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Robust empirical likelihood for time series
- Source :
- Journal of Time Series Analysis. 42:4-18
- Publication Year :
- 2020
- Publisher :
- Wiley, 2020.
-
Abstract
- This paper introduces a robust frequency domain empirical likelihood inference procedure for the parametric component in the spectral densities of stationary processes. We construct the empirical likelihood function by using a new spectral estimating function to achieve robustness against contamination in the spectral density. Simulation studies demonstrate the good performance of the proposed robust frequency domain empirical likelihood method, which produces more accurate confidence regions than the ordinary empirical likelihood counterpart.
- Subjects :
- Statistics and Probability
Applied Mathematics
05 social sciences
Inference
Spectral density
01 natural sciences
010104 statistics & probability
Empirical likelihood
Robustness (computer science)
Frequency domain
0502 economics and business
Periodogram
0101 mathematics
Statistics, Probability and Uncertainty
Algorithm
050205 econometrics
Mathematics
Parametric statistics
Subjects
Details
- ISSN :
- 14679892 and 01439782
- Volume :
- 42
- Database :
- OpenAIRE
- Journal :
- Journal of Time Series Analysis
- Accession number :
- edsair.doi...........994e00d26c14f8e639741e239955f062