TY - JOUR
T1 - Asymptotic normality of pseudo-LS estimator for partly linear autoregression models
AU - Gao, Jiti
AU - Liang, Hua
PY - 1995/1/1
Y1 - 1995/1/1
N2 - Consider the model Yt = βYt-1 + g(Yt-2) + εt for t ≥ 3. Here g is an unknown function, β is an unknown parameter to be estimated and εt are i.i.d. random error with zero 0 and variance σ2 and εt are independent of Ys for all t ≥ 3 and s = 1, 2. A class of asymptotically normal estimators of β are directly obtained based on piecewise polynomial approximator g ̂T(·) of g and the model Yt = βYt-1 + g ̂T(Yt-2) + εt. The asymptotic normality of pseudo-LS (PLS) estimator β ̌T of β and an estimator σ ̌T
2 of σ2 are investigated.
AB - Consider the model Yt = βYt-1 + g(Yt-2) + εt for t ≥ 3. Here g is an unknown function, β is an unknown parameter to be estimated and εt are i.i.d. random error with zero 0 and variance σ2 and εt are independent of Ys for all t ≥ 3 and s = 1, 2. A class of asymptotically normal estimators of β are directly obtained based on piecewise polynomial approximator g ̂T(·) of g and the model Yt = βYt-1 + g ̂T(Yt-2) + εt. The asymptotic normality of pseudo-LS (PLS) estimator β ̌T of β and an estimator σ ̌T
2 of σ2 are investigated.
KW - Asymptotic theory
KW - Non-linear time series model
KW - Piecewise polynomial
UR - http://www.scopus.com/inward/record.url?scp=0003035313&partnerID=8YFLogxK
U2 - 10.1016/0167-7152(94)00091-L
DO - 10.1016/0167-7152(94)00091-L
M3 - Article
AN - SCOPUS:0003035313
SN - 0167-7152
VL - 23
SP - 27
EP - 34
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
IS - 1
ER -