Question

exponential distribution x1 has density f1(x)=e^-x with r.v if Xa=X1/a then it has density fa(x)=ae^-ax can...

exponential distribution

x1 has density f1(x)=e^-x with r.v if Xa=X1/a then it has density fa(x)=ae^-ax

can someone tell me what happened here???? dont get why will become the parameter is a but not 1/a since we divide the r.v by a

Homework Answers

Answer #1

f(x)= e^-x, x>0..

Xa=x/a

Or x=Xa ×a, if we find jacobin of this then d(x)/dXa =a ;{d /dXa represent differencial function}

Now, to find density of transformed variable, we need to multiply the density of x by its jacobin and replace in its density x by transformed variable Xa. So

f(Xa)= f(x)×modulus(dx/dXa) = e^-(a×Xa)×modulus(dx/dXa) =e^-(Xa×a) .a =ae^(-aXa). This is the density of exponential distribution with parameter a.

Thank you please rate the answer

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
The r.v. X has the probability density function f (x) = ax + bx2 if 0...
The r.v. X has the probability density function f (x) = ax + bx2 if 0 < x < 1 and zero otherwise. If E[X] = 0.6, find (a) P[X < 21] and (b) Var(X). (Answers should be in numerical values and not be as expressions in a and b.)
. X has exponential distribution with parameter 4. Therefore E[X] = 1/4 . Find P(X >...
. X has exponential distribution with parameter 4. Therefore E[X] = 1/4 . Find P(X > 6) and P(X > 6|X > 1). Find E[X|X > 1]. Would someone help me with the correct detail solutions to the problems
Problem 1. The Cauchy distribution with scale 1 has following density function f(x) = 1 /...
Problem 1. The Cauchy distribution with scale 1 has following density function f(x) = 1 / π [1 + (x − η)^2 ] , −∞ < x < ∞. Here η is the location and rate parameter. The goal is to find the maximum likelihood estimator of η. (a) Find the log-likelihood function of f(x) l(η; x1, x2, ..., xn) = log L(η; x1, x2, ..., xn) = (b) Find the first derivative of the log-likelihood function l'(η; x1, x2,...
1. Remember that a Poisson Distribution has a density function of f(x) = [e^(−k)k^x]/x! . It...
1. Remember that a Poisson Distribution has a density function of f(x) = [e^(−k)k^x]/x! . It has a mean and variance both equal to k. (a) Use the method of moments to find an estimator for k. (b) Use the maximum likelihood method to find an estimator for k. (c) Show that the estimator you got from the first part is an unbiased estimator for k. (d) (5 points) Find an expression for the variance of the estimator you have...