Research output: Contribution to journal › Article › peer-review
Asymptotic normality of one-step M-estimators based on non-identically distributed observations. / Linke, Yuliana Yu.
In: Statistics and Probability Letters, Vol. 129, 01.10.2017, p. 216-221.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Asymptotic normality of one-step M-estimators based on non-identically distributed observations
AU - Linke, Yuliana Yu
PY - 2017/10/1
Y1 - 2017/10/1
N2 - We find general conditions for asymptotic normality of two types of one-step M-estimators based on independent not necessarily identically distributed observations. As an application, we consider some examples of one-step approximation of quasi-likelihood estimators in nonlinear regression.
AB - We find general conditions for asymptotic normality of two types of one-step M-estimators based on independent not necessarily identically distributed observations. As an application, we consider some examples of one-step approximation of quasi-likelihood estimators in nonlinear regression.
KW - Initial estimator
KW - Nonlinear regression
KW - One-step M-estimator
UR - http://www.scopus.com/inward/record.url?scp=85020986354&partnerID=8YFLogxK
U2 - 10.1016/j.spl.2017.05.020
DO - 10.1016/j.spl.2017.05.020
M3 - Article
AN - SCOPUS:85020986354
VL - 129
SP - 216
EP - 221
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
SN - 0167-7152
ER -
ID: 9048672