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・ Compound of two great dodecahedra
・ Compound of two great icosahedra
・ Compound of two great inverted snub icosidodecahedra
・ Compound of two great retrosnub icosidodecahedra
・ Compound of two great snub icosidodecahedra
・ Compound of two icosahedra
・ Compound of two inverted snub dodecadodecahedra
・ Compound of two small stellated dodecahedra
・ Compound of two snub cubes
・ Compound of two snub dodecadodecahedra
・ Compound of two snub dodecahedra
・ Compound of two snub icosidodecadodecahedra
・ Compound of two truncated tetrahedra
・ Compound option
・ Compound pier
Compound Poisson distribution
・ Compound Poisson process
・ Compound presentation
・ Compound prism
・ Compound probability distribution
・ Compound refractive lens
・ Compound S
・ Compound semiconductor
・ Compound shutter
・ Compound spirit of ether
・ Compound squeeze
・ Compound steam engine
・ Compound subject
・ Compound TCP
・ Compound term processing


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Compound Poisson distribution : ウィキペディア英語版
Compound Poisson distribution
In probability theory, a compound Poisson distribution is the probability distribution of the sum of a number of independent identically-distributed random variables, where the number of terms to be added is itself a Poisson-distributed variable. In the simplest cases, the result can be either a continuous or a discrete distribution.
==Definition==

Suppose that
:N\sim\operatorname(\lambda),
i.e., ''N'' is a random variable whose distribution is a Poisson distribution with expected value λ, and that
:X_1, X_2, X_3, \dots
are identically distributed random variables that are mutually independent and also independent of ''N''. Then the probability distribution of the sum of N i.i.d. random variables conditioned on the number of these variables (N):
:Y \mid N=\sum_^N X_n
has a well-defined distribution. In the case ''N'' = 0, then the value of ''Y'' is 0, so that then ''Y'' | ''N'' = 0 has a degenerate distribution.
The compound Poisson distribution is obtained by marginalising the joint distribution of (''Y'',''N'') over ''N'', where this joint distribution is obtained by combining the conditional distribution ''Y'' | ''N'' with the marginal distribution of ''N''.

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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