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A Forecasting Model for Japan's Unemployment Rate [PDF]
Eurasian Journal of Business and Economics, 2010 This note aims to achieve a parsimonious fractionally-integrated autoregressive and moving average (ARFIMA) model for recent time series data of Japan's unemployment rate. A brief review of the ARFIMA model is provided, leading to econometric modeling of
Takamitsu KURITA
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Inflation Dynamics in the ABC (Argentina, Brazil and Chile) countries
Ensayos de Política Económica, 2020 Este trabajo evalúa la inercia y persistencia de la inflación y sus componentes para Argentina (dos períodos), Brasil y Chile utilizando modelos estacionales y fraccionalmente integrados autorregresivo de promedios móviles (modelo S-ARFIMA).
Fernando Zarzosa Valdivia
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Kubik, 2015 Model ARFIMA (Autoregressive Fractionally Integrated Moving Average) merupakan pengembangan dari model ARIMA yang pertama kali dikenalkan oleh Granger dan Joyeux (1980). Sedangkan Hosking (1981) memperkenalkan sifat jangka panjang (long memory) pada data
Rini Cahyandari, Rima Erviana
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MODELLING FOR THE WAVELET COEFFICIENTS OF ARFIMA PROCESSES [PDF]
Journal of Time Series Analysis, 2014 AbstractWe consider a model for the discrete nonboundary wavelet coefficients of autoregressive fractionally integrated moving average (ARFIMA) processes in each scale. Because the utility of the wavelet transform for the long‐range dependent processes, which many authors have explained in semi‐parametrical literature, is approximating the transformed ...
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Maximum likelihood estimation of stationary multivariate ARFIMA processes [PDF]
Journal of Statistical Computation and Simulation, 2010 This article considers the maximum likelihood estimation (MLE) of a class of stationary and invertible vector autoregressive fractionally integrated moving-average (VARFIMA) processes considered in Equation (26) of Luceno [A fast likelihood approximation for vector general linear processes with long series: Application to fractional differencing ...
Martin, Vance L., Wilkins, Nigel P.
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Journal of Hydrology and Hydromechanics, 2014 Short term streamflow forecasting is important for operational control and risk management in hydrology. Despite a wide range of models available, the impact of long range dependence is often neglected when considering short term forecasting.
Szolgayová Elena +3 more
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SMALL-SAMPLE LIKELIHOOD-BASED INFERENCE IN THE ARFIMA MODEL [PDF]
Econometric Theory, 2000 The autoregressive fractionally integrated moving average (ARFIMA) model has become a popular approach for analyzing time series that exhibit long-range dependence. For the Gaussian case, there have been substantial advances in the area of likelihood-based inference, including development of the asymptotic properties of the maximum likelihood ...
Offer Lieberman +2 more
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Evaluation of Dual Long Memory Properties with Emphasizing the Skewed and Fat-Tail Distribution: Evidence from Tehran Stock Exchange [PDF]
Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī, 2014 This paper investigates the presence of long memory in the Tehran stock market, using the ARFIMA, GPH, GSP and FIGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of TEPIX ...
Mohammad Javad Mohagheghnia +3 more
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Adjusted Empirical Likelihood for Long-memory Time Series Models
, 2016 Empirical likelihood method has been applied to short-memory time series models by Monti (1997) through the Whittle's estimation method. Yau (2012) extended this idea to long-memory time series models. Asymptotic distributions of the empirical likelihood
Gamage, Ramadha D. Piyadi +2 more
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InPrime, 2019 Wind speed is one of the most important weather factors in the landing and takeoff process of airplane because it can affect the airplane's lift. Therefore, we need a model to predict the wind speed in an area.
Devi Ila Octaviyani +2 more
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