FORECASTING FRESH WATER AND MARINE FISH PRODUCTION IN MALAYSIA USING ARIMA AND ARFIMA MODELS
Malaysian Journal of Computing, 2018 Malaysia is surrounded by sea, rivers and lakes which provide natural sources of fish for human consumption. Hence, fish is one source of protein supply to the country and fishery is a sub-sector that contribute to the national gross domestic product ...
P.J.W. Mah, N.N.M. Zali, N.A.M. Ihwal, N.Z. Azizan
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A guide to Whittle maximum likelihood estimator in MATLAB. [PDF]
Front Netw Physiol, 2023 Roume C.
europepmc +1 more source
Measuring core inflation in the euro area [PDF]
We propose a measure of core inflation which is derived from a Markov switching ARFIMA model. The Markov switching ARFIMA model generalises the standard ARFIMA model allowing mean reversion to take place with respect to a changing unconditional mean.
Morana, Claudio
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A note on Michelacci and Zaffaroni, long memory, and time series of economic growth [PDF]
long memory, economic ...
B. Verspagen, G. Silverberg
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Network traffic prediction based on ARFIMA model
, 2013 ARFIMA is a time series forecasting model, which is an improved ARMA model, the ARFIMA model proposed in this article is demonstrated and deduced in detail. combined with network traffic of CERNET backbone and the ARFIMA model,the result shows that,compare to the ARMA model, the prediction efficiency and accuracy has increased significantly, and not ...
Zhou, Dingding +2 more
openaire +2 more sources
پژوهشهای ریاضی, 2020 Introduction The data obtained from observing a phenomenon over time is very common. One of the most popular models in time series and signal processing is the Autoregressive moving average model (ARMA).
Mahmod Afshari +2 more
doaj
TESTING THE LONG RANGE-DEPENDENCE FOR THE CENTRAL EASTERN EUROPEAN AND THE BALKANS STOCK MARKETS [PDF]
Annals of the University of Oradea: Economic Science, 2013 In this study we tested the existence of long memory in the the return series for major Central Eastern European and Balkans stock markets, using the following statistical methods: Hurst Exponent, GPH method, Andrews and Guggenberger method, Reisen ...
Pece Andreea Maria +3 more
doaj
Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach [PDF]
Previous models of monthly CPI inflation time series have focused on possible regime shifts, non-linearities and the feature of long memory. This paper proposes a new time series model, named Adaptive ARFIMA; which appears well suited to describe ...
Claudio Morana, Richard T. Baille
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SaPt-CNN-LSTM-AR-EA: a hybrid ensemble learning framework for time series-based multivariate DNA sequence prediction. [PDF]
PeerJ, 2023 Yan W +5 more
europepmc +1 more source
A Generalized ARFIMA Process with Markov-Switching Fractional Differencing Parameter [PDF]
We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the
Wen-Jen Tsay, Wolfgang Härdle
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