====== 베타분포 (Beta Distribution) ====== ===== 정의 ===== ===== 표기 ===== $$ X \sim Be(\alpha , \beta)$$ * $$ \alpha \in ( \ 0 \ , \ \infty \ ) $$ * $$ \beta \in ( \ 0 \ , \ \infty \ ) $$ ===== 받침 ===== $$ x \in [ \ 0 \ , \ 1 \ ] $$ ===== 확률밀도함수 ===== $$f(x)= \left[ \frac{\Gamma(\alpha+\beta)}{\Gamma(\alpha)\Gamma(\beta)} \right] x^{a-1}(1-x)^{\beta-1} $$ (1) 그래프 : $\alpha \ \mathrm{or} \ \beta \ = \ 1$ (2) 그래프 : $\alpha \ = \ \beta \ < \ 1$ (3) 그래프 : $\alpha \ = \ \beta > 1$ (4) 그래프 : $1 \ < \ \alpha \ < \ \beta \ \mathrm{or} \ 1 \ < \ \beta \ < \ \alpha$ set title "Beta Distribution PDF (1)" set size 1.0 set xrange [0:1] set yrange [0:5] set format x "%.1f" set format y "%.2f" set xlabel "x" set ylabel "f(x)" f(x,a,b) = (gamma(a+b)/(gamma(a)*gamma(b)))*(x**(a-1))*((1-x)**(b-1)) plot f(x,1,1) title "Be(1,1)", \ f(x,0.5,1) title "Be(0.5,1)", \ f(x,1,0.5) title "Be(1,0.5)", \ f(x,2,1) title "Be(2,1)", \ f(x,1,2) title "Be(1,2)", \ f(x,4,1) title "Be(4,1)", \ f(x,1,4) title "Be(1,4)" set title "Beta Distribution PDF (2)" set size 1.0 set xrange [0:1] set yrange [0:5] set format x "%.1f" set format y "%.2f" set xlabel "x" set ylabel "f(x)" f(x,a,b) = (gamma(a+b)/(gamma(a)*gamma(b)))*(x**(a-1))*((1-x)**(b-1)) plot f(x,0.9,0.9) title "Be(0.9,0.9)", \ f(x,0.7,0.7) title "Be(0.7,0.7)", \ f(x,0.5,0.5) title "Be(0.5,0.5)", \ f(x,0.3,0.3) title "Be(0.3,0.3)", \ f(x,0.1,0.1) title "Be(0.1,0.1)" set title "Beta Distribution PDF (3)" set size 1.0 set xrange [0:1] set yrange [0:5] set format x "%.1f" set format y "%.2f" set xlabel "x" set ylabel "f(x)" f(x,a,b) = (gamma(a+b)/(gamma(a)*gamma(b)))*(x**(a-1))*((1-x)**(b-1)) plot f(x,2,2) title "Be(2,2)", \ f(x,4,4) title "Be(4,4)", \ f(x,6,6) title "Be(6,6)", \ f(x,8,8) title "Be(8,8)", \ f(x,10,10) title "Be(10,10)" set title "Beta Distribution PDF (4)" set size 1.0 set xrange [0:1] set yrange [0:5] set format x "%.1f" set format y "%.2f" set xlabel "x" set ylabel "f(x)" f(x,a,b) = (gamma(a+b)/(gamma(a)*gamma(b)))*(x**(a-1))*((1-x)**(b-1)) plot f(x,2,4) title "Be(2,4)", \ f(x,2,6) title "Be(2,6)", \ f(x,2,8) title "Be(2,8)", \ f(x,4,2) title "Be(4,2)", \ f(x,6,2) title "Be(6,2)", \ f(x,8,2) title "Be(8,2)" ===== 누적분포함수 ===== $$ F(x) = I( \ x \ ; \ \alpha \ , \ \beta \ ) $$ * 단, $I( \ x \ ; \ \alpha \ , \ \beta \ )$는 [[정칙 베타함수]]이다. (1) 그래프 : $\alpha \ \mathrm{or} \ \beta \ = \ 1$ (2) 그래프 : $\alpha \ = \ \beta \ < \ 1$ (3) 그래프 : $\alpha \ = \ \beta > 1$ (4) 그래프 : $1 \ < \ \alpha \ < \ \beta \ \mathrm{or} \ 1 \ < \ \beta \ < \ \alpha$ set title "Beta Distribution CDF (1)" set size 1.0 set xrange [0:1] set yrange [0:1.1] set format x "%.1f" set format y "%.2f" set xlabel "x" set ylabel "F(x)" f(x,a,b) = ibeta(a,b,x) plot f(x,1,1) title "Be(1,1)", \ f(x,0.5,1) title "Be(0.5,1)", \ f(x,1,0.5) title "Be(1,0.5)", \ f(x,2,1) title "Be(2,1)", \ f(x,1,2) title "Be(1,2)", \ f(x,4,1) title "Be(4,1)", \ f(x,1,4) title "Be(1,4)" set title "Beta Distribution CDF (2)" set size 1.0 set xrange [0:1] set yrange [0:1.1] set format x "%.1f" set format y "%.2f" set xlabel "x" set ylabel "F(x)" f(x,a,b) = ibeta(a,b,x) plot f(x,0.9,0.9) title "Be(0.9,0.9)", \ f(x,0.7,0.7) title "Be(0.7,0.7)", \ f(x,0.5,0.5) title "Be(0.5,0.5)", \ f(x,0.3,0.3) title "Be(0.3,0.3)", \ f(x,0.1,0.1) title "Be(0.1,0.1)" set title "Beta Distribution CDF (3)" set size 1.0 set xrange [0:1] set yrange [0:1.1] set format x "%.1f" set format y "%.2f" set xlabel "x" set ylabel "F(x)" f(x,a,b) = ibeta(a,b,x) plot f(x,2,2) title "Be(2,2)", \ f(x,4,4) title "Be(4,4)", \ f(x,6,6) title "Be(6,6)", \ f(x,8,8) title "Be(8,8)", \ f(x,10,10) title "Be(10,10)" set title "Beta Distribution CDF (4)" set size 1.0 set xrange [0:1] set yrange [0:1.1] set format x "%.1f" set format y "%.2f" set xlabel "x" set ylabel "F(x)" f(x,a,b) = ibeta(a,b,x) plot f(x,2,4) title "Be(2,4)", \ f(x,2,6) title "Be(2,6)", \ f(x,2,8) title "Be(2,8)", \ f(x,4,2) title "Be(4,2)", \ f(x,6,2) title "Be(6,2)", \ f(x,8,2) title "Be(8,2)" ===== 기대값 ===== $$E(X)=\frac{\alpha}{\alpha+\beta}$$ ===== 분산 ===== $$Var(X)=\frac{\alpha\beta}{(\alpha+\beta)^{2}(\alpha+\beta+1)}$$ ===== 왜도 ===== $$ \gamma_{1} = \frac{2(\beta - \alpha) \sqrt{1 + \alpha + \beta}}{\sqrt{\alpha \beta} (2 + \alpha + \beta)} $$ ===== 첨도 ===== $$ \gamma_{2} = \frac{6 \left[ \alpha^{3} + \alpha^{2} (1 - 2 \beta) + \beta^{2} (1 + \beta) - 2 \alpha \beta (2 + \beta) \right] }{\alpha \beta (\alpha + \beta + 2) (\alpha + \beta + 3)} $$ ===== 특성함수 ===== $$ \phi \ (t) = \ _{1}F_{1} (\alpha \ ; \ \alpha + \beta \ ; \ i \cdot t) $$ ===== 원적률 ===== $$ \mu'_{k} = \frac{\Gamma (\alpha + \beta) \cdot \Gamma (\alpha + k)}{\Gamma (\alpha + \beta + k) \cdot \Gamma (\alpha)} $$ ===== 중심적률 ===== $$ \mu_{k} = \left( - \frac{\alpha}{\alpha + \beta} \right)^{k} \ _{2}F_{1} \left( -k \ , \ \alpha \ ; \ \alpha + \beta \ ; \ \frac{\alpha + \beta}{\alpha} \right) $$ ---- * [[분포]] * [[연속형 분포]]