[SciPy-user] Error in nonlinear least squares fit analysis

[David Lonie]

> leastsq(full_output=True) will also return an estimate of the
> covariance matrix in recent (probably > 0.6) SVN versions of scipy.

This sounds like what I'm looking for -- just to make sure I'm looking
at this right, the diagonal terms of the covariance matrix represent
the variance in the parameters? I.e., for the error in a exponential
fit y = coef[0]*e**(coef[1]*x), the error for coef[1] would be the
sqrt of leastsq's cov_x[1][1], and I can return the best value of the
parameter as:

coef[1] +/- sqrt(cov_x[1][1]) ?

This may be a simple question, but I'm having great difficulty finding
a source that explains the meaning of all of these various matricies
:)

Thanks for the help,

Dave