In details plz Thank you! Suppose that X ~ Gamma(a, b) and Y ~ Chisquare(k) and X and Y are independent. Îet w = X+Y (a) Find the MGF of W. / (b) For what value(s) of b would W be a Gamma Random Vari...
1. Suppose X ∼ Gamma(a,b) and Y ∼ Gamma(c,d). Furthermore suppose X and Y are independent. Let W = X + Y . (a) Find the MGF of W. (b) What restrictions would need to be placed on the values of a, b, c, and d in order for W to be a Gamma Random Variable. What would the parameters be?
Suppose X Gamma (a; b) and YGamma (c; d). Let W-X+Y. (a) Find the MGF of w. (b) What restrictions would need to be placed on the values of a, b; c; and d for Ww to be a Gamma Random Variable. What would the parameters be?
Suppose X ∼ Gamma(a, b) and Y ∼ Gamma(c, d). Let W = X + Y . (a) Find the MGF of W. (b) What restrictions would need to be placed on the values of a, b, c, and d in order for W to be a Gamma Random Variable. What would the parameters be?
uppose XGamma(a, b) and Y Gamma(c,d). Let W -X +Y. (a) Find the MGF of W. b) What restrictions would need to be placed on the values of a, b, c, and d in order for W to be a Gamma Random Variable. What would the parameters be?
The moment generating function (MGF) for a random variable X is: Mx (t) = E[e'X]. Onc useful property of moment generating functions is that they make it relatively casy to compute weighted sums of independent random variables: Z=aX+BY M26) - Mx(at)My (Bt). (A) Derive the MGF for a Poisson random variable X with parameter 1. (B) Let X be a Poisson random variable with parameter 1, as above, and let y be a Poisson random variable with parameter y. X...
Having troubles with question 2. Please help 2. If X has a Gamma distribution with parameters a and B, then its mgf is given by (a) Obtain expressions for the moment-genérating functions of an exponential random variable and of a chi-square random variable by recognizing that these are special cases of a Gamma distribution and using the mgf given above. (b) Suppose that X1 is a Gamma variable with parameters α1 and β, X2 is a Gamma variable with parameters...
(1 point) In Unit 3, I claimed that the sum of independent, identically distributed exponential random variables is a gamma random variable. Now that we know about moment generating functions, we can prove it. Let X be exponential with mean A 4. The density is 4 a) Find the moment generating function of X, and evaluate at t 3.9 The mgf of a gamma is more tedious to find, so l'll give it to you here. Let W Gamma(n, A...
Suppose that random variables X and Y are independent. Further, X is an exponential random variable with parameter 1 = 3, and Y is an uniformly distributed random variable on the interval (0,4). Find the correlation between X and Y, rounded to nearest .xx
I. Let X be a random sample from an exponential distribution with unknown rate parameter θ and p.d.f (a) Find the probability of X> 2. (b) Find the moment generating function of X, its mean and variance. (c) Show that if X1 and X2 are two independent random variables with exponential distribution with rate parameter θ, then Y = X1 + 2 is a random variable with a gamma distribution and determine its parameters (you can use the moment generating...
A random variable X has the following mgf et M(t)=1−t, t<1. (a) Find the value of ∞ (−1)k E(Xk). (b) Find the value of E(2−X). (c) Find the value of Var(2−X). (d) Find the probability P (X > 4). 10. A random variable X has the following mgf М() t 1 1 t (a) Find the value of 1E(Xk) (b) Find the value of E(2X). (c) Find the value of Var(2-X) k 0 k! (d) Find the probability P(X >...