Auto-regressive integrated moving average (ARIMA)
Comparison of auto regressive integrated moving average and artificial neural networks forecasting in mortality of breast cancer
... One of the most common models in time series is auto regressive integrated moving average (ARIMA) model. This model uses Box– Jenkins methodology in the model constructing the model ...
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A Comparative Study in Predicting Colon Rectum Cancer using Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) Models
... using Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network ...Jenkin’s Auto Regressive Integrated Moving Average (ARIMA) ...
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Forecasting risk using auto regressive integrated moving average approach: an evidence from S&P BSE Sensex
... research, Auto Regressive Integrated Moving Average method is used to forecast the future risk and returns for 10 years of historical data from April 2007 to March ...the average ...
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Forecasting Gold Price with Auto Regressive Integrated Moving Average Model
... The present study forecasts the gold price of India by using auto regressive integrated moving average (ARIMA) model over a period of 25 years from July 1990 to February 2015. The study ...
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Forecasting time series data using hybrid grey relational artificial neural network and auto regressive integrated moving average model
... or Auto Regres- sive Integrated Moving Average (ARIMA), Multiple Regressions and Exponential Smoothing are examples of statistical methods, whilst AI paradigms include fuzzy inference systems, ...
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Predictability of Earthquake Occurrence Using Auto Regressive Integrated Moving Average (ARIMA) Model
... of auto regression process (AR), d refers to the degree of differentiation involved (I) and q refers to the (MA) which is the order of the Moving ...
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Forecasting Foreign Institutional Investment Flows towards India Using ARIMA Modelling
... India has witnessed substantial increase in capital flows, particularly Foreign Institutional Investment in equity as well as derivatives segment since the 1990s. However, FII flows are sighted as ‘hot money’- more ...
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Forecasting Inflation Rate of Zambia Using Holt’s Exponential Smoothing
... and Auto-Regressive Integrated Moving Average (ARIMA) models were used to forecast inflation rate of Zambia using the monthly consumer price index (CPI) data from May 2010 to May ...
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A Comparative Study on FFNN and ARIMA Model in the Presence of Outliers
... Time series data mining (TSDM) techniques explores large amount of time series data in search of interesting relationships among variables. The TSDM methods overcome limitations including stationarity and linearity ...
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Spatio temporal dynamic of malaria in Ouagadougou, Burkina Faso, 2011–2015
... seasonal auto‑regressive integrated moving average; GAM: general additive model; GPS: global positioning system; HAs: health areas; HTP: high transmission period; ITP: intermediate ...
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THE MIXTURE MODEL: COMBINING LEAST SQUARE METHOD AND DENSITY BASED CLASS BOOST ALGORITHM IN PRODUCING MISSING DATA AND BETTER MODELS
... e.g. Auto Regressive Moving Average (ARMA) and Auto Regressive Integrated Moving Average (ARIMA) ...
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The Application of Time Series analysis in Forecasting Bridge Displacement Data: Case Study in Wuxi Bridge, Taiwan
... as Auto-Regressive (AR) models, Moving Average (MA) models, Auto- Regressive Moving Average (ARMA), Auto-Regressive Moving Average with ...
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Forecasting daily meteorological time series using ARIMA and regression models
... seasonal auto regressive integrated moving-average, the autoregressive integrated moving-average with external regres- sors in the form of Fourier terms and the ...
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Forecasting of Pakistans Import Prices of Black Tea Using ANN and SARIMA Model
... Many researchers have used time series analysis to forecast the different variables. Review of some past studies have been done in this section. Abeysinghe (1994) showed that using seasonal dummies in removing ...
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Auto Regressive (AR) Models in Forecasting Methods
... autoregressive integrated moving average (ARIMA) models that came to be associated with Box and Jenkins (1976) but has its roots in the Poineering work of Slutski and Yule in year 1920 and wold in ...
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Auto-Regressive Integrated Moving-Averages Model For Daily Rainfall Forecasting
... time series-based methods to analyse and model the data values. The stationary behaviour of the time series is studied in the paper. Studied the Fractal and wavelet methods [1]. Studied T-170 model for forecasting [2]. ...
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Application of SARIMA Model on Money Supply
... research on the trend of narrow money supply in the past. But narrow money supply is central bank’s key regulatory object because of its strong liquidity. Therefore, it is of great significance to predict its development ...
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Forecasting of Potato Prices of Hooghly in West Bengal: Time Series Analysis Using SARIMA Model
... Seasonal Auto Regressive Integrated Moving Average (SARIMA) modeling is deployed in forecasting of monthly average price of potato in Hooghly of West Bengal up to October 2020 ...
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Seasonal Interval Time Series Models in Comparative Study of Industrial Forecasting
... Seasonal Auto-Regressive Integrated Moving Average model (SARIMA), Fuzzy Seasonal Auto-Regressive Integrated Moving Average (FSARIMA), Fuzzy Seasonal ...
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An Analysis Of The Relationship Between Risk And Return In The Gold Market Of Asian Countries
... Average (EWMA)” forecasted the stock prices for 100 companies listed in FTSE 100 from the historical data using exponential weighted moving ...Vector Auto Regressive ...weighted moving ...
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