Estimation of the Mean Positively Skewed Distributions,

Abstract

We consider estimating the mean of a positively skewed distribution. It has been noted that in random samples the sample mean has a large probability of falling below the mean of the distribution, because of such skewness. Various ad hoc procedures have been proposed to correct this low coverage of the mean in order to estimate conservatively longterm exposure to contaminated soils at toxic waste sites. We propose a direct estimate of the mean based on a penalized empirical loss function. This loss function is made up of a squared error loss plus a penalty for each observation that falls above the estimate. The resulting minimum risk estimate, called the penalized mean, is derived iteratively and shown to be biased in favor of greater coverage.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADP007194

Entities

People

  • Ling Chen
  • Robert W. Jernigan

Organizations

  • Florida International University

Tags

DTIC Thesaurus Topics

  • Computer Science
  • Data Science
  • Engineering
  • Information Science
  • Mathematical Analysis
  • Mathematics
  • Network Science
  • Observation
  • Probability
  • Skewness
  • Statistical Samples
  • Statistics
  • Theoretical Computer Science

Fields of Study

  • Mathematics

Readers

  • Agricultural Chemistry/Soil Science
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms