NDK_PCR_FORE

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

Returns

status code of the operation

Return values

NDK_SUCCESS	Operation successful
NDK_FAILED	Operation unsuccessful. See Macros for full list.

Parameters

[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.

Remarks

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.

Requirements

Header	SFSDK.H
Library	SFSDK.LIB
DLL	SFSDK.DLL