Description Usage Arguments Details Value Author(s) References Examples
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).
1 | 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.
1 2 3 4 5 6 7 8 9 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.