标签:技术分享 tps try variable height other oba not tco
https://www.statlect.com/probability-distributions/multinoulli-distribution3
The Multinoulli distribution (sometimes also called categorical distribution) is a generalization of the Bernoulli distribution. If you perform an experiment that can have only two outcomes (either success or failure), then a random variable that takes value 1 in case of success and value 0 in case of failure is a Bernoulli random variable. If you perform an experiment that can have outcomes and you denote by
a random variable that takes value 1 if you obtain the
-th outcome and 0 otherwise, then the random vector
defined as
is a Multinoulli random vector. In other words, when the
-th outcome is obtained, the
-th entry of the Multinoulli random vector
takes value
, while all other entries take value
.
In what follows the probabilities of the possible outcomes will be denoted by
.
The distribution is characterized as follows.
Definition Let be a
discrete random vector. Let the support of
be the set of
vectors having one entry equal to
and all other entries equal to
:
Let
, ...,
be
strictly positive numbers such that
We say that
has a Multinoulli distribution with probabilities
, ...,
if its joint probability mass function is
If you are puzzled by the above definition of the joint pmf, note that when and
because the
-th outcome has been obtained, then all other entries are equal to
and
The expected value of is
where the
vector
is defined as follows:
The covariance matrix of is
where
is a
matrix whose generic entry is
The joint moment generating function of is defined for any
:
The joint characteristic function of is
标签:技术分享 tps try variable height other oba not tco
原文地址:http://www.cnblogs.com/bnuvincent/p/6629346.html