Estimating the Parameters in Regression with Uniformly Distributed Errors

Edna Schechtman; Gideon Schechtman

doi:10.1080/00949658608810965

Estimating the Parameters in Regression with Uniformly Distributed Errors

Edna Schechtman, Gideon Schechtman

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

In this paper we develop maximum likelihood estimators of the intercept and the slope in linear regression where the error term is uniformly distributed. We prove that these estimators are unbiased and we show, theoretically and via simulation, that their variances are in most practical cases smaller than the variances of the corresponding LSE.

Original language	English
Pages (from-to)	269-281
Number of pages	13
Journal	Journal of Statistical Computation and Simulation
Volume	26
Issue number	3-4
DOIs	https://doi.org/10.1080/00949658608810965
State	Published - 1 Dec 1986
Externally published	Yes

ASJC Scopus subject areas

Statistics and Probability
Modeling and Simulation
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1080/00949658608810965

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title = "Estimating the Parameters in Regression with Uniformly Distributed Errors",

abstract = "In this paper we develop maximum likelihood estimators of the intercept and the slope in linear regression where the error term is uniformly distributed. We prove that these estimators are unbiased and we show, theoretically and via simulation, that their variances are in most practical cases smaller than the variances of the corresponding LSE.",

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Estimating the Parameters in Regression with Uniformly Distributed Errors

Abstract

ASJC Scopus subject areas

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