How to calculate standard errors for estimated parameters for a 3-parameter Weibull Distribution?


The example discussed below provides a code for estimating parameters of a three-parameter weibull distribution. I am interested in calculating the standard errors of these estimated parameters, can anyone please tell me how to proceed?

Link to matlab example: <>

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One method is to use Fisher information; another method is to use bootstrapping. Google will explain these if you are not already familiar with them.

Here is some code implementing each method:

%%Demo showing 2 methods of computing standard errors of 3-parameter Weibull distribution.
% Both methods require Cupid available at
% Method 2 also requires RawRT available at
% Here are some sample data to be used for this demo.
myDist = Weibull(550,1.9,300); % Arbitrary parameter values to generate some data.
data = myDist.Random(300,1); % Replace this with your own data.
figure; histogram(data);
%%Method 1: Estimate SEs using Fisher Information
myDist = Weibull(500,1.8,200); % Use your best guesses for the initial parameter values.
myDist.EstML(data); % Estimate the parameter values.
estparms = myDist.ParmValues;
[SEs, Cov] = myDist.MLSE(data,'rrr'); % This step computes the standard errors.




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