bool f(
	double[] theta,
	int iobs,
	double[] frq,
	double[] wt,
	double[] e
)

Function f ( 
	theta As Double(),
	iobs As Integer,
	frq As Double(),
	wt As Double(),
	e As Double()
) As Boolean

bool f(
	array<double>^ theta, 
	int iobs, 
	array<double>^ frq, 
	array<double>^ wt, 
	array<double>^ e
)

abstract f : 
        theta : float[] * 
        iobs : int * 
        frq : float[] * 
        wt : float[] * 
        e : float[] -> bool 

Parameters

theta

Type: SystemDouble
An input double array containing the parameter values of the model.

iobs

Type: SystemInt32
An input int value indicating the observation index.

frq

Type: SystemDouble
An output double array of length 1 containing the frequency for observation y[iobs].

wt

Type: SystemDouble
An output double array of length 1 containing the weight for observation y[iobs].

e

Type: SystemDouble
An output double array of length 1 which contains the error (residual) for observation y[iobs].

Return Value

The length of theta corresponds to the number of unknown parameters in the model.

The function is evaluated at observation y[iobs].

Use wt = 1.0 for equal weighting (unweighted least squares).

Reference