Tarima, Sergey, and Pavlov, Dmitri. "Using auxiliary information in statistical function estimation." ESAIM: Probability and Statistics 10 (2005): 11-23. <http://eudml.org/doc/104344>.
@article{Tarima2005,
abstract = {
In many practical situations sample sizes are not sufficiently large
and estimators based on such samples may not be satisfactory in
terms of their variances. At the same time it is not unusual that
some auxiliary information about the parameters of interest is
available. This paper considers a method of using auxiliary
information for improving properties of the estimators based on a
current sample only. In particular, it is assumed that the
information is available as a number of estimates based on samples
obtained from some other mutually independent data sources. This
method uses the fact that there is a correlation effect between
estimators based on the current sample and auxiliary information
from other sources. If variance covariance matrices of vectors of
estimators used in the estimating procedure are known, this method
produces more efficient estimates in terms of their variances
compared to the estimates based on the current sample only. If these
variance-covariance matrices are not known, their consistent
estimates can be used as well such that the large sample properties
of the method remain unchangeable. This approach allows to improve
statistical properties of many standard estimators such as an
empirical cumulative distribution function, empirical characteristic
function, and Nelson-Aalen cumulative hazard estimator.
},
author = {Tarima, Sergey, Pavlov, Dmitri},
journal = {ESAIM: Probability and Statistics},
keywords = {Auxiliary information; multiple data sources; partially
grouped samples; convergence rates.; partially grouped samples; convergence rates},
language = {eng},
month = {12},
pages = {11-23},
publisher = {EDP Sciences},
title = {Using auxiliary information in statistical function estimation},
url = {http://eudml.org/doc/104344},
volume = {10},
year = {2005},
}
TY - JOUR
AU - Tarima, Sergey
AU - Pavlov, Dmitri
TI - Using auxiliary information in statistical function estimation
JO - ESAIM: Probability and Statistics
DA - 2005/12//
PB - EDP Sciences
VL - 10
SP - 11
EP - 23
AB -
In many practical situations sample sizes are not sufficiently large
and estimators based on such samples may not be satisfactory in
terms of their variances. At the same time it is not unusual that
some auxiliary information about the parameters of interest is
available. This paper considers a method of using auxiliary
information for improving properties of the estimators based on a
current sample only. In particular, it is assumed that the
information is available as a number of estimates based on samples
obtained from some other mutually independent data sources. This
method uses the fact that there is a correlation effect between
estimators based on the current sample and auxiliary information
from other sources. If variance covariance matrices of vectors of
estimators used in the estimating procedure are known, this method
produces more efficient estimates in terms of their variances
compared to the estimates based on the current sample only. If these
variance-covariance matrices are not known, their consistent
estimates can be used as well such that the large sample properties
of the method remain unchangeable. This approach allows to improve
statistical properties of many standard estimators such as an
empirical cumulative distribution function, empirical characteristic
function, and Nelson-Aalen cumulative hazard estimator.
LA - eng
KW - Auxiliary information; multiple data sources; partially
grouped samples; convergence rates.; partially grouped samples; convergence rates
UR - http://eudml.org/doc/104344
ER -
