On the asymptotic properties of a feasible estimator of the continuous time long memory parameter

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On the asymptotic properties of a feasible estimator of the continuous time long memory parameter. / Ercolani, Joanne.

In: Journal of Time Series Analysis, Vol. 32, No. 5, 01.09.2011, p. 512-517.

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@article{676d75e9da1c408fb9ff4fd833f5af4d,
title = "On the asymptotic properties of a feasible estimator of the continuous time long memory parameter",
abstract = "This article considers a fractional noise model in continuous time and examines the asymptotic properties of a feasible frequency domain maximum likelihood estimator of the long memory parameter. The feasible estimator is one that maximizes an approximation to the likelihood function (the approximation arises from the fact that the spectral density function involves the finite truncation of an infinite summation). It is of interest therefore to explore the conditions required of this approximation to ensure the consistency and asymptotic normality of this estimator.",
keywords = "long memory processes, Continuous time models",
author = "Joanne Ercolani",
year = "2011",
month = sep,
day = "1",
doi = "10.1111/j.1467-9892.2010.00709.x",
language = "English",
volume = "32",
pages = "512--517",
journal = "Journal of Time Series Analysis",
issn = "0143-9782",
publisher = "Wiley",
number = "5",

}

RIS

TY - JOUR

T1 - On the asymptotic properties of a feasible estimator of the continuous time long memory parameter

AU - Ercolani, Joanne

PY - 2011/9/1

Y1 - 2011/9/1

N2 - This article considers a fractional noise model in continuous time and examines the asymptotic properties of a feasible frequency domain maximum likelihood estimator of the long memory parameter. The feasible estimator is one that maximizes an approximation to the likelihood function (the approximation arises from the fact that the spectral density function involves the finite truncation of an infinite summation). It is of interest therefore to explore the conditions required of this approximation to ensure the consistency and asymptotic normality of this estimator.

AB - This article considers a fractional noise model in continuous time and examines the asymptotic properties of a feasible frequency domain maximum likelihood estimator of the long memory parameter. The feasible estimator is one that maximizes an approximation to the likelihood function (the approximation arises from the fact that the spectral density function involves the finite truncation of an infinite summation). It is of interest therefore to explore the conditions required of this approximation to ensure the consistency and asymptotic normality of this estimator.

KW - long memory processes

KW - Continuous time models

U2 - 10.1111/j.1467-9892.2010.00709.x

DO - 10.1111/j.1467-9892.2010.00709.x

M3 - Article

VL - 32

SP - 512

EP - 517

JO - Journal of Time Series Analysis

JF - Journal of Time Series Analysis

SN - 0143-9782

IS - 5

ER -