Scipy Weibull parameter confidence intervals
You could use scipy.optimize.curve_fit to fit the weibull distribution to your data. This will also give you the covariance and thus you can estimate the error of the fitted parameters.
I've been using Matlab to fit data to a Weibull distribution using [paramhat, paramci] = wblfit(data, alpha).  This gives the shape and scale parameters for a Weibull distribution as well as the confidence intervals for each value.
I'm trying to use Scipy to accomplish the sane task and can easily get the parameters with scipy.stats.weibull_min.fit but I cannot figure out a way to get the confidence intervals on the vlauee.  Does Scipy offer this functionality? Or do I need to write the MLE confidence intervals estimation myself?