Question

In: Statistics and Probability

If X and Y are independent exponential random variables, each having parameter λ  =  6, find...

If X and Y are independent exponential random variables, each having parameter λ  =  6, find the joint density function of U  =  X + Y  and  V  =  e 2X.

The required joint density function is of the form

fU,V(u, v)  = 
{ g(u, v) u  >  h(v), v  >  a
0 otherwise

(a) Enter the function g(u, v) into the answer box below.
(b) Enter the function h(v) into the answer box below.
(c) Enter the value of a into the answer box below.

Solutions

Expert Solution

Solution:-

Given that

x and y are exponential random variable each having parameter .

density function of X,

joint density of x, y

, x> 0, y > 0

,  

(x and y are independent)

By the method of transforms on

f(u, v) is the joint density of u and v

(a) Enter the function g(u, v) into the answer box below

(a)

so

(b) Enter the function h(v) into the answer box below.

So the function h(v) is given that

(c) Enter the value of a into the answer box below.

value of "a" into the answer box below

a = 1

Thanks for supporting...

Please give positive rating...


Related Solutions

X and Y are independent Exponential random variables with mean=4, λ = 1/2. 1) Find the...
X and Y are independent Exponential random variables with mean=4, λ = 1/2. 1) Find the joint CDF of the random variables X, Y and  Find the probability that 4X > Y . 2) Find the expected value of X^3 + X*Y .
Let X1, X2,..., Xnbe independent and identically distributed exponential random variables with parameter λ . a)...
Let X1, X2,..., Xnbe independent and identically distributed exponential random variables with parameter λ . a) Compute P{max(X1, X2,..., Xn) ≤ x} and find the pdf of Y = max(X1, X2,..., Xn). b) Compute P{min(X1, X2,..., Xn) ≤ x} and find the pdf of Z = min(X1, X2,..., Xn). c) Compute E(Y) and E(Z).
Let X and Y be independent geometric random variables with parameter p. Find the pmf of...
Let X and Y be independent geometric random variables with parameter p. Find the pmf of X + Y
Question 6 . Let X and Y be independent random variables each having density function Determine...
Question 6 . Let X and Y be independent random variables each having density function Determine E(Y ), E(X), E(Y 2 + X), E(X.Y ). Determine Variance σX2 and the standard deviation σY . If a new random variable Z is such that Z = 3X + 2Y + 2, determine E(Z). Answers :
Let X1,...,Xn be exponentially distributed independent random variables with parameter λ. (a) Find the pdf of...
Let X1,...,Xn be exponentially distributed independent random variables with parameter λ. (a) Find the pdf of Yn= max{X1,...,Xn}. (b) Find E[Yn]. (c) Find the median of Yn. (d) What is the mean for n= 1, n= 2, n= 3? What happens as n→∞? Explain why.
Let X, Y be independent exponential random variables with mean one. Show that X/(X + Y...
Let X, Y be independent exponential random variables with mean one. Show that X/(X + Y ) is uniformly distributed on [0, 1]. (Please solve it with clear explanations so that I can learn it. I will give thumbs up.)
Assume that X, Y, and Z are independent random variables and that each of the random...
Assume that X, Y, and Z are independent random variables and that each of the random variables have a mean of 1. Further, assume σX = 1, σY = 2, and σZ = 3. Find the mean and standard deviation of the following random variables: a. U = X + Y + Z b. R = (X + Y + Z)/3 c. T = 2·X + 5·Y d. What is the correlation between X and Y? e. What is the...
Let X and Y be independent Exponential random variables with common mean 1. Their joint pdf...
Let X and Y be independent Exponential random variables with common mean 1. Their joint pdf is f(x,y) = exp (-x-y) for x > 0 and y > 0 , f(x, y ) = 0 otherwise. (See "Independence" on page 349) Let U = min(X, Y) and V = max (X, Y). The joint pdf of U and V is f(u, v) = 2 exp (-u-v) for 0 < u < v < infinity, f(u, v ) = 0 otherwise....
Let X be an exponential random variable with parameter λ, which means that fX(x) = λe^(−λx)...
Let X be an exponential random variable with parameter λ, which means that fX(x) = λe^(−λx) * u(x). (a) For x > 0, find P(X ≤ x). (b) For x2 > x1 > 0, find P(x1 ≤ X ≤ x2). (c) For x > 0, find P(X ≥ x). (d) Segment the positive real line into three equally likely disjoint intervals.
For a random sample of sizenfrom an Exponential distribution with rate parameter λ (so that the...
For a random sample of sizenfrom an Exponential distribution with rate parameter λ (so that the density is fY(y) =λe−λy), derive the maximum likelihood estimator, the methods of moments estimator, and the Bayes estimator (that is, the posterior mean) using a prior proportional to λe−λ, for λ >0. (Hint: the posterior distribution will be a Gamma.)
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT