Weibull distribution

In probability theory and statistics, the Weibull distribution (named after Wallodi Weibull) is a continuous probability distribution with the probability density function

<math> f(x) = (k/\lambda) (x/\lambda)^{(k-1)} e^{-(x/\lambda)^k} \qquad \mbox{for } x>0<math>

where k >0 is the shape parameter and λ > 0 is the scale parameter of the distribution.

The cumulative density function is defined as

<math> F(x) = 1- e^{-(x/\lambda)^k} \qquad \mbox{for } x>0<math>

The Exponential distribution (when k = 1) and Rayleigh distribution (when k = 2) are two special cases of the Weibull distribution.

Weibull distributions are often used to model the time until a given technical device fails. If the failure rate of the device decreases over time, one chooses k < 1 (resulting in a decreasing density f). If the failure rate of the device is constant over time, one chooses k = 1, again resulting in a decreasing function f. If the failure rate of the device increases over time, one chooses k > 1 and obtains a density f which increases towards a maximum and then decreases forever. Manufacturers will often supply the shape and scale parameters for the lifetime distribution of a particular device. The Weibull distribution can also be used to model the distribution of wind speeds at a given location on Earth. Again, every location is characterized by a particular shape and scale parameter.

The expected value and standard deviation of a Weibull random variable can be expressed in terms of the gamma function:

E(X) = λ Γ((k + 1) / k) and

var(X) = λ²[Γ((k + 2) / k) - Γ²((k + 1) / k)]

External links

• The Weibull distribution (with examples, properties, and calulators). (http://www.xycoon.com/Weibull.htm)
• The Weibull plot. (http://www.itl.nist.gov/div898/handbook/eda/section3/weibplot.htm)

sv:Weibullfördelning