Time Series Analysis in SPSS | ARIMA vs Expert Modeler

Time series analysis with ARIMA (Autoregressive Integrated Moving Average) is a popular method for modeling and forecasting time series data. ARIMA is a class of statistical models for analyzing and forecasting time series data.
ARIMA models can be used to model a wide range of time series data, including economic, financial, and stock market data, as well as data from other fields such as meteorology, engineering, and biology.
The ARIMA model is a combination of three components:
Autoregressive (AR) component: This component models the dependence of the current observation on the past observations of the time series.
Integrated (I) component: This component models the degree of differencing required to make the time series stationary.
Moving Average (MA) component: This component models the dependence of the current observation on the past errors (the differences between the actual and predicted values) of the time series.
To build an ARIMA model, we need to determine the appropriate order of the ARIMA model, which is usually denoted as (p, d, q), where p is the order of the autoregressive component, d is the degree of differencing required to make the time series stationary, and q is the order of the moving average component.
The order of the ARIMA model can be determined by analyzing the autocorrelation and partial autocorrelation plots of the time series data. Once the order is determined, we can estimate the parameters of the model using maximum likelihood estimation or other optimization techniques.
ARIMA models can be used to make forecasts of future values of the time series, and can also be used for anomaly detection and outlier detection. However, it is important to note that ARIMA models are based on certain assumptions about the data, and may not be appropriate for all types of time series data.
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[@EstherDavid-x5i]

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[@piusodunze]

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[@theoutlier7395]

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[@tellusapartments3398]

Thank you!
This was the only video I found that explained the output in SPSS. Not just going over the graphs but explaining the data that SPSS display.

[@theoutlier7395]

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[@vijithav8224]

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[@ambatnisha]

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[@makav3li665]

Excellent tutorial. Please, how do/did you create ur training and test data??

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[@makav3li665]

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[@amirataki8591]

Can we use GARCH / EGARCH model in SPSS?

[@theoutlier7395]

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