TY - JOUR
T1 - An adaptive estimator of location based on the t-family
AU - Hawkins, D. L.
AU - Lakshminarayan, C. K.
PY - 1994/1/1
Y1 - 1994/1/1
N2 - For estimating the location of a continuous symmetric distribution, we consider the maximum likelihood estimate of location in a location-scale-tailweight family based on the t-distributions. The idea is to obtain an asymptotically efficient estimator of location within a parametric family large enough to contain members close to the normal tailweight, as well as members with heavy tails. This is the “partially adaptive” idea of Bickel (1982). Ve present Monte Carlo results comparing this estimator to several competitors, particularly with one due to Hogg which motivated our idea.
AB - For estimating the location of a continuous symmetric distribution, we consider the maximum likelihood estimate of location in a location-scale-tailweight family based on the t-distributions. The idea is to obtain an asymptotically efficient estimator of location within a parametric family large enough to contain members close to the normal tailweight, as well as members with heavy tails. This is the “partially adaptive” idea of Bickel (1982). Ve present Monte Carlo results comparing this estimator to several competitors, particularly with one due to Hogg which motivated our idea.
KW - maximum likelihood
KW - partially adaptive
KW - symmetric distributions
KW - tailweight
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U2 - 10.1080/03610929408831284
DO - 10.1080/03610929408831284
M3 - Article
AN - SCOPUS:84963474904
SN - 0361-0926
VL - 23
SP - 747
EP - 761
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 3
ER -