On the Consistency of Least Squares Estimator in Models Sampled at Random Times Driven by Long Memory Noise: The Jittered Case

DOI10.5705/ss.202020.0323OpenAlexW4200326225MaRDI QIDQ6039877

Natalia Bahamonde, Tania Roa, Héctor Araya, Lisandro J. Fermín, Soledad Torres

Publication date: 23 May 2023

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.202020.0323

zbMATH Keywords

least squares estimatorregression modelrandom timeslong-memory noise

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Finite sample performance of density estimators from unequally spaced data
• Kernel estimation of the regression function with random sampling times
• Random discretization of stationary continuous time processes
• Analysis of Variations for Self-similar Processes
• A Non-Parametric Estimator of the Spectral Density of a Continuous-Time Gaussian Process Observed at Random Times
• Probability density estimation from sampled data
• Area Estimation by Point-Counting Techniques
• Analysis of the Rosenblatt process
• Likelihood‐based Analysis of a Class of Generalized Long‐Memory Time Series Models
• Fractional Brownian Motions, Fractional Noises and Applications
• ON THE CONSISTENCY OF THE LEAST SQUARES ESTIMATOR IN MODELS SAMPLED AT RANDOM TIMES DRIVEN BY LONG MEMORY NOISE: THE RENEWAL CASE
• Limit distribution of the least square estimator with observations sampled at random times driven by standard Brownian motion

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