int __stdcall NDK_PCR_FORE ( double **  X,
size_t  nXSize,
size_t  nXVars,
LPBYTE  mask,
size_t  nMaskLen,
double *  Y,
size_t  nYSize,
double  intercept,
double *  target,
double  alpha,
WORD  nRetType,
double *  retVal 

Calculates the model's estimated values, std. errors and related statistics.

status code of the operation
Return values
NDK_SUCCESS  Operation successful
NDK_FAILED  Operation unsuccessful. See Macros for full list.
[in] X is the independent variables data matrix, such that each column represents one variable
[in] nXSize is the number of observations (i.e. rows) in X
[in] nXVars is the number of variables (i.e. columns) in X
[in] mask is the boolean array to select a subset of the input variables in X. If missing (i.e. NULL), all variables in X are included.
[in] nMaskLen is the number of elements in mask
[in] Y is the response or the dependent variable data array (one dimensional array)
[in] nYSize is the number of elements in Y
[in] intercept is the constant or the intercept value to fix (e.g. zero). If missing (NaN), an intercept will not be fixed and is computed normally
[in] target is the value of the explanatory variables (a one dimensional array)
[in] alpha is the statistical significance of the test (i.e. alpha)
[in] nRetType is a switch to select the return output (1 = forecast (default), 2 = error, 3 = upper limit, 4 = lower limit).
[out] retVal is the calculated forecast value or statistics.
  1. The underlying model is described here.
  2. The sample data may include missing values.
  3. Each column in the input matrix corresponds to a separate variable.
  4. Each row in the input matrix corresponds to an observation.
  5. Observations (i.e. row) with missing values in X or Y are removed.
  6. The number of rows of the response variable (Y) must be equal to the snumber of rows of the explanatory variables (X).
  7. The MLR_FORE function is available starting with version 1.60 APACHE.
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