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2.7(難) 連続確率変数の期待値と分布関数の関係

Last updated at Posted at 2021-07-15

1.方針

初見で解くのは不可能.

\begin{align}
x=
\begin{cases}
\int_0^xdt,\ \ \ \ \ \ \ \mathrm{if}\ 0<x\\
-\int_x^0dt,\ \ \ \ \mathrm{if}\ x<0
\end{cases}
\end{align}

であることを用いる.

1.答案

\begin{align}
\mathbb{E}_{X\sim f_X}[X]&= \int_{-\infty}^\infty xf_X(x)dx\\
&= \int_0^\infty xf_(x)dx+\int_{-\infty}^0xf_X(x)dx\\
&= \int_0^\infty\{\int_0^xdt f_X(x)\}dx+\int_{-\infty}^0\{-\int_x^0dtf_X(x)\}dx\\
&= \int_0^\infty dx\int_0^xdtf_X(x)-\int_{-\infty}^0dx\int_x^0dtf_X(x)\\
&= \int_0^\infty dt\int_t^\infty dxf_X(x)-\int_{-\infty}^0dt\int_{-\infty}^tdxf_X(x)\\
&= \int_0^\infty\{\int_t^\infty f_X(x)dx\}dt-\int_{-\infty}^0\{\int_{-\infty}^tf_X(x)dx\}dt\\
&= \int_0^\infty \{1-F_X(x)\}dx-\int_{-\infty}^0F_X(x)dx
\end{align}

2.方針

逆関数になっているのは嫌なので,

\begin{align}
x=F^{-1}_X(t)&\Leftrightarrow t=F_X(x)\\
&\Leftrightarrow t=P[X\leq x]
\end{align}

と置換する.t→xの置換のため,

\frac{dt}{dx}=f_X(x)\Rightarrow dt=f_X(x)dx

を用いる.

2.答案

x=F^-1(t)と置換する.

\int_0^1F_X^{-1}(t)dt=\int_{-\infty}^\infty xf_X(x)dx=\mathbb{E}_{X\sim f_X}[X]

参考文献

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