LinFit

Advanced Analysis Library Only

AnalysisLibErrType LinFit (double arrayX[], double arrayY[], int numberOfElements, double outputArray[], double *slope, double *intercept, double *meanSquaredError);

Purpose

Note  This function is obsolete. National Instruments recommends that you use LinearFitEx instead.

Finds the slope and intercept values that best represent the linear fit of the data points (X, Y) using the least squares method. LinFit obtains the element of the output array, using the following formula:

Zi = slope × Xi + intercept

LinFit obtains the mean squared error using the following formula:


where n is the number of sample points.

LinFit can perform this operation in place; that is, the input and output arrays can be the same.

Example

/* Generate a ramp pattern and find the best linear fit. */
double x[200], y[200], z[200];
double start, end, a, b, slope, intercept, mse;
int n;
n = 200;
start = 0.0;
end = 1.99E2;
Ramp (n, start, end, x); /* x[i] = i */
a = 3.5;
b = -2.75;
LinEv1D (x, n, a, b, y); /* y[i] = a*x[i] + b */
/* Find the best linear fit in z. */
LinFit (x, y, n, z, &slope, &intercept, &mse);

Parameters

Input
Name Type Description
arrayX double-precision array An array whose elements contain the X coordinates of the (X,Y) data sets.
arrayY double-precision array An array whose elements contain the Y coordinates of the (X,Y) data sets.
numberOfElements integer Number of sample points used in the linear fit operation.
Output
Name Type Description
outputArray double-precision array The linear values that best represent the data.
slope double-precision Slope of line that best describes the data set.
intercept double-precision Y-intercept value that best represents the data.
meanSquaredError double-precision The mean squared error generated by the difference between the fitted curve and the raw data.

Return Value

Name Type Description
status AnalysisLibErrType A value that specifies the type of error that occurred. Refer to analysis.h for definitions of these constants.