hence Y follows Negative binomial distribution marginally.
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3. Let Yx Poisson(j). That is, PY - Y|H) – 4P . Let, Gamma(0,B), i.e., f(x)...
3. Let Yx Poisson(j). That is, PY - Y|H) – 4P . Let, Gamma(0,B), i.e., f04) - - exp(-B). Find the marginal distribution of Y, i.e., find P(Y - y)
(20 points) Consider the following joint distribution of X and Y ㄨㄧㄚ 0 0.1 0.2 1 0.3 0.4 (a) Find the marginal distributions of X and Y. (i.e., Px(x) and Py()) (b) Find the conditional distribution of X given Y-0. (i.e., Pxjy (xY-0)) (c) Compute EXIY-01 and Var(X)Y = 0). (d) Find the covariance between X and Y. (i.e., Cov(X, Y)) (e) Are X and Y independent? Justify your answer. (20 points) Consider the following joint distribution of X and...
iid 14 marksAssume that e Denote T 4i Gamma(k, A) and X1,... , X,,e Poisson(0) (a) [4 marks Show that the posterior distribution of 0 is Gamma(nTk, n ). (b) [4 marks Find the probability function of the marginal distribution of Y = nX. (Note that the conditional distribution of on Y is not the same X1, ..., Xn.) as on iid 14 marksAssume that e Denote T 4i Gamma(k, A) and X1,... , X,,e Poisson(0) (a) [4 marks Show...
10. (a) Find the surface area of the portion of the graph of f(x, y)-yx which is above the region in the xy- plane bounded by y x,y 0 and x.(b) Let f(x)-2 (n+3)2 _____ for each x for which the series o 5" converges. Write a power series in summation notation for an indefinite integral of f. 10. (a) Find the surface area of the portion of the graph of f(x, y)-yx which is above the region in the...
3. Let G1 ∼ Gamma(α1, β) and G2 ∼ Gamma(α2, β) and let G1 and G2 be independent. Define B1 = G1/(G1 + G2) and B2 = G1 + G2. (a) Find the joint pdf of (B1, B2). (b) Give the marginal pdf of B1 and identify its distribution. (c) Give the marginal pdf of B2 and identify its distribution.
Let X, Y and Z be three independent Poisson random variable with parameters λι, λ2, and λ3, respectively. For y 0,1,2,t, calculate P(Y yX+Y+Z-t) (Hint: Determine first the probability distribution of T -X +Y + Z using the moment generating function method. Moment generating function for Poisson random variable is given in earlier lecture notes) Let X, Y and Z be three independent Poisson random variable with parameters λι, λ2, and λ3, respectively. For y 0,1,2,t, calculate P(Y yX+Y+Z-t) (Hint:...
3. Let Xi, , Xn be a random sample from a Poisson distribution with p.m.f Assume the prior distribution of Of λ is is an exponential with mean 1, i.e. the prior pdi g(A) e-λ, λ > 0 Note that the exponential distribution is a special gamma distribution; and a general gamma distribution with parameters α > 0 and β > 0 has the pd.f. h(A; α, β)-16(. otherwise Also the mean of a gamma random variable with the pd.f.h(Χα,...
Let X and Y have the joint pdf f(x,y) = e-x-y I(x > 0,y > 0). a. What are the marginal pdfs of X and Y ? Are X and Y independent? Why? b. Please calculate the cumulative distribution functions for X and Y, that is, find F(x) and F(y). c. Let Z = max(X,Y), please compute P(Z ≤ a) = P(max(X,Y) ≤ a) for a > 0. Then compute the pdf of Z.
Let y,p ~iid Exp (0), for i = 1, . . . , n. (p(y|0) for 6 to be Gamma(a, b), tha distribution of θ BeAy). Assume the prior distribution Find the posterior 2. t is, p(0) -ba/ra)ge-i exp{-be. 3. Find the posterior predictive distribution of a future observation in problem 2
Suppose that f(x, y) = cx, for 0 y x 2. (a) Find c. (b) Find P(x > 1 and Y < (c) Find the marginal pdf of X. (d) Find the conditional pdf of Y given that X = x. (e) Find E[Y IX x (f) Find E[E[YX]]. (g) Find Cov(X, Y) (h) Are X and Y independent? Suppose that f(x, y) = cx, for 0 y x 2. (a) Find c. (b) Find P(x > 1 and Y