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![luif (0 i 0 ) X1-Xn MSE(E (1) 2 [e - ৪)] 2 2 ()(as ECR) = TE (Xi) 40(0 amd EX 2 E)E 2 Ixi2 Z 2 2Xi Xj n2 nE(x n2 2 n2](http://img.homeworklib.com/questions/7770bb80-c0c4-11ea-b042-859569932c9d.png?x-oss-process=image/resize,w_560)
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Problem 3 Uniform Order Stats as Estimators Suppose that X,.., X,, ~ Unif(0, 0) are independent....
1) LetX,, ,X, be i.i.d. Uniform (0 , ) random variables for some > 0 (unknown). Which of the following estimators of0 are unbiased and which ones are biased? For each of the biased estimators...
1) LetX,, ,X, be i.i.d. Uniform (0 , ) random variables for some > 0 (unknown). Which of the following estimators of0 are unbiased and which ones are biased? For each of the biased estimators ofO, find the MSE. (a)2X, (b) the smallest order statistic, (e) the largest order statistic, (d) x, /2 ) For each of the unbiased estimators of 0 in the above problem, find the variance. Which unbiased estimator has the smallest variance? Find the relative efficiency...
3. Consider a random sample Yı, ,Yn from a Uniform[0, θ]. In class we discussed the...
3. Consider a random sample Yı, ,Yn from a Uniform[0, θ]. In class we discussed the method of ,y,). We moment estimator θ-2Y and the maximum likelihood estimator θ-maxx,Yo, derived the Bias and MSE for both estimators. With the intent to correct the bias of the mle θ we proposed the following new estimator -Imax where the subscript u stands for "unbiased." (a) Find the MSE of (b) Compare the MSE of θυ to the MSE of θ, the original...
1. Suppose that X Unif(0, 30) and we draw a random sample X1,..., Xn Find the...
1. Suppose that X Unif(0, 30) and we draw a random sample X1,..., Xn Find the MME and compute its relative efficiency to 6, = 2X1-3X2. 2. In class, I showed the below picture. Here, I have changed the vertical axis from variance to SD. In this new picture, how can we visualize the MSE? How does this way of seeing the MSE help us decide which of two (possibly biased) estimators is more efficient? SD 04 Bias (B) 0...
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...
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....
3. Suppose that the 5-year survival probability, X, for women with breast cancer who live in...
3. Suppose that the 5-year survival probability, X, for women with breast cancer who live in a rural county follows Beta distribution with probability density function (pdf) fx (20) = 0.00-1 where 0 < x < 1 and parameter 6 > 0. Let X1, ..., X, be a random sample of size n from a population of rural counties. Researchers intend to make statistical inference on the parameter 6 using collected data X1, ..., (a) Let Y; = – log(Xi)...
A (3 pt) Let Xi, ,X, are drawn from the distribution ftheta(z) = F 404 (r+0) , for 0 < x < oo and...
A (3 pt) Let Xi, ,X, are drawn from the distribution ftheta(z) = F 404 (r+0) , for 0 < x < oo and 0 < θ < oo. We define Y = 3X an estimator for θ. Verify whether this estimator is unbiased? Find the MSE of Y. Hint: E(x)E(X B (3 pt) Let X,.., X, are drawn from the distribution fo) for O < x < 00 and 0 < θ < oo. We define Y = 2X...
3. (5 marks) Let U be a random variable which has the continuous uniform distribution on the inte...
3. (5 marks) Let U be a random variable which has the continuous uniform distribution on the interval I-1, 1]. Recall that this means the density function fu satisfies for(z-a: a.crwise. 1 u(z), -1ss1, a) Find thc cxpccted valuc and the variancc of U. We now consider estimators for the expected value of U which use a sample of size 2 Let Xi and X2 be independent random variables with the same distribution as U. Let X = (X1 +...
2 Let X1, X2, ...,X, be independent continuous random variables from the following distribution: f(3) =...
2 Let X1, X2, ...,X, be independent continuous random variables from the following distribution: f(3) = ox-(0-1) where : > 1 and a > 1 You may use the fact: E[X]- .- 2.1 Show that the maximum likelihood estimator of a is ômle = Ei log Xi 2.3 Derive a sufficient statistic for a. What theorem are you using to determine sufficiency? 2.4 Show that the fisher information in the whole sample is: 1(a)= 2.5 What Cramer Rao lower bound...
2. (Discrete uniform). Consider the PMF P(X x)= for x 1,2,...0 _ You have a random...
2. (Discrete uniform). Consider the PMF P(X x)= for x 1,2,...0 _ You have a random sample of size three from this distribution: {2,3,10}. a. Find the method of moments estimate for 0 HINT: a very useful fact is that k1 n(n+1) 2 b. Find the MLE for 0 c. Which estimator is unbiased? d. Which estimator is preferred?
2. (Discrete uniform). Consider the PMF P(X x)= for x 1,2,...0 _ You have a random sample of size three from...
1) LetX,, ,X, be i.i.d. Uniform (0 , ) random variables for some > 0 (unknown). Which of the following estimators of0 are unbiased and which ones are biased? For each of the biased estimators ofO, find the MSE. (a)2X, (b) the smallest order statistic, (e) the largest order statistic, (d) x, /2 ) For each of the unbiased estimators of 0 in the above problem, find the variance. Which unbiased estimator has the smallest variance? Find the relative efficiency...
3. Consider a random sample Yı, ,Yn from a Uniform[0, θ]. In class we discussed the method of ,y,). We moment estimator θ-2Y and the maximum likelihood estimator θ-maxx,Yo, derived the Bias and MSE for both estimators. With the intent to correct the bias of the mle θ we proposed the following new estimator -Imax where the subscript u stands for "unbiased." (a) Find the MSE of (b) Compare the MSE of θυ to the MSE of θ, the original...
1. Suppose that X Unif(0, 30) and we draw a random sample X1,..., Xn Find the MME and compute its relative efficiency to 6, = 2X1-3X2. 2. In class, I showed the below picture. Here, I have changed the vertical axis from variance to SD. In this new picture, how can we visualize the MSE? How does this way of seeing the MSE help us decide which of two (possibly biased) estimators is more efficient? SD 04 Bias (B) 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....
3. Suppose that the 5-year survival probability, X, for women with breast cancer who live in a rural county follows Beta distribution with probability density function (pdf) fx (20) = 0.00-1 where 0 < x < 1 and parameter 6 > 0. Let X1, ..., X, be a random sample of size n from a population of rural counties. Researchers intend to make statistical inference on the parameter 6 using collected data X1, ..., (a) Let Y; = – log(Xi)...
A (3 pt) Let Xi, ,X, are drawn from the distribution ftheta(z) = F 404 (r+0) , for 0 < x < oo and 0 < θ < oo. We define Y = 3X an estimator for θ. Verify whether this estimator is unbiased? Find the MSE of Y. Hint: E(x)E(X B (3 pt) Let X,.., X, are drawn from the distribution fo) for O < x < 00 and 0 < θ < oo. We define Y = 2X...
3. (5 marks) Let U be a random variable which has the continuous uniform distribution on the interval I-1, 1]. Recall that this means the density function fu satisfies for(z-a: a.crwise. 1 u(z), -1ss1, a) Find thc cxpccted valuc and the variancc of U. We now consider estimators for the expected value of U which use a sample of size 2 Let Xi and X2 be independent random variables with the same distribution as U. Let X = (X1 +...
2 Let X1, X2, ...,X, be independent continuous random variables from the following distribution: f(3) = ox-(0-1) where : > 1 and a > 1 You may use the fact: E[X]- .- 2.1 Show that the maximum likelihood estimator of a is ômle = Ei log Xi 2.3 Derive a sufficient statistic for a. What theorem are you using to determine sufficiency? 2.4 Show that the fisher information in the whole sample is: 1(a)= 2.5 What Cramer Rao lower bound...
2. (Discrete uniform). Consider the PMF P(X x)= for x 1,2,...0 _ You have a random sample of size three from this distribution: {2,3,10}. a. Find the method of moments estimate for 0 HINT: a very useful fact is that k1 n(n+1) 2 b. Find the MLE for 0 c. Which estimator is unbiased? d. Which estimator is preferred?
2. (Discrete uniform). Consider the PMF P(X x)= for x 1,2,...0 _ You have a random sample of size three from...
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