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Difference between revisions of "Dirichlet distribution"

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====References====
 
====References====
 
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<TR><TD valign="top">[1]</TD> <TD valign="top">  S.S. Wilks,  "Mathematical statistics" , Wiley  (1962)</TD></TR>
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<TR><TD valign="top">[1]</TD> <TD valign="top">  S.S. Wilks,  "Mathematical statistics" , Wiley  (1962) {{ZBL|0173.45805}}</TD></TR>
 
<TR><TD valign="top">[a1]</TD> <TD valign="top">  T.S. Ferguson,  "A Bayesian analysis of some nonparametric problems"  ''Ann. Stat.'' , '''1'''  (1973)  pp. 209–230</TD></TR>
 
<TR><TD valign="top">[a1]</TD> <TD valign="top">  T.S. Ferguson,  "A Bayesian analysis of some nonparametric problems"  ''Ann. Stat.'' , '''1'''  (1973)  pp. 209–230</TD></TR>
 
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Latest revision as of 08:57, 8 April 2023


A probability distribution on the simplex

$$ S _ {k} = \{ {( x _ {1}, \dots, x _ {k} ) } : {x _ {1} > 0, \ldots, x _ {k} > 0 , x _ {1} + \dots + x _ {k} = 1 } \} , $$

where $ k= 2, 3 \dots $ determined by the probability density

$$ p ( x _ {1}, \dots, x _ {k} ) = \left \{ \begin{array}{ll} C _ {k} \prod _ { i=1 } ^ { k } x _ {i} ^ {\nu _ {i} - 1 } & \textrm{ if } ( x _ {1}, \ldots, x _ {k} ) \in S _ {k} , \\ 0 & \textrm{ if } ( x _ {1}, \ldots, x _ {k} ) \notin S _ {k} , \\ \end{array} \right .$$

where $ \nu _ {1} > 0, \dots, \nu _ {k} > 0 $ and

$$ C _ {k} = \Gamma ( \nu _ {1} + \dots + \nu _ {k} ) \prod _ { i=1 } ^ { k } \frac{1}{\Gamma ( \nu _ {i} ) } , $$

where $ \Gamma ( \cdot ) $ is the gamma-function. If $ k= 2 $, one has a special case of the Dirichlet distribution: the beta-distribution. The Dirichlet distribution plays an important role in the theory of order statistics. For instance, if $ X _ {1}, \ldots, X _ {n} $ are independent random variables that are uniformly distributed over the interval $ [ 0, 1] $ and $ X ^ {( 1)} \leq \dots \leq X ^ {( n)} $ are the corresponding order statistics (cf. Order statistic), the joint distribution of the $ k $ differences

$$ X ^ {( m _ {1} ) } , X ^ {( m _ {2} ) } - X ^ {( m _ {1} ) }, \ldots, X ^ {( m _ {k-1} ) } - X ^ {( m _ {k-2} ) } , 1 - X ^ {( m _ {k} ) } $$

(it is assumed that $ 1 \leq m _ {1} < m _ {2} < \dots < m _ {k-1} $) has the Dirichlet distribution with $ \nu _ {1} = m _ {1} $, $ \nu _ {2} = m _ {2} - m _ {1}, \ldots, \nu _ {k-1} = m _ {k-1} - m _ {k-2} $, $ \nu _ {k} = n - m _ {k-1} $.

References

[1] S.S. Wilks, "Mathematical statistics" , Wiley (1962) Zbl 0173.45805
[a1] T.S. Ferguson, "A Bayesian analysis of some nonparametric problems" Ann. Stat. , 1 (1973) pp. 209–230
How to Cite This Entry:
Dirichlet distribution. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Dirichlet_distribution&oldid=53636
This article was adapted from an original article by L.N. Bol'shev (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article