منابع مشابه
Nonparametric Renewal Function Estimation and Smoothing by Empirical Data
We consider an estimate of the renewal function (rf) using a limited number of independent observations of the interarrival times for an unknown interarrival-time distribution (itd). The nonparametric estimate is derived from the rf-representation as series of distribution functions (dfs) of consecutive arrival times using a finite summation and approximations of the latter by empirical dfs. Du...
متن کاملNonparametric estimation and consistency for renewal processes
In reliability or medical studies, we may only observe each ongoing renewal process for a certain period of time. When the underlying distribution F is arithmetic, Vardi (Ann. Statist. 10 (1982b), 772-785) developed the RT algorithm for nonparametric estimation. In this paper we extend the study to the nonarithmetic case and show that the choice of an arbitrary constant in the RT algorithm can ...
متن کاملWavelets and Nonparametric Function Estimation
The problem of nonparametric function estimation has received a substantial amount of attention in the statistical literature over the last 15 years. To a very large extent, the literature has described kernel-based convolution smoothing solutions to the problems of probability density estimation and nonlinear regression. Among the subcultures within this literature has been a substantial effor...
متن کاملUnbalanced Haar technique for nonparametric function estimation
The discrete Unbalanced Haar (UH) transform is a decomposition of one-dimensional data with respect to an orthonormal Haar-like basis where jumps in the basis vectors do not necessarily occur in the middle of their support. We introduce a multiscale procedure for estimation in Gaussian noise which consists of three steps: a UH transform, thresholding of the decomposition coefficients, and the i...
متن کاملNonparametric Function Estimation Involving Errors-in-variables
We examine the effect of errors in covariates in rionparametric function estimation. These functions include densities, regressions and conditional quantiles. To estimate these functions, we use the idea of deconvoluting kernels in conjunction with the ordinary kernel methods. We also discuss a new class of function estimators based on local polynomials. oAbbreviated title. Error-in-variable re...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 1986
ISSN: 0090-5364
DOI: 10.1214/aos/1176350163