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Strong consistency of the distribution estimator in the nonlinear autoregressive time series
- Source :
- Journal of Multivariate Analysis. 142:41-47
- Publication Year :
- 2015
- Publisher :
- Elsevier BV, 2015.
-
Abstract
- This paper considers the uniform strong consistency of the error cumulative distribution function (CDF) estimator. Under appropriate assumptions, the classical Glivenko-Cantelli Theorem is obtained for the residual based empirical error CDF in the nonlinear autoregressive time series.
- Subjects :
- Computer Science::Machine Learning
Statistics and Probability
Statistics::Theory
Numerical Analysis
Nonlinear autoregressive exogenous model
Stationary process
Cumulative distribution function
Strong consistency
Estimator
SETAR
Autoregressive model
Statistics
Applied mathematics
High Energy Physics::Experiment
Statistics, Probability and Uncertainty
STAR model
Mathematics
Subjects
Details
- ISSN :
- 0047259X
- Volume :
- 142
- Database :
- OpenAIRE
- Journal :
- Journal of Multivariate Analysis
- Accession number :
- edsair.doi...........6ae0fb0c5160dccefc412540fb5fd804
- Full Text :
- https://doi.org/10.1016/j.jmva.2015.07.014