A Smooth Nonparametric Quantile Estimator from Right-Censored Data.

Abstract

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)

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1987
Accession Number
ADA186180

Entities

People

  • L. A. Thombs
  • William J. Padgett

Organizations

  • University of South Carolina

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Bandwidth
  • Computational Science
  • Consistency
  • Data Science
  • Distribution Functions
  • Estimators
  • Information Science
  • Mathematics
  • Normality
  • Probability
  • Random Variables
  • Simulations
  • South Carolina
  • Statistical Algorithms
  • Statistics
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Statistical inference.