NDK_ARIMA_FORE

C/C++
.Net

int __stdcall NDK_ARIMA_FORE	(	double *	pData,
		size_t	nSize,
		double	mean,
		double	sigma,
		WORD	nIntegral,
		double *	phis,
		size_t	p,
		double *	thetas,
		size_t	q,
		size_t	nStep,
		FORECAST_RETVAL_FUNC	retType,
		double	alpha,
		double *	retVal
	)

Calculates the out-of-sample forecast statistics.

Returns: status code of the operation

Return values

NDK_SUCCESS	Operation successful
NDK_FAILED	Operation unsuccessful. See Macros for full list.

Parameters

[in] pData is the univariate time series data (a one dimensional array).

[in] nSize is the number of observations in pData.

[in] mean is the ARMA model mean (i.e. mu).

[in] sigma is the standard deviation of the model's residuals/innovations.

[in] nIntegral is the model's integration order.

[in] phis are the parameters of the AR(p) component model (starting with the lowest lag).

[in] p is the number of elements in phis (order of AR component)

[in] thetas are the parameters of the MA(q) component model (starting with the lowest lag).

[in] q is the number of elements in thetas (order of MA component)

[in] nStep is the forecast time/horizon (expressed in terms of steps beyond end of the time series).

[in]

retType

is a switch to select the type of value returned

Order	Description
1	Mean forecast value (default)
2	Forecast standard error (aka local volatility)
3	Volatility term structure
4	Lower limit of the forecast confidence interval
5	Upper limit of the forecast confidence interval

[in] alpha is the statistical significance level. If missing, a default of 5% is assumed.

[out] retVal is the calculated forecast value

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.
- 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.
- 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).

Requirements

Header	SFSDK.H
Library	SFSDK.LIB
DLL	SFSDK.DLL

Examples

Namespace:	NumXLAPI
Class:	SFSDK
Scope:	Public
Lifetime:	Static

int NDK_ARIMA_FORE	(	double[]	pData,
		UIntPtr	nSize,
		double	mean,
		double	sigma,
		short	nIntegral,
		double[]	phis,
		UIntPtr	p,
		double[]	thetas,
		UIntPtr	q,
		UIntPtr	nStep,
		FORECAST_RETVAL_FUNC	retType,
		double	alpha,
		ref double	retVal
	)