.png){kind=icon}
.png){kind=icon}
Return
Threshold models in time series analysis-Some reflections
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jeconom.2015.03.039.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, I reflect on the developments of the threshold model in time series analysis since its birth in 1978, with particular reference to econometrics. (C) 2015 Elsevier B.V. All rights reserved.
Keywords:
All-step-ahead prediction
Asymmetry
Bayesian decision
Business cycle
Catastrophe
Conditionally heteroscedastic autoregressive models with thresholds
GARCH model
Hidden Markov chain
Hysteresis
Jump resonance
Markov switching model
Mis-specified model
Mixture of distributions
Non-likelihood approach
Nonlinear unit root
Non-stationarity
Open-loop system
Panel threshold model
Positive-valued time series
Smooth threshold autoregressive models
Splines
Stochastic volatility
Structural breaks
Threshold autoregressive models
Threshold moving average models
Threshold principle
Threshold unit root
Volatility
Wrong model
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4
Papers:
5.2K
Citations:
3.0W
Organization
No organization information available