Empirical likelihood approach toward discriminant analysis for dynamics of stable processes
DOI10.1016/j.stamet.2014.01.004zbMath1486.62237OpenAlexW2043510916MaRDI QIDQ1731205
Publication date: 13 March 2019
Published in: Statistical Methodology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.stamet.2014.01.004
discriminant analysisstable processempirical likelihood ratioclassification statisticsnormalized power transfer functions
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Inference from stochastic processes and spectral analysis (62M15) Stable stochastic processes (60G52)
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Cites Work
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- Discriminant analysis for dynamics of stable processes
- Spectral estimates and stable processes
- Limit theory for moving averages of random variables with regularly varying tail probabilities
- On tail index estimation using dependent data
- A simple general approach to inference about the tail of a distribution
- The integrated periodogram for stable processes
- How to make a Hill plot.
- The maximum of the periodogram for a heavy-tailed sequence.
- Empirical likelihood ratio confidence intervals for a single functional
- Linear Discriminant Functions for Stationary Time Series
- DISCRIMINANT ANALYSIS FOR STATIONARY VECTOR TIME SERIES
- Discriminant analysis for non-gaussian vector stationary processes
- Empirical likelihood confidence regions in time series models
- AN EMPIRICAL LIKELIHOOD APPROACH FOR NON‐GAUSSIAN VECTOR STATIONARY PROCESSES AND ITS APPLICATION TO MINIMUM CONTRAST ESTIMATION
- On the Asymptotic Optimality of Spectral Analysis for Testing Hypotheses About Time Series
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