Hi,
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: <https://in.mathworks.com/help/stats/weibull-distribution.html>
NOTE:-
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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 https://github.com/milleratotago/Cupid % Method 2 also requires RawRT available at https://github.com/milleratotago/RawRT % Here are some sample data to be used for this demo. myDist = Weibull(550,1.9,300); % Arbitrary parameter values to generate some data. myDist.PlotDens; 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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