TY - JOUR

T1 - Two-Step Estimation in a Heteroscedastic Linear Regression Model

AU - Linke, Y. Y.

PY - 2018/5/1

Y1 - 2018/5/1

N2 - We study the problem of estimating a parameter in some heteroscedastic linear regression model in the case where the regressors consist of all order statistics based on the sample of identically distributed not necessarily independent observations with finite second moment. It is assumed that the random errors depend on the parameter and distributions of the corresponding regressors. We propose a two-step procedure for finding explicit asymptotically normal estimators.

AB - We study the problem of estimating a parameter in some heteroscedastic linear regression model in the case where the regressors consist of all order statistics based on the sample of identically distributed not necessarily independent observations with finite second moment. It is assumed that the random errors depend on the parameter and distributions of the corresponding regressors. We propose a two-step procedure for finding explicit asymptotically normal estimators.

UR - http://www.scopus.com/inward/record.url?scp=85045947229&partnerID=8YFLogxK

U2 - 10.1007/s10958-018-3816-y

DO - 10.1007/s10958-018-3816-y

M3 - Article

AN - SCOPUS:85045947229

VL - 231

SP - 206

EP - 217

JO - Journal of Mathematical Sciences (United States)

JF - Journal of Mathematical Sciences (United States)

SN - 1072-3374

IS - 2

ER -