A Comparison of Least Squares and Least Absolute Deviation Regression Models for Estimating Weibull Parameters

Kenneth D. Lawrence; Douglas R. Shier

doi:10.1080/03610919808813515a

A Comparison of Least Squares and Least Absolute Deviation Regression Models for Estimating Weibull Parameters

Kenneth D. Lawrence, Douglas R. Shier

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

7 Scopus citations

Abstract

This paper studies alternative methods for simple estimation of the parameters of a Weibull distribution. Results from an extensive series of simulation experiments indicate that L1 estimation can provide a useful alternative to L2 estimation over a range of sample sizes and parameter values. Different methods for approximating the cumulative Weibull distribution have also been investigated.

Original language	English (US)
Pages (from-to)	315-326
Number of pages	12
Journal	Communications in Statistics - Simulation and Computation
Volume	10
Issue number	3
DOIs	https://doi.org/10.1080/03610919808813515a
State	Published - Jan 1 1981
Externally published	Yes

All Science Journal Classification (ASJC) codes

Statistics and Probability
Modeling and Simulation

Keywords

Weibull
least absolute deviation
least squares
regression
robust

Access to Document

10.1080/03610919808813515a

Cite this

@article{f6c45858356e46399a7b473759c5aa05,

title = "A Comparison of Least Squares and Least Absolute Deviation Regression Models for Estimating Weibull Parameters",

abstract = "This paper studies alternative methods for simple estimation of the parameters of a Weibull distribution. Results from an extensive series of simulation experiments indicate that L1 estimation can provide a useful alternative to L2 estimation over a range of sample sizes and parameter values. Different methods for approximating the cumulative Weibull distribution have also been investigated.",

keywords = "Weibull, least absolute deviation, least squares, regression, robust",

author = "Lawrence, \{Kenneth D.\} and Shier, \{Douglas R.\}",

year = "1981",

month = jan,

day = "1",

doi = "10.1080/03610919808813515a",

language = "English (US)",

volume = "10",

pages = "315--326",

journal = "Communications in Statistics - Simulation and Computation",

issn = "0361-0918",

publisher = "Taylor and Francis Ltd.",

number = "3",

}

TY - JOUR

T1 - A Comparison of Least Squares and Least Absolute Deviation Regression Models for Estimating Weibull Parameters

AU - Lawrence, Kenneth D.

AU - Shier, Douglas R.

PY - 1981/1/1

Y1 - 1981/1/1

N2 - This paper studies alternative methods for simple estimation of the parameters of a Weibull distribution. Results from an extensive series of simulation experiments indicate that L1 estimation can provide a useful alternative to L2 estimation over a range of sample sizes and parameter values. Different methods for approximating the cumulative Weibull distribution have also been investigated.

AB - This paper studies alternative methods for simple estimation of the parameters of a Weibull distribution. Results from an extensive series of simulation experiments indicate that L1 estimation can provide a useful alternative to L2 estimation over a range of sample sizes and parameter values. Different methods for approximating the cumulative Weibull distribution have also been investigated.

KW - Weibull

KW - least absolute deviation

KW - least squares

KW - regression

KW - robust

UR - https://www.scopus.com/pages/publications/12344313963

UR - https://www.scopus.com/inward/citedby.url?scp=12344313963&partnerID=8YFLogxK

U2 - 10.1080/03610919808813515a

DO - 10.1080/03610919808813515a

M3 - Article

AN - SCOPUS:12344313963

SN - 0361-0918

VL - 10

SP - 315

EP - 326

JO - Communications in Statistics - Simulation and Computation

JF - Communications in Statistics - Simulation and Computation

IS - 3

ER -

A Comparison of Least Squares and Least Absolute Deviation Regression Models for Estimating Weibull Parameters

Abstract

All Science Journal Classification (ASJC) codes

Keywords

Access to Document

Other files and links

Fingerprint

Cite this