Let Xi iid∼ Unif(0, θ) for i = 1, 2, 3 and = 4Y(1) = 2Y(2)...
Let Xi iid∼ Unif(0, θ) for i = 1, 2, 3 and
=
4Y(1)
=
2Y(2)
θ* = (4/3)Y(3)
(a) For each estimator compute the bias?
(b) For each estimator compute the variance?
(c) Which estimator is best and why?
Homework Answers
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Let Xi iid∼ N(0, θ) for i = 1, ..., n. a) Find the MLE for...
Let Xi iid∼ N(0, θ) for i = 1, ..., n.
a) Find the MLE for θ. Call it
b) Is biased?
c) Is
consistent?
d) Find the variance of
(e) What is the asymptotic distribution of ?
Consider X1,X2, , Xn be an iid random sample fron Unif(0.0). Let θ = (끄+1) Y where Y = max(X1, x...
Consider X1,X2, , Xn be an iid random sample fron Unif(0.0). Let θ = (끄+1) Y where Y = max(X1, x. . . . , X.). It can be easily shown that the cdf of Y is h(y) = Prp.SH-()" 1. Prove that Y is a biased estimator of θ and write down the expression of the bias 2. Prove that θ is an unbiased estimator of θ. 3. Determine and write down the cdf of 0 4. Discuss why...
Exercice 6. Let be (Xi,..., Xn) an iid sample from the Bernoulli distribution with parameter θ,...
Exercice 6. Let be (Xi,..., Xn) an iid sample from the Bernoulli distribution with parameter θ, ie. I. What is the Maximum Likelihood estimate θ of θ? 2. Show that the maximum likelihood estimator of θ is unbiased. 3. We're looking to cstimate the variance θ (1-9) of Xi . x being the empirical average 2(1-2). Check that T is not unli ator propose an unbiased estimator of θ(1-0).
Problem 4 Define f(x) as follows θ2 -1<=x<0 1-θ2 0<=x>1 0 otherwise Let X1, … Xn be iid random variables with density f for some unknown θ...
Problem 4 Define f(x) as follows θ2 -1<=x<0 1-θ2 0<=x>1 0 otherwise Let X1, … Xn be iid random variables with density f for some unknown θ (0,1), Let a be the number of Xi which are negatives and b be the number of Xi which are positive. Total number of samples n = a+b. Find he Maximum likelihood estimator of θ? Is it asymptotically normal in this sample? Find the asymptotic variance Consider the following hypotheses: H0: X is...
Let X1, . . . , Xn ∼ iid Unif(θ − 1/2 , θ + 1/2...
Let X1, . . . , Xn ∼ iid Unif(θ − 1/2 , θ + 1/2 ) for θ unknown. Find an asymptotic confidence interval for θ.
Fix θ > 0 and let Xi, , x, i d. Unif[0.0]. We saw in class...
Fix θ > 0 and let Xi, , x, i d. Unif[0.0]. We saw in class that the MLE of θ, oMLE- I give two other estimators of θ, which can be made unbiased by appropriate choice of -C1 max(Xs , . . . , X,) max(X., Xn), is biased. constants C1,C2 We have two questions: (1) Find values of C1, C2 for which these estimators are unbiased. Note that Ci,C2 may depend on n (2) Which of these estimators...
Let X1, . . . , Xn ∼ iid Unif(θ − 1/2 , θ + 1/2 ) for θ unknown. Find an asymptotic confidence in...
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Additional Question i.i.d. ˆ Fix θ > 0 and let X1,...,Xn ∼ Unif[0,θ]. We saw in...
Additional Question i.i.d. ˆ Fix θ > 0 and let X1,...,Xn ∼
Unif[0,θ]. We saw in class that the MLE of θ, θMLE = max(X1, . . .
, Xn), is biased. I give two other estimators of θ, which can be
made unbiased by appropriate choice of constants C1, C2:
ADDITIONAL QUESTION Fix θ 0 and let Xi, . . . , Xn iid. Unifl0.0]. We saw in class that the MLE of θ, θΜ1E- max(Xi,..., Xn), is biased....
Let X1, X2, ..., Xn be iid with pdf f(x|θ) = θ*x(θ-1). a) Find the Maximum...
Let X1, X2, ..., Xn be iid with
pdf f(x|θ) = θ*x(θ-1). a) Find the Maximum Likelihood
Estimator of θ, and b) show that its variance converges to
0 as n approaches infinity.
I have no problem with part a, finding the MLE of θ. However,
I'm having some trouble with finding the variance.
The professor walked us through part b generally, but I need
help with univariate transformation for sigma(-ln(xi))
(see picture below - the professor used Y=sigma(-ln(x)), and...
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Let Xi iid∼ N(0, θ) for i = 1, ..., n.
a) Find the MLE for θ. Call it
b) Is biased?
c) Is
consistent?
d) Find the variance of
(e) What is the asymptotic distribution of ?
Consider X1,X2, , Xn be an iid random sample fron Unif(0.0). Let θ = (끄+1) Y where Y = max(X1, x. . . . , X.). It can be easily shown that the cdf of Y is h(y) = Prp.SH-()" 1. Prove that Y is a biased estimator of θ and write down the expression of the bias 2. Prove that θ is an unbiased estimator of θ. 3. Determine and write down the cdf of 0 4. Discuss why...
Exercice 6. Let be (Xi,..., Xn) an iid sample from the Bernoulli distribution with parameter θ, ie. I. What is the Maximum Likelihood estimate θ of θ? 2. Show that the maximum likelihood estimator of θ is unbiased. 3. We're looking to cstimate the variance θ (1-9) of Xi . x being the empirical average 2(1-2). Check that T is not unli ator propose an unbiased estimator of θ(1-0).
Fix θ > 0 and let Xi, , x, i d. Unif[0.0]. We saw in class that the MLE of θ, oMLE- I give two other estimators of θ, which can be made unbiased by appropriate choice of -C1 max(Xs , . . . , X,) max(X., Xn), is biased. constants C1,C2 We have two questions: (1) Find values of C1, C2 for which these estimators are unbiased. Note that Ci,C2 may depend on n (2) Which of these estimators...
Additional Question i.i.d. ˆ Fix θ > 0 and let X1,...,Xn ∼
Unif[0,θ]. We saw in class that the MLE of θ, θMLE = max(X1, . . .
, Xn), is biased. I give two other estimators of θ, which can be
made unbiased by appropriate choice of constants C1, C2:
ADDITIONAL QUESTION Fix θ 0 and let Xi, . . . , Xn iid. Unifl0.0]. We saw in class that the MLE of θ, θΜ1E- max(Xi,..., Xn), is biased....
Let X1, X2, ..., Xn be iid with
pdf f(x|θ) = θ*x(θ-1). a) Find the Maximum Likelihood
Estimator of θ, and b) show that its variance converges to
0 as n approaches infinity.
I have no problem with part a, finding the MLE of θ. However,
I'm having some trouble with finding the variance.
The professor walked us through part b generally, but I need
help with univariate transformation for sigma(-ln(xi))
(see picture below - the professor used Y=sigma(-ln(x)), and...
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