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Estimation of autoregressive models with epsilon-skew-normal innovations
- Source :
- Proceedings of the 22nd European Signal Processing Conference, 22nd European Signal Processing Conference (EUSIPCO 2014), 22nd European Signal Processing Conference (EUSIPCO 2014), Sep 2014, Lisboa, Portugal. ⟨10.1016/j.jmva.2009.02.006⟩
- Publication Year :
- 2009
- Publisher :
- Elsevier BV, 2009.
-
Abstract
- International audience; We consider the problem of modelling asymmetric near-Gaussian correlated signals by autoregressive models with epsilon-skew normal innovations. Moments and maximum likelihood estimators of the parameters are proposed and their limit distributions are derived. Monte Carlo simulation results are analyzed and the model is fitted to a real time series.
- Subjects :
- Statistics and Probability
Skew normal distribution
skewness
maximum likelihood estimation
01 natural sciences
010104 statistics & probability
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
Non-Gaussian time series
0502 economics and business
Econometrics
Applied mathematics
Autoregressive integrated moving average
0101 mathematics
050205 econometrics
Mathematics
Nonlinear autoregressive exogenous model
Numerical Analysis
Index Terms— Non-Gaussian
05 social sciences
Autocorrelation
Skew-normal distribution
Estimator
autoregressive model
SETAR
Autoregressive model
Statistics, Probability and Uncertainty
Autoregression
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
STAR model
Subjects
Details
- ISSN :
- 0047259X
- Volume :
- 100
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- Journal of Multivariate Analysis
- Accession number :
- edsair.doi.dedup.....b3fcb8fa419b60d61f1b91ec69731738
- Full Text :
- https://doi.org/10.1016/j.jmva.2009.02.006