Results 171 to 180 of about 23,794,745 (244)

Comparative study on sea-level rise in the Yangtze River Estuary and Red River Estuary in the recent 30 years. [PDF]

Sci Rep
Xue W, Qiao L, Zhang S, Zhong Y, Duan X, Yin P, Liu J.   +6 more
europepmc   +1 more source

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

, 2021
Leme PAF, Jalalizadeh M, Dionato FAV, Buosi K, Col LSD, Giacomelli CF, Ferrari KL, Pagliarone AC, Gon LM, Maia CL, Esfahani AA, Reis LO.   +11 more
europepmc   +1 more source

Forecasting COVID-19 new cases in Algeria using Autoregressive fractionally integrated moving average Models (ARFIMA)

, 2020
Balah B, Djeddou M.
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 ...
G. Durham, John Geweke, S. Porter-Hudak, Fallaw Sowell   +3 more
semanticscholar   +2 more sources

Efficient estimation method for generalized ARFIMA models

Communications in Statistics - Theory and Methods, 2022
This paper focuses on pretest and shrinkage estimation strategies for generalized autoregressive fractionally integrated moving average (GARFIMA) models when some of the regression parameters are possible to restrict to a subspace.
S. Pandher, S. Hossain, K. Budsaba, Andrei Volodin   +3 more
semanticscholar   +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 ...
L. Shalalfeh, P. Bogdan, E. Jonckheere
semanticscholar   +2 more sources

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.
R. Baillie, C. Morana
semanticscholar   +2 more sources

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
E. Eğrioğlu, Süleyman Günay
semanticscholar   +3 more sources