int __stdcall NDK_SARIMAX_FITTED | ( | double * | pData, |
double ** | pFactors, | ||
size_t | nSize, | ||
size_t | nFactors, | ||
double * | fBetas, | ||
double | mean, | ||
double | sigma, | ||
WORD | nIntegral, | ||
double * | phis, | ||
size_t | p, | ||
double * | thetas, | ||
size_t | q, | ||
WORD | nSIntegral, | ||
WORD | nSPeriod, | ||
double * | sPhis, | ||
size_t | sP, | ||
double * | sThetas, | ||
size_t | sQ, | ||
FIT_RETVAL_FUNC | retType | ||
) |
Returns an array of cells for the fitted values (i.e. mean, volatility and residuals)
- Returns
- status code of the operation
- Return values
-
NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
- Parameters
-
[in,out] pData is the univariate time series data (a one dimensional array). [in] pFactors is the exogneous factors time series data (each column is a separate factor, and each row is an observation). [in] nSize is the number of observations. [in] nFactors is the number of exognous factors [in] fBetas is the weights or loading of the exogneous factors [in] mean is the ARIMA/SARIMA model's long-run mean/trend (i.e. mu). If missing (i.e. NaN), then it is assumed zero. [in] sigma is the standard deviation of the model's residuals/innovations. [in] nIntegral is the non-seasonal difference order [in] phis are the coefficients's values of the non-seasonal AR component [in] p is the order of the non-seasonal AR component [in] thetas are the coefficients's values of the non-seasonal MA component [in] q is the order of the non-seasonal MA component [in] nSIntegral is the seasonal difference [in] nSPeriod is the number of observations per one period (e.g. 12=Annual, 4=Quarter) [in] sPhis are the coefficients's values of the seasonal AR component [in] sP is the order of the seasonal AR component [in] sThetas are the coefficients's values of the seasonal MA component [in] sQ is the order of the seasonal MA component [in] retType is a switch to select a output type Order Description 1 Fitted mean (default) 2 Fitted standard deviation or volatility 3 Raw (non-standardized) residuals 4 Standardized residuals
- 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.
- Requirements
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Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
- Examples
-