| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 5776500 | Journal of Computational and Applied Mathematics | 2017 | 15 Pages |
Abstract
In this paper three formulas for recovering the conditional mean and conditional variance based on product moments are proposed. The upper bounds for the uniform rate of approximations of regression and derivatives of some moment-determinate function are derived. Two cases where the support of underlying functions is bounded and unbounded from above are studied. Based on the proposed approximations, novel nonparametric estimates of the distribution function and its density in multiplicative-censoring model are constructed. Simulation study justifies the consistency of the estimates.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Robert M. Mnatsakanov, Broti Garai,