The red line is a linear fit to the global mean data demonstrating a fairly constant annual growth rate of 0.24 ppt per year.

Other types of integral linearity place constraints on the symmetry or end points of the linear fit with respect to the actual data.

Transform is computed by linear fit to a subfamily of functions corresponding to constraints on a reasonable solution.

This can be found by doing a linear fit to the to hold time data.

The single coefficient of this linear fit was multiplied with the average difference values for each gene on the array to yield initial frequency estimates.

The slope of the linear fit is equal to the .

Time series of surface temperature and total sky cover for Barrow (1965-1995) with linear fits superimposed (thin solid lines).

Corresponding thin lines are linear fits to monthly values.

The estimated coefficients from this linear fit are used as the starting values for fitting the nonlinear model to the full data set.

A linear fit is specified in the model above, but this can be replaced with a more elaborate function if needed.