Description Usage Arguments Value Author(s) Examples
Two-parameter Weibull distribution is characterized by the following probability density function,
f(x;λ, k)= \frac{k}{λ} ≤ft( \frac{x}{λ} \right)^{k-1} \exp( -(x/λ)^k )
where the domain is x \in [0,∞) with scale λ > 0 and shape k > 0 parameter.
1 |
x |
a length-n vector of values in [0,∞). |
weight |
a length-n weight vector. If set as |
a named list containing (weighted) MLE of
scale parameter λ.
shape parameter k.
Kisung You
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | # generate data from half-normal
x = abs(stats::rnorm(100))
# fit unweighted
Weibull(x)
## Not run:
# put random weights to see effect of weights
niter = 500
ndata = 200
# generate data and fit unweighted MLE
x = abs(stats::rnorm(ndata))
xmle = Weibull(x)
# iterate
vec.lbd = rep(0,niter)
vec.k = rep(0,niter)
for (i in 1:niter){
# random weight
ww = abs(stats::rnorm(ndata))
MLE = Weibull(x, weight=ww)
vec.lbd[i] = MLE$lambda
vec.k[i] = MLE$k
if ((i%%10) == 0){
print(paste0(" iteration ",i,"/",niter," complete.."))
}
}
# visualize distributions of weighted estimates and MLE
opar <- par(no.readonly=TRUE)
par(mfrow=c(1,2))
hist(vec.lbd, main="scale 'lambda'")
abline(v=xmle$lambda, lwd=3, col="red")
hist(vec.k, main="shape 'k'")
abline(v=xmle$k, lwd=3, col="blue")
par(opar)
## End(Not run)
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