ARIMA models
Forecasting irish inflation using ARIMA models
... Multivariate models may consist of single equation models with exogenous explanatory variables or alternatively may include a structural or non-structural system of ...(BVAR) models for forecasting ...
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Modeling and forecasting inflation in Philippines using ARIMA models
... and models by not using an inflation rate prediction can result in imprecise investment and saving decisions, potentially leading to economic instability (Enke & Mehdiyev, ...
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Predicting inflation in the Kingdom of Bahrain using ARIMA models
... and models by not using an inflation rate prediction can result in imprecise investment and saving decisions, potentially leading to economic instability (Enke & Mehdiyev, ...
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Modeling and forecasting inflation in Tanzania using ARIMA models
... One of the methods that are commonly used for forecasting time series data is the Autoregressive Integrated Moving Average (ARIMA) (Box & Jenkins, 1976; Brocwell & Davis, 2002; Chatfield, 2004; Wei, 2006; ...
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COMPARATIVE ANALYSIS OF THE PERFORMANCE OF ARTIFICIAL NEURAL NETWORKS (ANNs) AND AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) MODELS ON RAINFALL FORECASTING
... Traditionally, ARIMA is one of the widely used method for rainfall prediction due to its ability to predict k-step ahead based on past observations (Somvanshi et ...Nigeria. ARIMA (1,1,0) was found to best ...
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Modeling and forecasting inflation in Burundi using ARIMA models
... One of the methods that are commonly used for forecasting time series data is the Autoregressive Integrated Moving Average (ARIMA) (Box & Jenkins, 1976; Brocwell & Davis, 2002; Chatfield, 2004; Wei, 2006; ...
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Prediction of Inflation in Algeria using ARIMA models
... One of the methods that are commonly used for forecasting time series data is the Autoregressive Integrated Moving Average (ARIMA) (Box & Jenkins, 1976; Brocwell & Davis, 2002; Chatfield, 2004; Wei, 2006; ...
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ARMA and ARIMA MODELS in PT H. M Sampoerna Tbk
... From the research that has been done can be concluded that the data analysis of financial ratios EPS, ROI, ROE, ROS, IGR, SGR are stationary filmed and again not filmed. As for causality test results almost had a two way ...
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Prediction of total population in Togo using ARIMA models
... ARIMA models are often considered as delivering more accurate forecasts then econometric techniques (Song et al, ...2003b). ARIMA models outperform multivariate models in forecasting ...
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Modeling and forecasting carbon dioxide emissions in China using Autoregressive Integrated Moving Average (ARIMA) models
... ARIMA models are often considered as delivering more accurate forecasts then econometric techniques (Song et al, ...2003b). ARIMA models outperform multivariate models in forecasting ...
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Is Nigeria's economy progressing or backsliding? Implications from ARIMA models
... Both AR components (i.e the AR (1) and AR (2) coefficients) are positive as conventionally expected, although statistically insignificant. The statistical insignificance of the coefficients could be attributed to the ...
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Forecasting by (Arima) models Toinflation rate in Sudan
... We will use the second difference of the varibles from The stationary test for our Box-Jenkins (ARIMA) Models to estimaedthe model of Inflation Rate in Sudan by using the leat square method.The outputof the ...
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Applicability of ARIMA Models in Wholesale Wheat Market of Rajasthan: An Investigation
... series approach to forecasting is one such approach which relies on the past pattern in a time series to forecast prices in the future. Burark and Sharma (2012) confirmed the suitability of Box-Jenkins univariate ...
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FORECASTING GENERAL AND VOCATIONAL SECONDARY STUDENTS AND SCHOOLS IN EGYPT BY USING ARIMA
... This paper aims to provide short term projection of general and vocational students and schools in Egypt by using ARIMA models. This study uses data during the period of 1987 to 2017 to forecast the period ...
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Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models
... hybrid ARIMA-GARCH and ARIMA-EGARCH models. Generally, ARIMA models can handle nonstationary data while the GARCH family models have the ability to capture nonlinear ...
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Improving the performance of financial forecasting using different combination architectures of ARIMA and ANN models
... (ARIMA) models are one of the most important and widely used linear time series ...the ARIMA model comes from its statistical features as well as the well-known Box-Jenkins (1976) methodology in the ...
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Modeling Monthly Rainfall Time Series Using Ets State Space And Sarima Models
... space models based on exponential smoothing and the Box-Jenkins modelling ...Seasonal ARIMA models and ETS state space models were ...Both models were found to be adequate for ...
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Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model
... Kwasi and Sharma (2015) also carried out a study to explore modelling and forecasting of wholesale groundnut monthly prices in Bikaner district of Rajasthan using the Autoregressive Integrated Moving Average ...
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Modelling of crude oil prices using hybrid arima-garch model
... series models. Eventhough ARIMA is a popular method for forecasting, it is not able to handle volatile ...the ARIMA model, it will be hybridized with GARCH model. The models proposed in this ...
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Modeling and forecasting Botswana's Growth Domestic Product (GDP) per capita
... between ARIMA models and Artificial Neural Networks (ANN), Okasha & Yaseen (2013) agreed that the Box-Jenkins, ARIMA models proved to be more accurate than the Artificial Neural Network ...
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