zieliński (matematyk) and published by . This book was released on 2000 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book PMC optimal Nonparametric Quantile Estimator written by Ryszard Zieliński and published by . This book was released on 2000 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Projecting Statistical Functionals written by Tomasz Rychlik and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a method of establishing explicit solutions to classical problems of calculating the best lower and upper mean-variance bounds. The following families of distributions are taken into account: arbitrary, symmetric, symmetric unimodal, and U-shaped. The book is addressed to students, researchers, and practitioners in statistics and applied probability. Most of the results are recent, and a significant part of them has not been published yet. Numerous open problems are stated in the text.

Download or read book Introduction to Nonparametric Estimation written by Alexandre B. Tsybakov and published by Springer Science & Business Media. This book was released on 2008-10-22 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.

Download or read book Applicationes Mathematicae written by and published by . This book was released on 2005 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Nonparametric Quantile Estimator Computation written by W. J. Padgett and published by . This book was released on 1986 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: Right-censored data arise very naturally in life testing and reliability studies. For such data, it is important to be able to obtain good nonparametric estimates of various characteristics of the unknown lifetime distribution. This report concerns the computational procedure for a kernel-type nonparametric estimator of the quantile function of the lifetimne distribution from right-censored data. This estimator was suggested by Padgett (1986), extending the complete sample results of Yang (1985). The large sample properties of the estimator, such as asymptotic normality and mean square convergence, were studied by Lio, Padgett and Yu (1986) and by Lio and Padgett (1985). In this report, a procedure for calculation of the kernel-type quantile estimate from right-censored data is described, and a listing of a computer program in FORTRAN code is provided.

Download or read book Nonparametric Estimation of Conditional Quantile Function written by Ashis Kumar Gangopadhyay and published by . This book was released on 1987 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mathematical Reviews written by and published by . This book was released on 2002 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Smooth Nonparametric Quantile Estimation Under Censoring Simulations and Bootstrap Methods written by W. J. Padgett and published by . This book was released on 1986 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objectives of this paper are two-fold. One is to report results of extensive Monte Carlo simulations which demonstrate the behavior of the mean squared error of the kernel estimator with respect to bandwidth. These simulations provide a method of choosing an optimal bandwidth when the form of the lifetime and censoring distributions are known. Also, they compare the kernel-type estimator with the product-limit qauntile estimator. Five commonly used parametric lifetime distributions, two censoring mechanisms, and four different kernel functions are considered in this study, which is an extension of the brief simulations for exponential distributions reported by Padgett (1986). The second objective is to present a nonparametric method for bandwidth selection based on the bootstrap for right-censored data. This data-based procedure used the bootstrap to estimate mean squared error, and is both an extension and modification of the methods proposed by Padgett. Bandwidth selection using the bootstrap is important for small and moderately large samples since no exact expressions exist for the mean squared error of the kernel-type quantile estimator.

Download or read book Nonparametric Quantile Estimation for Dependent Data written by Dana Florea Draghicescu and published by . This book was released on 2002 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Simulation Study of Some Nonparametric Quantile Estimators Under Censoring written by Michelle Elaine Skelton and published by . This book was released on 1989 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book 2 step Estimation of Semiparametric and Nonparametric Quantile Regression Models written by Shakeeb Khan and published by . This book was released on 1997 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Optimal Nonparametric Estimation for Semimartingales written by Aerambamoorthy Thavaneswaran and published by . This book was released on 1987 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Smooth Nonparametric Quantile Estimation from Right censored Data written by Yuhlong Lio and published by . This book was released on 1987 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Simulation Comparison of Parametric and Nonparametric Estimators of Quantiles from Right Censored Data written by Shyamalee Kumary Serasinghe and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantiles are useful in describing distributions of component lifetimes. Data, consisting of the lifetimes of sample units, used to estimate quantiles are often censored. Right censoring, the setting investigated here, occurs, for example, when some test units may still be functioning when the experiment is terminated. This study investigated and compared the performance of parametric and nonparametric estimators of quantiles from right censored data generated from Weibull and Lognormal distributions, models which are commonly used in analyzing lifetime data. Parametric quantile estimators based on these assumed models were compared via simulation to each other and to quantile estimators obtained from the nonparametric Kaplan- Meier Estimator of the survival function. Various combinations of quantiles, censoring proportion, sample size, and distributions were considered. Our simulation show that the larger the sample size and the lower the censoring rate the better the performance of the estimates of the 5th percentile of Weibull data. The lognormal data are very sensitive to the censoring rate and we observed that for higher censoring rates the incorrect parametric estimates perform the best. If you do not know the underlying distribution of the data, it is risky to use parametric estimates of quantiles close to one. A limitation in using the nonparametric estimator of large quantiles is their instability when the censoring rate is high and the largest observations are censored. Key Words: Quantiles, Right Censoring, Kaplan-Meier estimator.

Download or read book A Smooth Nonparametric Quantile Estimator from Right Censored Data written by W. J. Padgett and published by . This book was released on 1987 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on randomly right-censored data, a smooth nonparametric estimator of the quantile function of the lifetime distribution is studied. The estimator is defined to be the solution x sub n (p) to F sub n (p)) = O, where F sub n is the distribution function corresponding to a kernel estimator of the lifetime density. The strong consistency and asymptotic normality of x sub n (p) are shown. Some simulation results comparing this estimator with the product of the bandwidth required for computing F sub n is investigated using bootstrap methods. Illustrative examples are given. (Author).

Download or read book Nonparametric Estimation of Quantiles and of Density Functions Under Censoring Discrete Failure Models and Multiple Comparisons written by W. J. Padgett and published by . This book was released on 1985 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: Major results have been obtained in the areas of nonparametric estimation of quantiles and of density functions under censoring, discrete failure models, and multiple comparisons. In particular, smooth nonparametric estimators of quantile functions from censored data were developed which give better estimates of percentiles of the lifetime distribution than the usual product-limit quantile function. Also, smooth density estimators from censored data were investigated using maximum penalized likelihood procedures. Several parametric models were proposed for the case of discrete failure data. These models provide a better fit to such data than some previously used discrete models. Finally, new methods of constructing simultaneous confidence intervals for pairwise differences of means of normal populations were developed, and the problem of selecting an asymptotically optimal design for comparing several new treatments with a control was solved. Work is continuing on the study of properties of kernel type quantile function estimators and development of goodness-of-fit tests for the model assumptions in accelerated life testing. Keywords: Nonparametric quantile estimation; Density estimation; Right-censored data; Discrete failure models; Multiple comparisons; Accelerated life testing.