#StackBounty: #confidence-interval #maximum-likelihood #quantiles #uncertainty #error-propagation Uncertainty propagation for the solut…

Bounty: 50

I have a dataset and I use Maximum Likelihood Estimation to estimate the values of the parameters of a weibull distribution. The MLE theory provides with theoretical Confidence Intervals (asymptotical, or for $n$ samples).

Then, I use the fitted Weibull distribution in an expression which is currently optimised numerically :

$Y(t_0) = h(t_0) . int_{0}^{t_0} S(t) dt + S(t_0)$

Where $t_0$ is unknown and $h$ and $S$ are the hazard function and the survival function of the distribution, and therefore are functions of the parameters.

I would like to propagate uncertainty on the fitted weibull parameters to estimate confidence intervales or quantiles for Y(t_0), how could I do that (numerically or analytically) ?
Thanks !


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