NDK_AIRLINE_FORE

int __stdcall NDK_AIRLINE_FORE ( double *  pData,
size_t  nSize,
double  mean,
double  sigma,
WORD  S,
double  theta,
double  theta2,
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 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).
[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
  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 argument (mean) can take any value or be omitted, in which case a zero value is assumed.
  5. The value of the residuals/innovations standard deviation (sigma) must be positive.
  6. The season length must be greater than one.
  7. The input argument for the non-seasonal MA parameter - theta - is optional and can be omitted, in which case no non-seasonal MA component is included.
  8. The input argument for the seasonal MA parameter - theta2 - is optional and can be omitted, in which case no seasonal MA component is included.
Requirements
Header SFSDK.H
Library SFSDK.LIB
DLL SFSDK.DLL
Examples


   
Namespace:  NumXLAPI
Class:  SFSDK
Scope:  Public
Lifetime:  Static
int NDK_AIRLINE_FORE ( double[]  pData,
UIntPtr  nSize,
double  mean,
double  sigma,
short  dSeason,
double  theta,
double  theta2,
UIntPtr  nStep,
FORECAST_RETVAL_FUNC  retType,
double  alpha,
ref double  retVal 
)

Calculates the out-of-sample forecast statistics.

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 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).
[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
  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 argument (mean) can take any value or be omitted, in which case a zero value is assumed.
  5. The value of the residuals/innovations standard deviation (sigma) must be positive.
  6. The season length must be greater than one.
  7. The input argument for the non-seasonal MA parameter - theta - is optional and can be omitted, in which case no non-seasonal MA component is included.
  8. The input argument for the seasonal MA parameter - theta2 - is optional and can be omitted, in which case no seasonal MA component is included.
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