TY - JOUR
T1 - Strict stationarity of AR(P) processes generated by nonlinear random functions with additive perturbations
AU - Lee, Oesook
N1 - Funding Information:
The author would like to thank anonynlous referees for careful reading. This work was supported by a grant from Korea Ministry of Science and Technology, 1997.
PY - 1999
Y1 - 1999
N2 - Let {Xn} be a generalized autoregressive process of order p defined by Xn = φn(Xn-p, ⋯ , Xn-1) + ηn, where {φn} is a sequence of i.i.d. random maps taking values on H, and {ηn} is a sequence of i.i.d. random variables. Let H be a collection of Borel measurable functions on Rp to R. By considering the associated Markov process, we obtain sufficient conditions for stationarity, (geometric) ergodicity of {Xn}.
AB - Let {Xn} be a generalized autoregressive process of order p defined by Xn = φn(Xn-p, ⋯ , Xn-1) + ηn, where {φn} is a sequence of i.i.d. random maps taking values on H, and {ηn} is a sequence of i.i.d. random variables. Let H be a collection of Borel measurable functions on Rp to R. By considering the associated Markov process, we obtain sufficient conditions for stationarity, (geometric) ergodicity of {Xn}.
KW - Ergodicity
KW - Geometric ergodicity
KW - Markov chain
UR - http://www.scopus.com/inward/record.url?scp=28244480419&partnerID=8YFLogxK
U2 - 10.1080/03610929908832436
DO - 10.1080/03610929908832436
M3 - Article
AN - SCOPUS:28244480419
SN - 0361-0926
VL - 28
SP - 2527
EP - 2537
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 11
ER -