Statistical Estimation of Parameters for Binary Conditionally Nonlinear Autoregressive Time Series

2018 ◽  
Vol 27 (2) ◽  
pp. 103-118 ◽  
Author(s):  
Yu. S. Kharin ◽  
V. A. Voloshko ◽  
E. A. Medved
Keyword(s):  
Time Series ◽  
Statistical Estimation ◽  
Estimation Of Parameters ◽  
Autoregressive Time Series ◽  
Nonlinear Autoregressive

Identification of Lags in Nonlinear Autoregressive Time Series Using a Flexible Fuzzy Model

2015 ◽  
Vol 43 (3) ◽  
pp. 641-666 ◽  
Author(s):  
A. Veloz ◽  
R. Salas ◽  
H. Allende-Cid ◽  
H. Allende ◽  
C. Moraga
Keyword(s):  
Time Series ◽  
Fuzzy Model ◽  
Autoregressive Time Series ◽  
Nonlinear Autoregressive

PIGGYBACKING THRESHOLD PROCESSES WITH A FINITE STATE MARKOV CHAIN

2009 ◽  
Vol 09 (02) ◽  
pp. 187-204
Author(s):  
THOMAS R. BOUCHER ◽  
DAREN B. H. CLINE
Keyword(s):  
Time Series ◽  
Markov Chain ◽  
Markov Chains ◽  
State Space ◽  
The State ◽  
General State ◽  
Stationary Distributions ◽  
Autoregressive Time Series ◽  
Finite State ◽  
Nonlinear Autoregressive

The state-space representations of certain nonlinear autoregressive time series are general state Markov chains. The transitions of a general state Markov chain among regions in its state-space can be modeled with the transitions among states of a finite state Markov chain. Stability of the time series is then informed by the stationary distributions of the finite state Markov chain. This approach generalizes some previous results.

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