The number of automobile accidents a driver will be involved in during a one-year period is a random variable Y having a Poisson distribution with parameter X, where X depends on the driver. Suppose a driver is chosen at random from some population and hence X itself is a
continuous random variable with p.d.f f(x) , 0 < x < ∞
(a) Show that P(Y=k)= int o ^ infty P(Y=k|X=x)f(x)dx
(b) Suppose that x has an exponential distribution with mean 1/c where c is a
positive constant. Obtain the distribution of Y, hence find the expectation of Y.
"a:\\\\P\\left( Y=k \\right) =EI\\left\\{ Y=k \\right\\} =E\\left( E\\left( I\\left\\{ Y=k \\right\\} |X \\right) \\right) \\\\E\\left( I\\left\\{ Y=k \\right\\} |X \\right) =P\\left( Y=k|X \\right) =h\\left( X \\right) \\\\P\\left( Y=k \\right) =Eh\\left( X \\right) =\\int_0^{+\\infty}{h\\left( x \\right) f\\left( x \\right) dx}=\\int_0^{+\\infty}{P\\left( Y=k|X=x \\right) f\\left( x \\right) dx}\\\\b:\\\\P\\left( Y=k \\right) =\\int_0^{+\\infty}{\\frac{x^ke^{-x}}{k!}\\cdot ce^{-cx}dx}=\\frac{c}{k!}\\int_0^{+\\infty}{x^ke^{-\\left( c+1 \\right) x}dx}=\\\\=\\left[ \\left( c+1 \\right) x=y \\right] =\\frac{c}{\\left( c+1 \\right) ^{k+1}k!}\\int_0^{+\\infty}{y^ke^{-y}dy}=\\frac{c}{\\left( c+1 \\right) ^{k+1}k!}\\varGamma \\left( k+1 \\right) =\\frac{c}{\\left( c+1 \\right) ^{k+1}}=\\\\=\\left( 1-\\frac{c}{c+1} \\right) ^k\\left( \\frac{c}{c+1} \\right) \\sim Geom\\left( \\frac{c}{c+1} \\right) \\Rightarrow \\\\\\Rightarrow EY=\\frac{1-\\frac{c}{c+1}}{\\frac{c}{c+1}}=\\frac{1}{c}"
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