CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
research
Symmetry, regression design, and sampling distributions
Authors
A Chesher
S Peters
Publication date
1 January 1994
Publisher
Doi
Cite
Abstract
When values of regressors are symmetrically disposed, many M-estimators in a wide class of models have a reflection property, namely, that as the signs of the coefficients on regressors are reversed, their estimators' sampling distribution is reflected about the origin. When the coefficients are zero, sign reversal can have no effect. So in this case, the sampling distribution of regression coefficient estimators is symmetric about zero, the estimators are median unbiased and, when moments exist, the estimators are exactly uncorrelated with estimators of other parameters. The result is unusual in that it does not require response variates to have symmetric conditional distributions. It demonstrates the potential importance of covariate design in determining the distributions of estimators, and it is useful in designing and interpreting Monte Carlo experiments. The result is illustrated by a Monte Carlo experiment in which maximum likelihood and symmetrically censored least-squares estimators are calculated for small samples from a censored normal linear regression, Tobit, model. © 1994, Cambridge University Press. All rights reserved
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Supporting member
Explore Bristol Research
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:research-information.bris....
Last time updated on 10/08/2019
UCL Discovery
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:eprints.ucl.ac.uk.OAI2:161...
Last time updated on 12/04/2012