Estimating a Distribution Function When New is Better Than Used.

Abstract

The problem we study in this paper is the estimation of the distribution function F under the assumption that F belongs to the class of NBU distributions. Without the NBU restriction, the empirical distribution function F(n) converges to F in several senses and at the best possible rate. However, F(n) need not to be NBU, and, in fact, it is not difficult to show that P(f(n) is NBU) going to 0 when sampling from some NBU distributions (for example, the exponential distribution). Our goal here is to construct a sequence (F(n)) of NBU distributions which achieve the same asymptotic optimality as the sequence (F(n)).

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1980
Accession Number
ADA093150

Entities

People

  • Francisco J. Samaniego
  • Russell A. Boyles

Organizations

  • University of California, Davis

Tags

DTIC Thesaurus Topics

  • Computations
  • Convergence
  • Data Science
  • Distribution Functions
  • Estimators
  • Inequalities
  • Information Science
  • Order Statistics
  • Probability
  • Random Variables
  • Reliability
  • Sampling
  • Sequences
  • Statistical Inference
  • Statistical Samples
  • Statistical Sampling
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Statistical inference.