I want to provide a prediction model for the concentration of pollutant particles with the help of meteorological data and the concentration of pollutant particles. My output is particle concentration (regression) and my input is meteorological data. My data is time series. Which models consider the sequence of time series?Thank you for my answer.
Chuck A Arize
AutoRegressive Integrated Moving Average (ARIMA) models are among the most widely used time series forecasting techniques: In an Autoregressive model, the forecasts correspond to a linear combination of past values of the variable.
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Halis Bilgil
The grey modeling for the estimation of time series is one of the most successful tools in recent times. For example, you can use the exgm(1,1) model.
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