Question

Let ?? ~ ???? (2?, 4?) independet random variables. for ? = 1,2,… ?. a)Find an...

Let ?? ~ ???? (2?, 4?) independet random variables. for ? = 1,2,… ?.

a)Find an estimator for ? by the method of moments.
b) Find an estimator for ? by the maximum likelihood estimator (MLE)

Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Let ?? ~ ??? (?,θ ) independent random variable. for ? = 1,2,… ?. Find an...
Let ?? ~ ??? (?,θ ) independent random variable. for ? = 1,2,… ?. Find an estimator for ? by the maximum likelihood method.(MLE)
Let ?1, ?2,…. . , ?? (n random variables iid) as a variable X whose pdf...
Let ?1, ?2,…. . , ?? (n random variables iid) as a variable X whose pdf is given by ??-a-1 for ? ≥1. (a) For ? ≥ 1 calculate ? (??? ≤ ?) = ? (?). Deduce the function density of probabilities of Y = lnX. (b) Determine the maximum likelihood estimator (MLE) of ? and show that he is without biais
Suppose Y1, . . . , Yn are independent random variables with common density fY(y) =...
Suppose Y1, . . . , Yn are independent random variables with common density fY(y) = eμ−y , y > μ 1. Find the Method of Moments Estimator for μ. 2. Find the MLE for μ. Then find the bias of the estimator
Let Y1, Y2, . . ., Yn be a random sample from a Laplace distribution with...
Let Y1, Y2, . . ., Yn be a random sample from a Laplace distribution with density function f(y|θ) = (1/2θ)e-|y|/θ for -∞ < y < ∞ where θ > 0. The first two moments of the distribution are E(Y) = 0 and E(Y2) = 2θ2. a) Find the likelihood function of the sample. b) What is a sufficient statistic for θ? c) Find the maximum likelihood estimator of θ. d) Find the maximum likelihood estimator of the standard deviation...
6. Let X1, X2, ..., Xn be a random sample of a random variable X from...
6. Let X1, X2, ..., Xn be a random sample of a random variable X from a distribution with density f (x)  ( 1)x 0 ≤ x ≤ 1 where θ > -1. Obtain, a) Method of Moments Estimator (MME) of parameter θ. b) Maximum Likelihood Estimator (MLE) of parameter θ. c) A random sample of size 5 yields data x1 = 0.92, x2 = 0.7, x3 = 0.65, x4 = 0.4 and x5 = 0.75. Compute ML Estimate...
Let X1, X2, . . . , Xn be iid exponential random variables with unknown mean...
Let X1, X2, . . . , Xn be iid exponential random variables with unknown mean β. (1) Find the maximum likelihood estimator of β. (2) Determine whether the maximum likelihood estimator is unbiased for β. (3) Find the mean squared error of the maximum likelihood estimator of β. (4) Find the Cramer-Rao lower bound for the variances of unbiased estimators of β. (5) What is the UMVUE (uniformly minimum variance unbiased estimator) of β? What is your reason? (6)...
Let B > 0 and let X1 , X2 , … , Xn be a random...
Let B > 0 and let X1 , X2 , … , Xn be a random sample from the distribution with probability density function. f( x ; B ) = β/ (1 +x)^ (B+1), x > 0, zero otherwise. (i) Obtain the maximum likelihood estimator for B, β ˆ . (ii) Suppose n = 5, and x 1 = 0.3, x 2 = 0.4, x 3 = 1.0, x 4 = 2.0, x 5 = 4.0. Obtain the maximum likelihood...
Let X have a gamma distribution with  and  which is unknown. Let  be a random sample from this distribution....
Let X have a gamma distribution with  and  which is unknown. Let  be a random sample from this distribution. (1.1) Find a consistent estimator for  using the method-of-moments. (1.2) Find the MLE of  denoted by . (1.3) Find the asymptotic variance of the MLE, i.e. (1.4) Find a sufficient statistic for . (1.5) Find MVUE for .
Let X1, X2, . . . Xn be iid exponential random variables with unknown mean β....
Let X1, X2, . . . Xn be iid exponential random variables with unknown mean β. Find the method of moments estimator of β
Let X1, X2,..., Xn be a random sample from a population with probability density function f(x)...
Let X1, X2,..., Xn be a random sample from a population with probability density function f(x) = theta(1-x)^(theta-1), where 0<x<1, where theta is a positive unknown parameter a) Find the method of moments estimator of theta b) Find the maximum likelihood estimator of theta c) Show that the log likelihood function is maximized at theta(hat)
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT