Kernel-Based Density Estimation Using Censored, Truncated or Grouped Data.

Abstract

Censoring, truncation and grouping represent different but related forms of incompleteness. Methods of producing kernel functions on the incomplete observations are proposed. They involve substituting for or averaging over the incomplete observations. Consistency of the procedures in terms of the criterion of integrated mean squared error is established and optimal choice of smoothing parameter is achieved. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1982
Accession Number
ADA116174

Entities

People

  • D. M. Titterington

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Consistency
  • Data Science
  • Data Sets
  • Distribution Functions
  • Information Science
  • Kernel Functions
  • Mathematics
  • Normal Distribution
  • Observation
  • Probability
  • Probability Density Functions
  • Random Variables
  • Statistical Analysis
  • Statistics
  • Truncation
  • United States
  • Universities

Fields of Study

  • Mathematics

Readers

  • Statistical inference.
  • Systems Analysis and Design