NDK_ARMA_GOF

Computes the log-likelihood ((LLF), Akaike Information Criterion (AIC) or other goodness of fit function of the ARMA model.

Return Value

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

NDK_SUCCESS	operation successful
Error	Error Code

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]	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]	retType	is a switch to select a fitness measure Order   Description 1 Log-Likelihood Function (LLF) (default) 2 Akaike Information Criterion (AIC) 3 Schwarz/Bayesian Information Criterion (SIC/BIC) 4 Hannan-Quinn information criterion (HQC)
[out]	retVal	is the calculated goodness of fit value.

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. The long-run mean can take any value or be omitted, in which case a zero value is assumed.
5. The residuals/innovations standard deviation (sigma) must greater than zero.
6. 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 may have missing values 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).
7. 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).
8. Missing parameters values reduce the model's actual number of overall parameters, thus improving the AIC, BIC, and HQC statistics.

Exceptions

Exception Type	Condition
None	N/A

Requirements

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