MLEst {EWGoF} | R Documentation |
This function computes the Maximum Likelihood Estimators (MLEs) of the shape and scale parameters of the Weibull distribution from an i.i.d sample x. It also gives the sample \hat{y} after using the logarithmic transformation (\hat{y}=(\hat{shape})\ln(x/\hat{scale}), where \hat{shape} and \hat{scale} are the estimated shape and scale parameters).
MLEst(x)
x |
a numeric vector of data values. |
The elements of the numeric vector should be positive. The support of the Weibull distribution is R+*.
A list containing the following elements:
eta |
the maximum likelihood estimator of the scale parameter of the Weibull distribution (\hat{scale}). |
beta |
the maximum likelihood estimator of the shape parameter of the Weibull distribution (\hat{shape}). |
y |
the pseudo-observations \hat{y} after using the logarithmic transformation and the MLEs. |
Meryam KRIT
D'Agostino R.B. and Stephens M.A., Goodness-of-fit techniques, Marcel Dekker, 1986.
Krit M., Gaudoin O., Xie M. and Remy E., Simplified likelihood goodness-of-fit tests for the Weibull distribution, Communications in Statistics - Simulation and Computation.
x <- rweibull(50,2,3) Est <- MLEst(x) #Value of the maximum likelihood estimator of the scale parameter Est$eta #Value of the maximum likelihood estimator of the shape parameter Est$beta