| int __stdcall NDK_AIRLINE_VALIDATE | ( | double | mean, |
| double | sigma, | ||
| WORD | S, | ||
| double | theta, | ||
| double | theta2 | ||
| ) |
Examines the model's parameters for stability constraints (e.g. stationary, etc.).
- Returns
- status code of the operation
- Return values
-
NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
- Parameters
-
[in] mean is the model mean (i.e. mu). [in] sigma is the standard deviation 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 (see model description). [in] theta2 is the coefficient of s-lagged innovation (see model description).
- 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 standard deviation (i.e. \(\sigma\)) of the ARMA model's residuals should be greater than zero.
- The Airline model is a special case of multiplicative seasonal ARMA model.
- 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_VALIDATE | ( | double | mean, |
| double | sigma, | ||
| short | dSeason, | ||
| double | theta, | ||
| double | theta2 | ||
| ) |
Examines the model's parameters for stability constraints (e.g. stationary, etc.).
- Return Value
-
a value from NDK_RETCODE enumeration for the status of the call.
NDK_SUCCESS operation successful Error Error Code
- Parameters
-
[in] mean is the model mean (i.e. mu). [in] 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] theta is the coefficient of first-lagged innovation (see model description). [in] theta2 is the coefficient of s-lagged innovation (see model description).
- 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 standard deviation (i.e. \(\sigma\)) of the ARMA model's residuals should be greater than zero.
- The Airline model is a special case of multiplicative seasonal ARMA model.
- 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
