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4.6 (標準) 二変数確率変数の変数変換2 一様分布に従う確率変数の和,積 (畳み込み)

Last updated at Posted at 2021-10-18

方針

\begin{align}
\begin{cases}
Z=X+Y\\
W=XY
\end{cases}
\end{align}

という変換では一対一にならない (X=,Y=,と一意に書けない) ため,Z,Wそれぞれを畳み込みで求める.それぞれの定義域に注意.

答案

\begin{align}
\begin{cases}
Z=X+Y\\
V=Y
\end{cases}\Leftrightarrow
\begin{cases}
X=Z-V\\
Y=V
\end{cases}
\end{align}

なる一対一変換を考える.

\begin{align}
f_{Z,V}(z,v)&= f_X(z-v)f_Y(v)\\
\therefore f_Z(z)&= \int f_X(z-v)f_Y(v)dv,\ \ \ (0<v<1,0<z-v<1)
\end{align}

zの値によって積分範囲が変わるため,場合分けして求める.0<z<1の時,0<v<zより

f_Z(z)=\int_0^zdv=z

1<z<2の時,z-1<v<1より,

f_Z(z)=\int_{z-1}^1dv=2-z

次に,

\begin{align}
\begin{cases}
W=XY\\
U=Y
\end{cases}\Leftrightarrow
\begin{cases}
X=W/U\\
Y=U
\end{cases}
\end{align}

なる一対一変換を考える.

\left|\frac{\partial (X,Y)}{\partial(W,U)}\right|=\left|\begin{pmatrix}
1/u & -w/u^2\\
0 & 1
\end{pmatrix}\right|=\frac{1}{u}

なので,

\begin{align}
f_{W,U}(w,u)&= f_X(\frac{w}{u})f_Y(u)\frac{1}{u}\\
\therefore f_W(w)&= \int f_X(\frac{w}{u})f_Y(u)\frac{1}{u}du,\ \ (0<\frac{w}{u}<1,0<u<1)
\end{align}

ゆえ,w<u<1であるから,

f_W(w)=\int_w^1\frac{1}{u}du=-\log w

参考文献

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