Let X and Y be independent random variables, X~ Poisson(y) and Y~ Poisson (X); that is, for every pair of integers (i, j) such that 0 ≤ i and 0 ≤ j, P((X= i) n (Y = j)) = P(X = i) x P(Y = j). (a) Let S be the support of the random variable X + Y. Explicitly identify S. (b) For any k € S, find P(X + Y = k). (c) Fix k € S. For i > 0, find P(X = i| X + Y = k).

MATLAB: An Introduction with Applications
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Let X and Y be independent random variables, X~ Poisson(7) and Y~
Poisson (y) and Y~ Poisson (X);
that is, for every pair of integers (i, j) such that 0 ≤ i and 0 ≤ j,
P((X = i) n (Y = j)) = P(X = i) × P(Y = j).
(a) Let S be the support of the random variable X + Y. Explicitly identify S.
(b) For any k = S, find P(X + Y = k).
(c) Fix k € S. For i≥ 0, find P(X= i| X + Y = k).
(d) For k = S, let g : S → ( — ∞, + ∞) be a function defined by g(k) = E(Tk), where
for m≥ 0, T is the random variable such that P(T = m) = P(X= m X + Y = k).
Derive a simple algebraic expression for g(k).
(e) Find E[g(X + Y)].
(f) Find Var[g(X + Y)].
(g) For k = S, let h : S → ( − ∞, + ∞) be a function defined by h(k) = Var(Tk).
Derive a simple algebraic expression for h(k).
(h) Find E[h(X+Y)].
(i) Obtain a simple expression for E[h(X + Y)] + Var[g(X + Y)].
Transcribed Image Text:Let X and Y be independent random variables, X~ Poisson(7) and Y~ Poisson (y) and Y~ Poisson (X); that is, for every pair of integers (i, j) such that 0 ≤ i and 0 ≤ j, P((X = i) n (Y = j)) = P(X = i) × P(Y = j). (a) Let S be the support of the random variable X + Y. Explicitly identify S. (b) For any k = S, find P(X + Y = k). (c) Fix k € S. For i≥ 0, find P(X= i| X + Y = k). (d) For k = S, let g : S → ( — ∞, + ∞) be a function defined by g(k) = E(Tk), where for m≥ 0, T is the random variable such that P(T = m) = P(X= m X + Y = k). Derive a simple algebraic expression for g(k). (e) Find E[g(X + Y)]. (f) Find Var[g(X + Y)]. (g) For k = S, let h : S → ( − ∞, + ∞) be a function defined by h(k) = Var(Tk). Derive a simple algebraic expression for h(k). (h) Find E[h(X+Y)]. (i) Obtain a simple expression for E[h(X + Y)] + Var[g(X + Y)].
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