|int __stdcall NDK_PCR_FORE||(||double **||X,|
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.
- The underlying model is described here.
- The sample data may include missing values.
- Each column in the input matrix corresponds to a separate variable.
- Each row in the input matrix corresponds to an observation.
- Observations (i.e. row) with missing values in X or Y are removed.
- The number of rows of the response variable (Y) must be equal to the snumber of rows of the explanatory variables (X).
- The MLR_FORE function is available starting with version 1.60 APACHE.
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL