int __stdcall NDK_AIRLINE_GOF | ( | double * | pData, |
size_t | nSize, | ||
double | mean, | ||
double | sigma, | ||
WORD | S, | ||
double | theta, | ||
double | theta2, | ||
GOODNESS_OF_FIT_FUNC | retType, | ||
double * | retVal | ||
) |
Computes the log-likelihood (LLF), Akaike Information Criterion (AIC) or other goodness of fit function of the AirLine model.
- 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 model mean (i.e. \(\mu\)). [in] sigma is the standard deviation ( \(\sigma\)) of the model's residuals/innovations. [in] S is the length of seasonality (expressed in terms of lags, where s > 1). [in] theta is the coefficient of first-lagged innovation ( \(\theta\))(see model description). [in] theta2 is the coefficient of s-lagged innovation ( \(\Theta\)) (see model description). [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 value of the goodness of fit.
- Remarks
-
- The underlying model is described here.
- The time series is homogeneous or equally spaced
- The time series may include missing values (e.g. NaN) at either end.
- The airline model with order \(s\) has 4 parameters: \(\mu\,,\sigma\,\,,\theta\,,\Theta\)
- The Airline model is a special case of multiplicative seasonal ARIMA model, and it assumes independent and normally distributed residuals with constant variance.
- Requirements
-
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
- Examples
-
Namespace: | NumXLAPI |
Class: | SFSDK |
Scope: | Public |
Lifetime: | Static |
int NDK_AIRLINE_GOF | ( | double[] | pData, |
UIntPtr | nSize, | ||
double | mean, | ||
double | sigma, | ||
short | dSeason, | ||
double | theta, | ||
double | theta2, | ||
GOODNESS_OF_FIT_FUNC | retType, | ||
ref double | retVal | ||
) |
Computes the log-likelihood ((LLF), Akaike Information Criterion (AIC) or other goodness of fit function of the AirLine model.
- 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 model mean (i.e. \(\mu\)). [in] sigma is the standard deviation ( \(\sigma\)) of the model's residuals/innovations. [in] dSeason is the length of seasonality (expressed in terms of lags, where s > 1). [in] theta is the coefficient of first-lagged innovation ( \(\theta\))(see model description). [in] theta2 is the coefficient of s-lagged innovation ( \(\Theta\)) (see model description). [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 value of the goodness of fit.
- Remarks
-
- The underlying model is described here.
- The time series is homogeneous or equally spaced
- The time series may include missing values (e.g. NaN) at either end.
- The airline model with order \(s\) has 4 parameters: \(\mu\,,\sigma\,\,,\theta\,,\Theta\)
- The Airline model is a special case of multiplicative seasonal ARIMA model, and it assumes independent and normally distributed residuals with constant variance.
- Exceptions
-
Exception Type Condition None N/A
- Requirements
-
Namespace NumXLAPI Class SFSDK Scope Public Lifetime Static Package NumXLAPI.DLL
- Examples
-
- 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
- * D. S.G. Pollock; Handbook of Time Series Analysis, Signal Processing, and Dynamics; Academic Press; Har/Cdr edition(Nov 17, 1999), ISBN: 125609906
- * Box, Jenkins and Reisel; Time Series Analysis: Forecasting and Control; John Wiley & SONS.; 4th edition(Jun 30, 2008), ISBN: 470272848