다항분포 (multinominal distribution)
- 이항분포의 확장이라고 생각하면 된다.
\begin{bmatrix}
Y_{1} \\
Y_{2} \\
\end{bmatrix}
\sim
multinominal
(n,
\begin{bmatrix}
Y_{1} \\
Y_{2} \\
\end{bmatrix}
)
P(Y_{1}=y_{1}, Y_{2}=y_{2}) = \dfrac {n!}
{y_{1}!y_{2}!(n-y_{1}-y_{2})!} \,
p_{1}^{y_{1}} \,
p_{2}^{y_{2}} \,
(1-p_{1}-p_{2})^{n-y_{1}-y_{2}}
주변확률함수 구하기
P\,(Y_{1} = y_{1}) =
\sum_{y_{2}=0}^{n-y_{1}}
\,p\,(Y_{1} = y_{1}, \,Y_{2} = y_{2}) \\[20pt]
\begin{align*}
&=
\sum_{y_{2}=0}^{n-y_{1}}~\cdot~
\dfrac {n!}
{y_{1}!~y_{2}!~(n-y_{1}-y_{2})!}~
p_{1}^{y_{1}}~
p_{2}^{y_{2}}~
(1-p_{1}-p_{2})^{n-y_{1}-y_{2}}
\\[20pt]
&=
\frac{n!}{y_{1}!}~\cdot~
p_{1}^{y_{1}}~
\sum_{y_{2}=0}^{n-y_{1}}
\dfrac {n!}
{y_{2}!~(n-y_{1}-y_{2})!}~
p_{2}^{y_{2}}~
(1-p_{1}-p_{2})^{n-y_{1}-y_{2}}
\\[20pt]
&=
\binom{n}{y_{1}}~
p_{1}^{y_{1}}~
\{p_{2} + (1-p_{2}-p_{2})\}
^{n-y_{1}} \\[20pt]
&=
\binom{n}{y_{1}}
~p_{1}^{y_{1}}~
(1-p_{1})^{n-y_{1}}
\end{align*}
그래서, Y_{1} \sim binominal(n, p)이다.