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.
Arguments:
vx and 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
3 data points for logfit, and at least 2 for lnfit.
vg is a three-element
vector of real guess values for the parameters a,
b, and c in the logarithmic
fit equation.
Notes:
To further analyze your data, or determine the suitability
of a linear regression, you may wish to apply other statistics
functions for data analysis.
If you wish to do a logarithmic fit that differs
from the forms above, use genfit or linfit.