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As on the previous page, let Xi,...,Xn be i.i.d. with pdf where >0 2 points possible...
As on the previous page, let X1,... ,Xn be iid with pdf where θ > 0. (to) 2 Possible points (qual...
As on the previous page, let X1,... ,Xn be iid with pdf where θ > 0. (to) 2 Possible points (qualifiable, hidden results) Assume we do not actually get to observe Xı , . . . , X. . Instead let Yı , . . . , Y, be our observations where Yi = 1 (Xi 0.5) . Our goal is to estimate 0 based on this new data. What distribution does Y follow? First, choose the type of distribution:...
For z e R and θ (0, 1), define otherwise. Let X1 , . . . , X" be i..d. random variables with density f, for some unknown θ E (0, 1) 1 point possible (graded, results hidden) To prepare, sketch th...
For z e R and θ (0, 1), define otherwise. Let X1 , . . . , X" be i..d. random variables with density f, for some unknown θ E (0, 1) 1 point possible (graded, results hidden) To prepare, sketch the pdf f, (z) for different values of θ E (0,1) Which of the following properties of fo (z) guarantee that it is a probability density? (Check all that apply) Note (added May 3) Note that you are not...
4. Setup: Suppose you have observations X1,X2,X3,X4,X5 which are i.i.d. draws from a Gaussian distribution with...
4.
Setup:
Suppose you have observations X1,X2,X3,X4,X5 which are i.i.d.
draws from a Gaussian distribution with unknown mean μ and unknown
variance σ2.
Given Facts:
You are given the following:
15∑i=15Xi=0.90,15∑i=15X2i=1.31
Bookmark this page Setup: Suppose you have observations X1, X2, X3, X4, X5 which are i.i.d. draws from a Gaussian distribution with unknown mean u and unknown variance o? Given Facts: You are given the following: x=030, =1:1 Choose a test 1 point possible (graded, results hidden) To test...
Problem 4 True or False A Bookmark this page Instructions: Be very careful with the multiple choice questions below. Some are "choose all that apply," and many tests your knowledge of when pa...
Problem 4 True or False A Bookmark this page Instructions: Be very careful with the multiple choice questions below. Some are "choose all that apply," and many tests your knowledge of when particular statements apply As in the rest of this exam, only your last submission will count. 1 point possible (graded, results hidden) The likelihood ratio test is used to obtain a test with non-asymptotic level o True O False Submit You have used 0 of 3 attempts Save...
Suppose X is a random vector, where X = (X(1), . . . , x(d))T , d with mean 0 and covariance matr...
Suppose X is a random vector, where X = (X(1), . . . , x(d))T , d with mean 0 and covariance matrix vv1 , for some vector v ER 1point possible (graded) Let v = . (i.e., v is the normalized version of v). What is the variance of v X? (If applicable, enter trans(v) for the transpose v of v, and normv) for the norm |vll of a vector v.) Var (V STANDARD NOTATION SubmitYou have used 0...
Let X1 , . . . , xn be n iid. random variables with distribution N (θ, θ) for some unknown θ > 0....
Let X1 , . . . , xn be n iid. random variables with distribution N (θ, θ) for some unknown θ > 0. In the last homework, you have computed the maximum likelihood estimator θ for θ in terms of the sample averages of the linear and quadratic means, i.e. Xn and X,and applied the CLT and delta method to find its asymptotic variance. In this problem, you will compute the asymptotic variance of θ via the Fisher Information....
Let Xi,... ,Xn be i.i.d with pdf θνθ θ+1 where I(.) denotes the indicator function. (a) Find a 2-dimensional sufficient statistic for the mode (b) Suppose θ is a known constant. Find the MLE for v....
Let Xi,... ,Xn be i.i.d with pdf θνθ θ+1 where I(.) denotes the indicator function. (a) Find a 2-dimensional sufficient statistic for the mode (b) Suppose θ is a known constant. Find the MLE for v. (d) Suppose v-1. Find the MLE for and determine its asymptotic distribution. Carefully justify your answer and state any theorems that you use. (e) Suppose1. Find the asymptotic distribution of the MLE estimator of exp[-
Let Xi,... ,Xn be i.i.d with pdf θνθ θ+1...
2. Biased and unbiased estimation for variance of Bernoulli variables A Bookmark this page 2 points...
2. Biased and unbiased estimation for variance of Bernoulli variables A Bookmark this page 2 points possible (graded) Let X1, X, bed. Bernoull random variables, with unknown parameter PE (0,1). The aim of this exercise is to estimate the common variance of the X First, recall what Var (X) is for Bernoulli random variables. Var (X) - Let X, be the sample average of the Xi. X. - 3x Interested in finding an estimator for Var(X), and propose to use...
Degrees of Freedom of a Known Test 2 points possible graded) Let us consider a statistical...
Degrees of Freedom of a Known Test 2 points possible graded) Let us consider a statistical model with parameter ER". Let O be the parameter that generates the n lid samples X1,..., X, Let I ) be the Fisher information and assume that the MLE is asymptotically normal. Assume that I(C) is a diagonal matrix with positive entries 1/t1,...,1/td. We wish to perform a test for the hypotheses H : 8 - and H:8 + . Let the test statistic...
Concept Question: Maximum Likelihood Estimator for the Laplace distribution 1 point possible (graded) As in the...
Concept Question: Maximum Likelihood Estimator for the Laplace distribution 1 point possible (graded) As in the previous problem, let mn MLE denote the MLE for an unknown parameter m* of a Laplace distribution. MLE Can we apply the theorem for the asymptotic normality of the MLE to mn? (You must choose the correct answer that also has the correct explanation.) No, because the log-likelihood is not concave. No, because the log-likelihood is not twice-differentiable, so the Fisher information does not...
As on the previous page, let X1,... ,Xn be iid with pdf where θ > 0. (to) 2 Possible points (qualifiable, hidden results) Assume we do not actually get to observe Xı , . . . , X. . Instead let Yı , . . . , Y, be our observations where Yi = 1 (Xi 0.5) . Our goal is to estimate 0 based on this new data. What distribution does Y follow? First, choose the type of distribution:...
For z e R and θ (0, 1), define otherwise. Let X1 , . . . , X" be i..d. random variables with density f, for some unknown θ E (0, 1) 1 point possible (graded, results hidden) To prepare, sketch the pdf f, (z) for different values of θ E (0,1) Which of the following properties of fo (z) guarantee that it is a probability density? (Check all that apply) Note (added May 3) Note that you are not...
4.
Setup:
Suppose you have observations X1,X2,X3,X4,X5 which are i.i.d.
draws from a Gaussian distribution with unknown mean μ and unknown
variance σ2.
Given Facts:
You are given the following:
15∑i=15Xi=0.90,15∑i=15X2i=1.31
Bookmark this page Setup: Suppose you have observations X1, X2, X3, X4, X5 which are i.i.d. draws from a Gaussian distribution with unknown mean u and unknown variance o? Given Facts: You are given the following: x=030, =1:1 Choose a test 1 point possible (graded, results hidden) To test...
Problem 4 True or False A Bookmark this page Instructions: Be very careful with the multiple choice questions below. Some are "choose all that apply," and many tests your knowledge of when particular statements apply As in the rest of this exam, only your last submission will count. 1 point possible (graded, results hidden) The likelihood ratio test is used to obtain a test with non-asymptotic level o True O False Submit You have used 0 of 3 attempts Save...
Suppose X is a random vector, where X = (X(1), . . . , x(d))T , d with mean 0 and covariance matrix vv1 , for some vector v ER 1point possible (graded) Let v = . (i.e., v is the normalized version of v). What is the variance of v X? (If applicable, enter trans(v) for the transpose v of v, and normv) for the norm |vll of a vector v.) Var (V STANDARD NOTATION SubmitYou have used 0...
Let X1 , . . . , xn be n iid. random variables with distribution N (θ, θ) for some unknown θ > 0. In the last homework, you have computed the maximum likelihood estimator θ for θ in terms of the sample averages of the linear and quadratic means, i.e. Xn and X,and applied the CLT and delta method to find its asymptotic variance. In this problem, you will compute the asymptotic variance of θ via the Fisher Information....
Let Xi,... ,Xn be i.i.d with pdf θνθ θ+1 where I(.) denotes the indicator function. (a) Find a 2-dimensional sufficient statistic for the mode (b) Suppose θ is a known constant. Find the MLE for v. (d) Suppose v-1. Find the MLE for and determine its asymptotic distribution. Carefully justify your answer and state any theorems that you use. (e) Suppose1. Find the asymptotic distribution of the MLE estimator of exp[-
Let Xi,... ,Xn be i.i.d with pdf θνθ θ+1...
2. Biased and unbiased estimation for variance of Bernoulli variables A Bookmark this page 2 points possible (graded) Let X1, X, bed. Bernoull random variables, with unknown parameter PE (0,1). The aim of this exercise is to estimate the common variance of the X First, recall what Var (X) is for Bernoulli random variables. Var (X) - Let X, be the sample average of the Xi. X. - 3x Interested in finding an estimator for Var(X), and propose to use...
Degrees of Freedom of a Known Test 2 points possible graded) Let us consider a statistical model with parameter ER". Let O be the parameter that generates the n lid samples X1,..., X, Let I ) be the Fisher information and assume that the MLE is asymptotically normal. Assume that I(C) is a diagonal matrix with positive entries 1/t1,...,1/td. We wish to perform a test for the hypotheses H : 8 - and H:8 + . Let the test statistic...
Concept Question: Maximum Likelihood Estimator for the Laplace distribution 1 point possible (graded) As in the previous problem, let mn MLE denote the MLE for an unknown parameter m* of a Laplace distribution. MLE Can we apply the theorem for the asymptotic normality of the MLE to mn? (You must choose the correct answer that also has the correct explanation.) No, because the log-likelihood is not concave. No, because the log-likelihood is not twice-differentiable, so the Fisher information does not...
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