Nonparametric Maximum Penalized Likelihood Estimation of a Density from Arbitrarily Right-Censored Observations.

Abstract

Based on arbitrarily right-censored observations from a probability density function f deg, the existence and uniqueness of the maximum penalized likelihood estimator (MPLE) of f deg is proven. In particular, the first MPLE of Good and Gaskins of a density defined on (0, infinity) is shown to exist and to be unique under arbitrary right-censorship. Furthermore, the MPLE is in the form of an exponential spline which knots at the observed censored and uncensored data points. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1984
Accession Number
ADA145569

Entities

People

  • A. M. Lubecke
  • William J. Padgett

Organizations

  • University of South Carolina

Tags

DTIC Thesaurus Topics

  • Air Force
  • Censorship
  • Data Science
  • Differential Equations
  • Equations
  • Functional Analysis
  • Hilbert Space
  • Information Science
  • Mathematics
  • Maximum Likelihood Estimation
  • Probability
  • Probability Density Functions
  • South Carolina
  • Statistics
  • Theorems
  • Three Dimensional
  • United States

Fields of Study

  • Mathematics

Readers

  • Statistical inference.