Title

A Comparison Of Maximum-Likelihood And Least-Squares For The Estimation Of A Cumulative Distribution

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

J. Stat. Comput. Simul.

Keywords

Computer Science; Interdisciplinary Applications; Statistics; Probability

Abstract

Monte Carlo methods are used to compare the methods of maximum likelihood and least squares to estimate a cumulative distribution function. When the probabilistic model used is correct or nearly correct, the two methods produce similar results with the MLE usually slightly superior When an incorrect model is used, or when the data is contaminated, the least squares technique often gives substantially superior results.

Journal Title

Journal of Statistical Computation and Simulation

Volume

14

Issue/Number

3-4

Publication Date

1-1-1982

Document Type

Article

Language

English

First Page

229

Last Page

239

WOS Identifier

WOS:A1982NP92900006

ISSN

0094-9655

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