int __stdcall NDK_FARIMA_SIM ( double *  pData,
size_t  nSize,
double  mean,
double  sigma,
double  nIntegral,
double *  phis,
size_t  p,
double *  thetas,
size_t  q,
size_t  nStep,
size_t  nSeed,
double *  retVal 

Returns a simulated data series the underlying FARIMA process.

status code of the operation
Return values
NDK_SUCCESS  Operation successful
NDK_FAILED  Operation unsuccessful. See Macros for full list.
[in] mean is the FARMA model mean (i.e. mu).
[in] sigma is the standard deviation of the model's residuals/innovations.
[in] nIntegral is the model's integration order.
[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] pData is the univariate time series data (a one dimensional array).
[in] nSize is the number of observations in pData.
[in] nSeed is an unsigned integer for setting up the random number generators
[out] retVal is the calculated simulation value
[in] nSteps is the number of future steps to simulate for.
  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.
Header SFSDK.H

* 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