library(fitdistrplus)
#Generate fake data
shape <- 1.9
x <- rweibull(n=1000, shape=shape, scale=1)
#Fit x data with fitdist
fit.w <- fitdist(x, "weibull")
summary(fit.w)
plot(fit.w)
Fitting of the distribution ' weibull ' by maximum likelihood
Parameters :
estimate Std. Error
shape 1.8720133 0.04596699
scale 0.9976703 0.01776794
Loglikelihood: -636.1181 AIC: 1276.236 BIC: 1286.052
Correlation matrix:
shape scale
shape 1.0000000 0.3166085
scale 0.3166085 1.0000000