Time Series & Survival · TOOL GUIDE

ARIMA Forecasting

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Understand the method. Use it with confidence.

Fit ARIMA model and forecast future values. Quantly runs the method against your active analysis context and returns structured results for review and interpretation.

01

When to use it

Use this tool for ordered observations, forecasting, or time-to-event outcomes where timing and censoring matter.
Use it only when the selected variables and study design match the method's requirements.

02

How to use it

  1. Open the tool from the Quantly Tools panel.
  2. Confirm the active dataset and analysis session.
  3. Set Date/Time Column (Required): Select the column containing the date or time information.
  4. Set Value Column (Required): Select the numeric column to forecast.
  5. Set AR Order (p) (Required): The order of the autoregressive part of the model.
  6. Set Differencing Order (d) (Required): The degree of differencing needed to make the series stationary.
  7. Set MA Order (q) (Required): The order of the moving-average part of the model.
  8. Set Forecast Periods (Required): The number of periods to forecast into the future.
  9. Review optional or advanced settings and keep defaults unless your design requires a change.
  10. Run the tool, inspect warnings and diagnostics, then save or export the result with its assumptions.
03

How to interpret results

Review time order, stationarity or proportional-hazards assumptions, uncertainty intervals, censoring, and validation over later periods. Forecasts and survival estimates become less certain farther from observed data.