Logarithmic Regression
• logfit(vx, vy, vg)—Returns a vector containing the coefficients for a logarithmic curve of the form a · ln(x + b) + c that best approximates the data in vx and vy using guess values in vg.
• lnfit(vx, vy) Returns a vector containing the coefficients for a logarithmic curve of the form a · ln(x) + b that best approximates the data in vx and vy.
The logfit and lnfit functions employ the Levenberg-Marquardt method for minimization. For a logarithmic fit that differs from the forms above, use genfit or linfit.
Arguments
• vx, vy are vectors of real data values of the same length, corresponding to the x and y values in the data set. There must be at least three data points for logfit, and at least two for lnfit.
• vg is a three-element vector of real guess values for the parameters a, b, and c in the logarithmic fit equation.