Returns an array of cells for the quick guess, optimal (calibrated), or std. Errors in the values of the model's parameters.

## Syntax

**ARIMA_PARAM**(**X**, Order, **d**, Mean, **Sigma**, **Phi**, **Theta**, Type, MaxIter)

**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)).
Order Description 1 Ascending (the first data point corresponds to the earliest date) ( **default**).0 Descending (the first data point corresponds to the latest date). **d**- is the degree of the differencing (i.e., d).
**Mean**- is the ARMA model mean (i.e., mu). If missing, the mean is assumed to be zero.
**Sigma**- is the standard deviation value 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).
**Type**- is an integer switch to select the output array: (1 = Quick Guess (default), 2 = Calibrated, 3 = Std. Errors).
Order Description 1 Quick guess (non-optimal) of parameters' values ( **default**).2 Calibrated (optimal) values for the model's parameters. 3 Standard error of the parameters' values. **MaxIter**- is the maximum number of iterations used to calibrate the model. If missing, the default maximum of 100 is assumed.

## 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 integration order argument (d) must be a positive integer.
- The long-run mean can take any value or may be omitted, in which case a zero value is assumed.
- The residuals/innovations standard deviation (sigma) must be greater than zero.
- For the input argument (phi):
- The input argument is optional and can be omitted, in which case no AR component is included.
- The order of the parameters starts with the lowest lag.
- One or more parameters can be missing or an error code (i.e., #NUM!, #VALUE!, etc.).
- The order of the AR component model is solely determined by the order of the last value in the array with a numeric value (vs. missing or error).

- For the input argument (theta):
- The input argument is optional and can be omitted, in which case no MA component is included.
- The order of the parameters starts with the lowest lag.
- One or more values in the input argument can be missing or an error code (i.e., #NUM!, #VALUE!, etc.).
- The order of the MA component model is solely determined by the order of the last value in the array with a numeric value (vs. missing or error).

- The function was added in version 1.63 SHAMROCK.

## Files Examples

## Related Links

## References

- Hamilton, J.D.; Time Series Analysis, Princeton University Press (1994), ISBN 0-691-04289-6.
- Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740.

## Comments

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