Template:Weibull Probability Density Function
Weibull Probability Density Function
The 3-parameter Weibull pdf is given by:
- [math]\displaystyle{ f(t)={ \frac{\beta }{\eta }}\left( {\frac{t-\gamma }{\eta }}\right) ^{\beta -1}e^{-\left( {\frac{t-\gamma }{\eta }}\right) ^{\beta }} \,\! }[/math]
where:
- [math]\displaystyle{ f(t)\geq 0,\text{ }t\geq \gamma \,\! }[/math]
- [math]\displaystyle{ \beta\gt 0\ \,\! }[/math]
- [math]\displaystyle{ \eta \gt 0 \,\! }[/math]
- [math]\displaystyle{ -\infty \lt \gamma \lt +\infty \,\! }[/math]
and:
- [math]\displaystyle{ \eta= \,\! }[/math] scale parameter, or characteristic life
- [math]\displaystyle{ \beta= \,\! }[/math] shape parameter (or slope)
- [math]\displaystyle{ \gamma= \,\! }[/math] location parameter (or failure free life)
The Two-Parameter Weibull Distribution
The two-parameter Weibull pdf is obtained by setting [math]\displaystyle{ \gamma=0 \,\! }[/math], and is given by:
- [math]\displaystyle{ f(T)={ \frac{\beta }{\eta }}\left( {\frac{T}{\eta }}\right) ^{\beta -1}e^{-\left( { \frac{T}{\eta }}\right) ^{\beta }} \,\! }[/math]
The One-Parameter Weibull Distribution
The one-parameter Weibull pdf is obtained by again setting [math]\displaystyle{ \gamma=0 \,\! }[/math] and assuming [math]\displaystyle{ \beta=C=Constant \,\! }[/math] assumed value or:
- [math]\displaystyle{ f(T)={ \frac{C}{\eta }}\left( {\frac{T}{\eta }}\right) ^{C-1}e^{-\left( {\frac{T}{ \eta }}\right) ^{C}} \,\! }[/math]
where the only unknown parameter is the scale parameter, [math]\displaystyle{ \eta\,\! }[/math].
Note that in the formulation of the one-parameter Weibull, we assume that the shape parameter [math]\displaystyle{ \beta \,\! }[/math] is known a priori from past experience on identical or similar products. The advantage of doing this is that data sets with few or no failures can be analyzed.