a) Suppose that, for -1 ≤ a ≤ 1, the probability density function of (X₁, X₂) is given by f(x₁, x₂) = {11- ([1-a(1-2e-x1)(1-2e-₂)]e*₁-*₂ otherwise ,0 ≤ x₁,0 ≤ x₂. i) Find the marginal distribution of X₁. ii) Find E(X₁X₂).
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- The random variables X and Y have a joint probability density function given by f(x, y) = way, 0 < x < 3 and 1 < y < x, and 0 otherwise.a) Suppose that, for -1 ≤ a ≤ 1, the probability density function of (X₁, X₂) is given by f(x₁,x₂)= = = [[1-a(1-2e-1)(1-2e-*²)]e*1-*2 0, ,0 ≤ x₁,0 ≤ x₂. otherwise i) Find the marginal distribution of X₁. ii) Find E(X₁X₂).Let X1, X2, ..., Xn be a sample of n units from a population with a probability density function f (x I θ)=θxθ-1 , 0<x<1, θ>0 . According to this: Examine whether {f (x I θ)=θxθ-1 , 0<x<1: θ>0 } family of distributions has exponential family property.
- Let f, g be probability densities such supp(f) c supp(g). show yes X1, ... , Xn X1,..., X, iid. L(g) then f(X;) W; = g(X;) is hopeful 1. Argue why the weights need to be re-normalized even when the normalization constants of the densities f and g are known.Let X be the random variable having pdf f(x) = 1,0 < x < 1, zero e.w. Compute the probability of the range of the random sample of size 4 (X1, ., X4) is less than 1/2. Hint: Range is R = X(4) – X(1).The probability density function of a distribution is given by x f(x) = exp(-7). Use differentiation to show that the probability density function has a maximum at x = 0. The moment generating function of a distribution is M(t) = (q + pet)", where p € [0, 1], q = 1 - p and n is a positive integer. Use the moment generating function to find the mean and variance of the distribution in terms of p, q and n.
- Suppose that, for -1 ≤ a ≤ 1, the probability density function of (X₁, X₂) is given by f(x₁, x₂) = {11 [1-a(1-2e-x₁)(1 - 2e-x2)]ex1-x2 otherwise ,0 ≤ x₁,0 ≤ x₂. i) Find the marginal distribution of X₁. ii) Find E(X₁X₂).a) Suppose that, for -1 ≤ a ≤ 1, the probability density function of (X₁, X₂) is given by f(x₁, x₂) = {[1- -a(1-2e-*₁) (1 - 2e-x²)]e*1-*2 otherwise ,0 ≤ x₁,0 ≤ x₂. i) Find the marginal distribution of X₁. ii) Find E(X₁X₂). b) Consider a random variable K with parameter p, whose probability mass function (PMF) is given by f(k) pqk-1, k=1,2,. = lo, elsewhere i) Derive the moment generating function of K. ii) Use the result obtained in i), to find the expected value of K. iii) Use the result obtained in i), to find the variance of value of K.7. Let X and Y be continuous random variables with joint probability density function given by fxy(xy): Sc, (0, 0 < x < y < 1 otherwise a) Find the value of c. b) Find the marginal distributions of X and Y. c) Find the conditional distribution of Y given X. d) Find the E(Y) and Var(Y).