9)
Here
So, MGF of Y =
Now, U=cY, so MGF of U is
--------(1)
Also, we know the if
, then
----------(2)
On comparing (1) and (2), we get,
9. (5 marks) Consider a Gamma random variable, Y ~ Ganzma(α = n/2, β). Find the...
9. (9 pts) The random variable r-Gamma(x-2, β-4). functions to prove that the moment generating function for the random variable W mw(t) (1-12t)2. Use the method of moment-generating 3Y +5is eSt 10, (9 pts) Suppose that Y has a gamma distribution with α-n/2 for some positive integer n and β equal to some specified value. Use the method of moment-generating functions to prove that W- 2Y /g has a Chi-squared distribution with n degrees of freedom. Make sure you show...
Let Y_1~Gamma(α=3,β=3), Y_2~Gamma(α=5,β=1), and W=2Y_1+6Y_2.
a) (9 pts) Find the moment generating function ofW Justify all steps b) (3 pts) Based on your result in part (a), what is the distribution of W(name and parameters)? n 2N(O, I) 2. IfZ NO, 1), then Ux(1) 3. ItY Gmmaa,B) and W then Wx(n) - s, and i-1 7. y's~ Poisson(W (i-l, ,Rind) and U-ŽYi, then U-Poisson(XA) 8 If%-Gamma(a, β) (i-I, ,Rind) and U-ΣΥί , then U~Gamma( ,4 β).(Note: all same β) 9...
9. (9 pts) The random variable ??~??????????(∝= 2, ?? = 4). Use
the method of moment-generating functions to prove that the moment
generating function for the random variable ?? = 3?? + 5 is
10.
9. (9 pts) The random variable Y-Gamma(α-2. functions to prove that the moment generating function for the random variable W mw(t)120)2 4). Use the method of moment-generating 3Y 5 is est (1-12t)2 10, (9 pts) Suppose that Y has a gamma distribution with α-n/2 for...
Find the moment generating function for the following
distributions: N(μ, σ2),
Poisson(λ), Gamma(α, β), Chi-square with k degrees of freedom, and
Geometric(p).
Question 7: Find the moment generating function for the following distributions: N(Lơ2 Poisson(A), Gamma(α, β), Chi-square with k degrees of freedom, and Geometric(p)
with parameters α and β. 2. Yİ,%, , Y, are a random sample from the Gamma distribution (a) Suppose that α 4 is known and β is unknown. Find a complete sufficient statistic for β. Find the MVUE of β. (Hint: What is E(Y)?) (b) Suppose that β 4 is known and α is unknown. Find a complete sufficient statistic for a.
with parameters α and β. 2. Yİ,%, , Y, are a random sample from the Gamma distribution (a)...
Problem 1. (5 marks. 3. 2) Assume X ~ Gamma(01, β) and Y ~ Gamma(O2, β) are independent random variables. a) Compute the Joint density of U = X + Y and V X X + Y , be sure to include the support/domain. b) Based on the joint density derived in part (a) find the marginal densities of U and V, be sure to include the support (s)/domain(s). Explicitly state the name of the distributions of U and V...
LetX-Gamma(α = 2, β = 4), Y-Gamma(α = 3, β = 4), X & Y are independent, Z,- , Z,-X + Y. X+Y a) (3 pts) State the joint pdf ofX and Y. Simplify the expression, clearing all Г's. b) (9 pts) Find the joint pdf of Zi and Z2, using the two variable transformation method. In addition, clearly write the support for this joint pdf. When done, your answer should include the expression c) (5 pts) You should see...
If a random variable Xhas the gamma distribution with α= 2and β = 1, (a) What is the probability density function f(x)? (b) find P(1.8 < X< 2.4).
5. Consider a sample of size n from Gamma(α, β). Let a be given. Find the (minimal) sufficient statistic for parameter β
If X (in millions) is u a random variable gamma (β = 2.5, α = 2). a. What is the probability of x being greater than 6.5 million? b. If we take a sample of 10 and define T = ∑Xi. What is the probability that the total in this between 50 and 56.5 million? c. If we take a sample of 30 and define W (average) = ∑Xi / 30. What is the probability that the average is between...