Calculates the estimated error/standard deviation of the conditional mean forecast.

## Syntax

**ARMA_FORESD**(**X**, Order, **Mean**, **sigma**, **phi**, **theta**, **T**)

**X**- is the univariate time series data (a one-dimensional array of cells (e.g., rows or columns)).
**Order**- is the time order in the data series (i.e., the first data point's corresponding date (earliest date = 1 (default), latest date = 0)).
Value Order 1 Ascending (the first data point corresponds to the earliest date) ( **default**).0 Descending (the first data point corresponds to the latest date). **Mean**- is the ARMA model mean (i.e., mu).
**sigma**- is the standard deviation of the model's residuals/innovations.
**phi**- are the parameters of the AR(p) component model (starting with the lowest lag).
**theta**- are the parameters of the MA(q) component model (starting with the lowest lag).
**T**- is the forecast time/horizon (expressed in terms of steps beyond the end of the time series).

* *Warning

ARMA_FORESD() function is deprecated as of version 1.63: use the ARMA_FORE function instead.

## Remarks

- The underlying model is described here.
- The time series is homogeneous or equally spaced.
- The time series may include missing values (e.g., #N/A) at either end.
- The number of parameters in the input argument - phi - determines the order of the AR component.
- The number of parameters in the input argument - theta - determines the order of the MA component.

## Files Examples

## Related Links

## References

- D. S.G. Pollock; Handbook of Time Series Analysis, Signal Processing, and Dynamics; Academic Press; Har/Cdr edition(Nov 17, 1999), ISBN: 125609906.
- James Douglas Hamilton; Time Series Analysis; Princeton University Press; 1st edition(Jan 11, 1994), ISBN: 691042896.
- Tsay, Ruey S.; Analysis of Financial Time Series; John Wiley & SONS; 2nd edition(Aug 30, 2005), ISBN: 0-471-690740.
- Box, Jenkins and Reisel; Time Series Analysis: Forecasting and Control; John Wiley & SONS.; 4th edition(Jun 30, 2008), ISBN: 470272848.
- Walter Enders; Applied Econometric Time Series; Wiley; 4th edition(Nov 03, 2014), ISBN: 1118808568.

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