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Time-analysis of COVID-19 dispersion among health care workers and the general population

open access: yes, 2021
Leme PAF   +11 more
europepmc   +1 more source
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Bayesian Inference for ARFIMA Models

Journal of Time Series Analysis, 2019
This article develops practical methods for Bayesian inference in the autoregressive fractionally integrated moving average (ARFIMA) model using the exact likelihood function, any proper prior distribution, and time series that may have thousands of observations.
Durham, Garland   +3 more
openaire   +2 more sources

Modeling of PMU Data Using ARFIMA Models

2018 Clemson University Power Systems Conference (PSC), 2018
Installing Phasor Measurement Units (PMUs) in the smart grid has played an important role in having more reliable and secure grid. Due to the high sampling rate (50 samples/s), PMU generates massive amount of data compared to the conventional SCADA system.
Laith Shalalfeh   +2 more
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Adaptive ARFIMA models with applications to inflation

Economic Modelling, 2012
Abstract Many previous analyses of inflation have used either long memory or nonlinear time series models. This paper suggests a simple adaptive modification of the basic ARFIMA model, which uses a flexible Fourier form to allow for a time varying intercept.
Morana, C, Baillie, RT
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Bayesian model selection in ARFIMA models

Expert Systems with Applications, 2010
Various model selection criteria such as Akaike information criterion (AIC; Akaike, 1973), Bayesian information criterion (BIC; Akaike, 1979) and Hannan-Quinn criterion (HQC; Hannan, 1980) are used for model specification in autoregressive fractional integrated moving average (ARFIMA) models. Classical model selection criteria require to calculate both
Eǧrïoǧlu, Erol, Günay, Süleyman
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Bayesian analysis of long memory and persistence using ARFIMA models [PDF]

open access: possibleJournal of Econometrics, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
KOOP , Gary   +3 more
openaire   +5 more sources

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