Difference between revisions of "Weibull distribution"
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= Library = | = Library = | ||
− | + | Distribution | |
+ | |||
+ | = Example = | ||
+ | |||
+ | :Weibull(10,4) → [[Image:Weibull_graph.jpg]] | ||
+ | |||
+ | = Parameter Estimation = | ||
+ | |||
+ | Suppose you have sampled historic data in ''Data'', indexed by ''I'', and you want to find the parameters for the best-fit Weibull distribution. The parameters can be estimated using a linear regression as follows: | ||
+ | |||
+ | [[Index..Do|Index]] bm := ['b','m']; | ||
+ | [[Var..Do|Var]] Fx := ([[Rank]](Data,I) - 0.5) / [[Size]](I); | ||
+ | [[Var..Do|Var]] Z := [[Ln]](-[[Ln]](1-Fx)); | ||
+ | [[Var..Do|Var]] fit := [[Regression]](Z,[[Array]](bm,[1,[[Ln]](x)]),I,bm); | ||
+ | [[Var..Do|Var]] shape := fit[bm='m']; | ||
+ | [[Var..Do|Var]] b := fit[bm='b']; | ||
+ | [[Var..Do|Var]] scale := [[Exp]](-b/shape); | ||
+ | [shape,scale] | ||
= See Also = | = See Also = | ||
* [[Gamma]], [[Normal]] | * [[Gamma]], [[Normal]] |
Revision as of 21:14, 3 March 2009
Weibull( shape, scale )
The Weibull distribution is often used to represent failure time in reliability models. It is similar in shape to the gamma distribution, but tends to be less skewed and tail-heavy. It is a continuous distribution over the positive real numbers.
The Weibull distribution has a cumulative density given by
Library
Distribution
Example
Parameter Estimation
Suppose you have sampled historic data in Data, indexed by I, and you want to find the parameters for the best-fit Weibull distribution. The parameters can be estimated using a linear regression as follows:
Index bm := ['b','m']; Var Fx := (Rank(Data,I) - 0.5) / Size(I); Var Z := Ln(-Ln(1-Fx)); Var fit := Regression(Z,Array(bm,[1,Ln(x)]),I,bm); Var shape := fit[bm='m']; Var b := fit[bm='b']; Var scale := Exp(-b/shape); [shape,scale]
See Also
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