ARFIMA processes and outliers: a weighted likelihood approach

DOI10.1080/02664760903093609OpenAlexW2045180021MaRDI QIDQ5123639

Luisa Bisaglia, Claudio Agostinelli

Publication date: 29 September 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760903093609

zbMATH Keywords

outliersrobust estimationweighted likelihoodARFIMA processes

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (3)

Robust bootstrap prediction intervals for univariate and multivariate autoregressive time series models ⋮ Forecasting functional time series using weighted likelihood methodology ⋮ Robust Two-Step Wavelet-Based Inference for Time Series Models

Uses Software

• R
• longmemo

Cites Work

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• Time series: theory and methods.
• Efficiency versus robustness: The case for minimum Hellinger distance and related methods
• Robust and consistent estimates of autoregressive-moving average parameters
• Fractional differencing
• AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
• Weighted Likelihood Equations with Bootstrap Root Search
• On a class of M-estimators for Gaussian long-memory models
• Robust Statistics

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