NDK_AIRLINE_PARAM

Returns an array of cells for the initial (non-optimal), optimal or standard errors of the model's parameters.

Return Value

a value from NDK_RETCODE enumeration for the status of the call. 

NDK_SUCCESS	operation successful
Error	Error Code

Parameters

[in,out]	pData	is the univariate time series data (a one dimensional array).
[in]	nSize	is the number of observations in pData.
[in,out]	mean	is the model mean (i.e. mu).
[in,out]	sigma	is the standard deviation of the model's residuals/innovations.
[in]	dSeason	is the length of seasonality (expressed in terms of lags, where s > 1).
[in,out]	theta	is the coefficient of first-lagged innovation (see model description).
[in,out]	theta2	is the coefficient of s-lagged innovation (see model description
[in]	retType	is a switch to select the type of value returned: 1= Quick Guess, 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
[in]	maxIter	is the maximum number of iterations used to calibrate the model. If missing or less than 100, the default maximum of 100 is assumed.

Remarks

1. The underlying model is described here.
2. The time series is homogeneous or equally spaced
3. The time series may include missing values (e.g. NaN) at either end.
4. NDK_AIRLINE_PARAM returns an array of the values (or errors) of the model's parameters in the following order:
   • \(\mu\)
   • \(\theta\)
   • \(\Theta\)
   • \(\sigma\)
5. The AIRLINE_GUESS sets the \(\mu\) and \(\sigma\) equal to the differenced sample (i.e. \(Z_t=(1-L)(1-L^s)Y_t\)) average, and standard deviation respectively, and it sets the \(\theta = 0\) and \(\Theta=0\)

Exceptions

Exception Type	Condition
None	N/A

Requirements

Namespace	NumXLAPI
Class	SFSDK
Scope	Public
Lifetime	Static
Package	NumXLAPI.DLL

Examples