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Skew normal distribution : ウィキペディア英語版
Skew normal distribution
\int_^\right)} e^}\ dt|
cdf =\Phi\left(\frac\right)-2T\left(\frac,\alpha\right)
T(h,a) is Owen's T function|
mean =\xi + \omega\delta\sqrt} where \delta = \frac\right)|
skewness =\gamma_1 = \frac \frac\right)^4}|
entropy =|
mgf =M_X\left(t\right)=2\exp\left(\xi t+\frac\right)\Phi\left(\omega\delta t\right)|
cf =M_X\left(i\delta\omega t\right)|
char =|
}}
In probability theory and statistics, the skew normal distribution is a continuous probability distribution that generalises the normal distribution to allow for non-zero skewness.
==Definition==

Let \phi(x) denote the standard normal probability density function
:\phi(x)=\frac}
with the cumulative distribution function given by
:\Phi(x) = \int_^ \phi(t)\ dt = \frac \left(1 + \operatorname \left(\frac. One can verify that the normal distribution is recovered when \alpha = 0, and that the absolute value of the skewness increases as the absolute value of \alpha increases. The distribution is right skewed if \alpha>0 and is left skewed if \alpha<0. The probability density function with location \xi, scale \omega, and parameter \alpha becomes
:f(x) = \frac\phi\left(\frac\right)\Phi\left(\alpha \left(\frac\right)\right). \,
Note, however, that the skewness of the distribution is limited to the interval (-1,1).

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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