Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Asymptotic uniform linearity of some robust statistics under exponentially subordinated strongly dependent models
AU - Chen, Shijie
AU - Mukherjee, Kanchan
PY - 1999/8/15
Y1 - 1999/8/15
N2 - In this paper, we discuss an asymptotic distributional theory of three broad classes of robust estimators of the regression parameter namely, L-, M- and R-estimators in a linear regression model when the errors are generated by an exponentially subordinated strongly dependent process. The results are obtained as a consequence of an asymptotic uniform Taylor-type expansion of certain randomly weighted empirical processes. The limiting distributions of the estimators are nonnormal and depend on the rst nonzero index of the Laguerre polynomial expansion of a class of indicator functions of the error random variables.
AB - In this paper, we discuss an asymptotic distributional theory of three broad classes of robust estimators of the regression parameter namely, L-, M- and R-estimators in a linear regression model when the errors are generated by an exponentially subordinated strongly dependent process. The results are obtained as a consequence of an asymptotic uniform Taylor-type expansion of certain randomly weighted empirical processes. The limiting distributions of the estimators are nonnormal and depend on the rst nonzero index of the Laguerre polynomial expansion of a class of indicator functions of the error random variables.
KW - Laguerre expansion
KW - L-
KW - M- and R-estimators
KW - Regression quantiles
KW - Weighted empirical processes
U2 - 10.1016/S0167-7152(98)00300-9
DO - 10.1016/S0167-7152(98)00300-9
M3 - Journal article
VL - 44
SP - 137
EP - 146
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
SN - 0167-7152
IS - 2
ER -