Difference between revisions of "Warp Dist"

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= Warp_dist(dist,fracts,F) =
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== Warp_dist(dist, fracts, F) ==
  
Applies a smooth warping funtion to a given sample so as to obtain the listed fractiles, while maintaining the approximate shape of the distribution.  For example, if you have p10, p50 and p90 percentiles and you want a "Normal-like" distribution, you could use:
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Applies a smooth warping function to a given sample so as to obtain the listed fractiles, while maintaining the approximate shape of the distribution.  For example, if you have p10, p50 and p90 percentiles and you want a "[[Normal]]-like" distribution, you could use:
  
index F:=[10%,50%,90%];
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:<code>Index F := [10%, 50%, 90%];</code>
var pctiles := Array(F,[5,10,20]);
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:<code>Var pctiles := Array(F, [5, 10, 20]);</code>
Warp_dist(Normal(0,1),pctiles,F)
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:<code>Warp_dist(Normal(0, 1), pctiles, F)</code>
  
The resulting distribution will not be a Normal (you can't necessarily obtain a normal with any three fractiles, since Normal has only 2 free parameters), but it will be basically bell-shaped -- skewed a bit to the left to obtain the given fractiles.
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The resulting distribution will not be a [[Normal]] (you can't necessarily obtain a normal with any three fractiles, since Normal has only 2 free parameters), but it will be basically bell-shaped -- skewed a bit to the left to obtain the given fractiles.
  
 
Note that if you were to provide only two fractiles, Normality would be preserved in this example.
 
Note that if you were to provide only two fractiles, Normality would be preserved in this example.
  
= Library =
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== Library ==
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Distribution Variations.ana
  
Distribution Variations.ana
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==See Also==
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* [[Normal]]
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* [[Probability distributions]]
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* [[Distribution Densities Library]]

Revision as of 21:49, 27 January 2016


Warp_dist(dist, fracts, F)

Applies a smooth warping function to a given sample so as to obtain the listed fractiles, while maintaining the approximate shape of the distribution. For example, if you have p10, p50 and p90 percentiles and you want a "Normal-like" distribution, you could use:

Index F := [10%, 50%, 90%];
Var pctiles := Array(F, [5, 10, 20]);
Warp_dist(Normal(0, 1), pctiles, F)

The resulting distribution will not be a Normal (you can't necessarily obtain a normal with any three fractiles, since Normal has only 2 free parameters), but it will be basically bell-shaped -- skewed a bit to the left to obtain the given fractiles.

Note that if you were to provide only two fractiles, Normality would be preserved in this example.

Library

Distribution Variations.ana

See Also

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