Usage: |
{db,de,vb,ve,w2b,w2e,a2b,a2e,beta,tau,betamin,taumin,likconv} = estWeibull(analyzedsample,method,numberofiterations)
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Input: |
| analyzedsample | n x 1 vector, sample for which Weibull distribution parameters will be estimated.
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| method | integer, estimation method selection flag (0 - all methods, 1 - ML, 2 - A2).
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| numberofiterations | integer, number of iterations for minimization procedures.
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Output: |
| db | scalar, Value of Kolmogorov statistic for ML parameters. |
| de | scalar, Value of Kolmogorov statistic for A2 parameters. |
| vb | scalar, Value of Kuiper statistic for ML parameters. |
| ve | scalar, Value of Kuiper statistic for A2 parameters. |
| w2b | scalar, Value of Cramer-von Mises statistic for ML parameters. |
| w2e | scalar, Value of Cramer-von Mises statistic for A2 parameters. |
| a2b | scalar, Value of Anderson-Darling statistic for ML parameters. |
| a2e | scalar, Value of Anderson-Darling statistic for A2 parameters. |
| beta | scalar, Parameter beta from ML estimation. |
| tau | scalar, Parameter tau from ML estimation. |
| betamin | scalar, Parameter beta from A2 estimation. |
| taumin | scalar, Parameter tau from A2 estimation. |
| likconv | scalar, 1 - if ML estimation converged, 0 - otherwise. |