Statistical distribution
Fisher's z-distribution is the statistical distribution of half the logarithm of an F-distribution variate:
It was first described by Ronald Fisher in a paper delivered at the International Mathematical Congress of 1924 in Toronto.[1] Nowadays one usually uses the F-distribution instead.
The probability density function and cumulative distribution function can be found by using the F-distribution at the value of . However, the mean and variance do not follow the same transformation.
The probability density function is[2][3]
where B is the beta function.
When the degrees of freedom becomes large (), the distribution approaches normality with mean[2]
and variance
- If then (F-distribution)
- If then
References
External links
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Discrete univariate | with finite support | |
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with infinite support | |
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Continuous univariate | supported on a bounded interval | |
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supported on a semi-infinite interval | |
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supported on the whole real line | |
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with support whose type varies | |
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Mixed univariate | |
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Multivariate (joint) | |
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Directional | |
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Degenerate and singular | |
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Families | |
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