Maximum likelihood estimators for ARMA and ARFIMA models: a Monte Carlo study.

DOI10.1016/S0378-3758(98)00252-3zbMath1045.62528OpenAlexW3122918237WikidataQ126815647 ScholiaQ126815647MaRDI QIDQ1304365

Michael A. Hauser

Publication date: 1999

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(98)00252-3

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10) Monte Carlo methods (65C05)

Related Items (11)

Generalized maximum entropy based identification of graphical ARMA models ⋮ Inference with the Whittle Likelihood: A Tractable Approach Using Estimating Functions ⋮ NF-CECP: a novel approach to distinguish signals with different properties via modified Fisher information measure ⋮ Whittle-type estimation under long memory and nonstationarity ⋮ ASYMPTOTIC THEORY FOR MAXIMUM LIKELIHOOD ESTIMATION OF THE MEMORY PARAMETER IN STATIONARY GAUSSIAN PROCESSES ⋮ Invariance of the first difference in ARFIMA models ⋮ Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration ⋮ The exact maximum likelihood-based test for fractional cointegration: Critical values, power and size ⋮ First-order bias correction for fractionally integrated time series ⋮ Unnamed Item ⋮ A model of fractional cointegration, and tests for cointegration using the bootstrap.

Uses Software

• TRICP

Cites Work

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• Bias in the sample autocorrelations of fractional noise
• Twisted GFSR generators II

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