autoregressive moving-average analysis
ARIMA-M: A New Model for Daily Water Consumption Prediction, Based on the Autoregressive Integrated Moving Average Model and the Markov Chain Error Correction
... trend analysis and demand ...regression analysis to investigate the influencing factors of urban domestic water demand, such as population, output value of tertiary industry, and per capita living area, and ...
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Analysis of the Volatility of the Electricity Price in Kenya Using Autoregressive Integrated Moving Average Model
... The electric power industry in many countries all over the world is moving from a centralized operational approach to a competitive one. The understanding of electric power supply as a public service is being ...
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COMPARATIVE ANALYSIS OF THE PERFORMANCE OF ARTIFICIAL NEURAL NETWORKS (ANNs) AND AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) MODELS ON RAINFALL FORECASTING
... The ARIMA model, also known as the Box-Jenkins methodology. It is a robust and effective approach for analyzing time series data. The model was introduced by Box and Jenkins (1976) and commonly used in analysis ...
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Application of the Improved Generalized Autoregressive Conditional Heteroskedast Model Based on the Autoregressive Integrated Moving Average Model in Data Analysis
... the Autoregressive Inte- grated Moving Average model-Generalized Autoregressive Conditional Hete- roskedast (ARIMA-GARCH) model [1] and normal Asymmetric Power Autore- gressive Conditional ...
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Using autoregressive integrated moving average models in the analysis and forecasting of mobile network traffic data
... of Autoregressive Integrated Moving Average (ARIMA) models by using an empirical data measured from a live High Speed Downlink Packet Access (HSDPA) telecommunication network operator with coverage ...
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An Autoregressive Integrated Moving Average Models For Process Output And Forecasting
... of analysis, some descriptive measures were used to examine the main properties of the ...centred moving average and differencing of order twelve advocated by Box and Jenkins (1970) were used to ...
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A Box-jenkins Model For Monthly Natural Gas Production In Nigeria
... series analysis of the production of gas in ...series analysis of the monthly ...of autoregressive integrated moving average (ARIMA) modeling, of which seasonal autoregressive ...
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Forecasting daily meteorological time series using ARIMA and regression models
... these models (Hoffmann et al., 2017; Krzyszczak et al., 2017b; Walczak et al., 1997). When taking into account the global warming effects on the processes occurring in the soil-plant-atmosphere system, the shifts in ...
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Assessment of dynamic linear and non-linear models on rainfall variations predicting of Iran
... the Autoregressive Integrated Moving Average (ARIMA) models and Autoregressive Conditional Heteroskedasticity (ARCH) family models have been used for predicting the monthly and annual rainfall ...
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An Analysis Of The Relationship Between Risk And Return In The Gold Market Of Asian Countries
... weighted moving average method (EWMA) and Generalized Autoregressive Conditional Heteroskedasticity, GARCH (1, 1) ...Econometric Analysis between Commodities and Financial Variables: The Case ...
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Flood Prediction Using Seasonal Autoregressive Integrated Moving Average (SARIMA) Model
... This research focuses on forecasting flood and the accuracies are measured by RMSE values. The performance of the developed models is evaluated by comparing with those of LSTM and BP. More details about the methodology ...
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Autoregressive Integrated Moving Average (ARIMA) Model for Exchange Rate (Naira to Dollar)
... Analysis of exchange rate using ARIMA model, was carried out to help those in charge of the economy who are carried out to help those in charge of the economy who are interested in the strange and irregular trend ...
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Forecast Comparison of Seasonal Autoregressive Integrated Moving Average (SARIMA) and Self Exciting Threshold Autoregressive (SETAR) Models
... FORECAST PERFORMANCE MEASURES INDICES Using all indices as discussed in the mathematical preliminaries, the following tables were generated from the analysis. Both in-sample and out-of sample forecast performances ...
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Time series model for forecasting the number of new admission inpatients
... of autoregressive ( p ) and seasonal autoregressive ( P ), the order of regular differ- ence ( d ) and seasonal difference ( D ), and the order of moving average ( q ) and seasonal ...
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A novel prediction system in dengue fever using NARMAX model
... this analysis show that the NARMAX model yield better accuracy as compared to autoregressive moving average with exogenous input (ARMAX) model in diagnosis intelligent system based on the ...
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Time Series Analysis of Production and Price of Cattle and Milkfish in the Philippines
... considered Autoregressive (AR), Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) processes to select the appropriate stochastic model for forecasting ...
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Study & Development of Short Term Load Forecasting Models Using Stochastic Time Series Analysis
... The Autoregressive (AR), Autoregressive Moving Average (ARMA) and Autoregressive Integrated Moving Average (ARIMA) models can be developed using time series approach for ...
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Censored time series analysis with autoregressive moving average models
... the analysis of cloud ceiling height, which is an important variable accounting for weather-related accidents and flight delays, provided by the National Center for Atmospheric Research (NCAR), measured at San ...
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Modelling And Forecasting Small Haplochromine Species (Kambuzi) Production In Malawi - A Stochastic Model Approach
... graphical analysis method was ...an autoregressive of order p (AR ...a moving-average of order q (MA ...the autoregressive moving-average of order p and q (ARMA (p, ...
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Application of Arima and Garch models in forecasting crude oil prices
... The price of a barrel of oil is highly dependent on both its grade, determined by factors such as its specific API gravity, sulphur content and also location of production. The vast majority of oil is not traded on an ...
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