Question

If X and Y are independent exponential random variables, each having parameter λ  =  4, find...

If X and Y are independent exponential random variables, each having parameter λ  =  4, find the joint density function of U  =  X + Y  and  V  =  e 9X.

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.

Homework Answers

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
If X and Y are independent exponential random variables, each having parameter λ  =  4, find...
If X and Y are independent exponential random variables, each having parameter λ  =  4, find the joint density function of U  =  X + Y  and  V  =  e 3X. 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...
If X and Y are independent exponential random variables, each having parameter λ  =  5, find...
If X and Y are independent exponential random variables, each having parameter λ  =  5, find the joint density function of U  =  X + Y  and  V  =  e 6X. 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...
Assume that X and Y are independent random variables, each having an exponential density with parameter...
Assume that X and Y are independent random variables, each having an exponential density with parameter λ. Let Z = |X - Y|. What is the density of Z?
Let X and Y be independent random variables following Poisson distributions, each with parameter λ =...
Let X and Y be independent random variables following Poisson distributions, each with parameter λ = 1. Show that the distribution of Z = X + Y is Poisson with parameter λ = 2. using convolution formula
Problem 0.1 Suppose X and Y are two independent exponential random variables with respective densities given...
Problem 0.1 Suppose X and Y are two independent exponential random variables with respective densities given by(λ,θ>0) f(x) =λe^(−xλ) for x>0 and g(y) =θe^(−yθ) for y>0. (a) Show that Pr(X<Y) =∫f(x){1−G(x)}dx {x=0, infinity] where G(x) is the cdf of Y, evaluated at x [that is,G(x) =P(Y≤x)]. (b) Using the result from part (a), show that P(X<Y) =λ/(θ+λ). (c) You install two light bulbs at the same time, a 60 watt bulb and a 100 watt bulb. The lifetime of the...
Consider the random variables X and Y with the following joint probability density function: fX,Y (x,...
Consider the random variables X and Y with the following joint probability density function: fX,Y (x, y) = xe-xe-y, x > 0, y > 0 (a) Suppose that U = X + Y and V = Y/X. Express X and Y in terms of U and V . (b) Find the joint PDF of U and V . (c) Find and identify the marginal PDF of U (d) Find the marginal PDF of V (e) Are U and V independent?
If X is an exponential random variable with parameter λ, calculate the cumulative distribution function and...
If X is an exponential random variable with parameter λ, calculate the cumulative distribution function and the probability density function of exp(X).
Let X be a Poisson random variable with parameter λ and Y an independent Bernoulli random...
Let X be a Poisson random variable with parameter λ and Y an independent Bernoulli random variable with parameter p. Find the probability mass function of X + Y .
Let X and Y be a random variables with the joint probability density function fX,Y (x,...
Let X and Y be a random variables with the joint probability density function fX,Y (x, y) = { cx2y, 0 < x2 < y < x for x > 0 0, otherwise }. compute the marginal probability density functions fX(x) and fY (y). Are the random variables X and Y independent?.
Let X and Y be a random variables with the joint probability density function fX,Y (x,...
Let X and Y be a random variables with the joint probability density function fX,Y (x, y) = { e −x−y , 0 < x, y < ∞ 0, otherwise } . a. Let W = max(X, Y ) Compute the probability density function of W. b. Let U = min(X, Y ) Compute the probability density function of U. c. Compute the probability density function of X + Y .