Robert Kern wrote:
D.Hendriks (Dennis) wrote:
According to (for instance)
http://en.wikipedia.org/wiki/Weibull_distribution the Weibull
distribution has two parameters: lambda > 0 is the scale parameter
(real) and k > 0 is the shape parameter (real). However, the
numpy.random.weibull function has only a single 'a' parameter (except
for the size parameter which indicates the size of the array to fill
with values - this is NOT a parameter of the distribution itself). My
question is how this 'a' parameter translates to the Weibull
distribution as it 'normally' is and how to sample the distribution when
I have the lambda and k parameters?
lambda * numpy.random.weibull(k)
Thanks for the quick replay. However, when I look at the image of the
probability density function at
http://en.wikipedia.org/wiki/Weibull_distribution I see a red line and a
green line, both with k=2. The red line is for lambda=0.5 and the green
for lambda=1.0. The green line is not only half the height of the red
one (while double the lambda factor!), but also has its mean a bit more
to the right. Looking at the formulas on the same page, this makes
sense. All of this makes me doubt the correctness of the formula you
proposed...
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