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Let X, denote a binary variable and consider the regressions Yi = A + Ax, +...
f Squares and Properties of Estimators o. Let xi yi denote two series ofn numbers xi:...
f Squares and Properties of Estimators o. Let xi yi denote two series ofn numbers xi: i-1,2...), tyi: i 1,2...n) Assume that xi s drawn from a distribution that is NOHm σ) Show that the sample mean i ΣΙ-1 χί has a variance of σ/n carefully stating any required assunmptions at each step. Is the sample mean an unbiased estimator of u,? 1. ii. The following results are useful when working with linear regressions. Show that: 2 iii. Show that:...
(Econometrics) 1. Consider the simple linear model and let Z, be a binary instrumental variable for...
(Econometrics)
1. Consider the simple linear model and let Z, be a binary instrumental variable for X,. Show that the IV estimator β1JV for A can be written as I X1-Xo where Yo and Xo are the sample averages of Y, and X, over the part of the sample with Zi = 0, and Yi and Xi are the sample averages of Yand Xi over the part of the sample with Zi = 1.
2. Consider a simple linear regression model for a response variable Yi, a single predictor variable...
2. Consider a simple linear regression model for a response variable Yi, a single predictor variable ri, i-1,... , n, and having Gaussian (i.e. normally distributed) errors Ý,-BzitEj, Ejį.i.d. N(0, σ2) This model is often called "regression through the origin" since E(Yi) 0 if xi 0 (a) Write down the likelihood function for the parameters β and σ2 (b) Find the MLEs for β and σ2, explicitly showing that they are unique maximizers of the likelihood function. (Hint: The function...
8) Let Yi, X, denote a random sample from a normal distribution with mean μ and...
8) Let Yi, X, denote a random sample from a normal distribution with mean μ and variance σ , with known μ and unknown σ' . You are given that Σ(X-μ)2 is sufficient for σ a) Find El Σ(X-μ). |. Show all steps. Use the fact that: Var(Y)-E(P)-(BY)' i-1 b) Find the MVUE of σ.
X denote the mean of a random sample of size 25 from a gamma type distribu-...
X denote the mean of a random sample of size 25 from a gamma type distribu- tion with a = 4 and β > 0. Use the Central Limit theorem to find an approximate 0.954 confidence interval for μ, the mean of the gallina distribution. Hint: Use the random variable (X-43)/?7,/432/25. 6. Let Yi < ½ < < }, denote the order statistics of a randon sample of size n from a distribution that has pdf f(z) = 4r3/04, O...
Please consider the following problem: Yi = Xiß +€; i-lycoon a) Denote the OLS coefficient estimates...
Please consider the following problem:
Yi = Xiß +€; i-lycoon a) Denote the OLS coefficient estimates based on your sample of n observations by bn 6) suppose another observation ExtY3 is acquired. show that b=bot if and only if you can be perfectly predicted on the basis of tot e bo
QUESTION 3 Let Y1, Y2, ..., Yn denote a random sample of size n from a...
QUESTION 3 Let Y1, Y2, ..., Yn denote a random sample of size n from a population whose density is given by (Parcto distribution). Consider the estimator β-Yu)-min(n, Y, where β is unknown (a) Derive the bias of the estimator β. (b) Derive the mean square error of B. , Yn).
3. Let {x1, x2,...,xn} be a list of numbers and let ¯ x denote the average...
3. Let {x1, x2,...,xn} be a list of numbers and let ¯ x denote the average of the list. Let a and b be two constants, and for each i such that 1 ≤ i ≤ n, let yi = axi + b. Consider the new list {y1,y2,...,yn}, and let the average of this list be ¯ y. Prove a formula for ¯ y in terms of a, b, and ¯ x. 4. Let n be a positive integer. Consider...
Problem 2: Let (X1,... Xn) denote a random variable from X having density fx(x) = 1/...
Problem 2: Let (X1,... Xn) denote a random variable from X having density fx(x) = 1/ β,0 < x < β where β > 0 is an unknown param eter. Explain why the Cramer Rao Theorem cannot be applied to show that an unbiased estimator of β is MVU. (Hint: see slides. Condition (A) of Cramer Rao Theorem)
MA2500/18 8. Let X be a random variable and let 'f(r; θ) be its PDF where...
MA2500/18 8. Let X be a random variable and let 'f(r; θ) be its PDF where θ is an unknown scalar parameter. We wish to test the simple null hypothesis Ho: 0 against the simple alternative Hi : θ-64. (a) Define the simple likelihood ratio test (SLRT) of Ho against H (b) Show that the SLRT is a most powerful test of Ho against H. (c) Let Xi, X2.... , X be a random sample of observations from the Poisson(e)...
f Squares and Properties of Estimators o. Let xi yi denote two series ofn numbers xi: i-1,2...), tyi: i 1,2...n) Assume that xi s drawn from a distribution that is NOHm σ) Show that the sample mean i ΣΙ-1 χί has a variance of σ/n carefully stating any required assunmptions at each step. Is the sample mean an unbiased estimator of u,? 1. ii. The following results are useful when working with linear regressions. Show that: 2 iii. Show that:...
(Econometrics)
1. Consider the simple linear model and let Z, be a binary instrumental variable for X,. Show that the IV estimator β1JV for A can be written as I X1-Xo where Yo and Xo are the sample averages of Y, and X, over the part of the sample with Zi = 0, and Yi and Xi are the sample averages of Yand Xi over the part of the sample with Zi = 1.
2. Consider a simple linear regression model for a response variable Yi, a single predictor variable ri, i-1,... , n, and having Gaussian (i.e. normally distributed) errors Ý,-BzitEj, Ejį.i.d. N(0, σ2) This model is often called "regression through the origin" since E(Yi) 0 if xi 0 (a) Write down the likelihood function for the parameters β and σ2 (b) Find the MLEs for β and σ2, explicitly showing that they are unique maximizers of the likelihood function. (Hint: The function...
8) Let Yi, X, denote a random sample from a normal distribution with mean μ and variance σ , with known μ and unknown σ' . You are given that Σ(X-μ)2 is sufficient for σ a) Find El Σ(X-μ). |. Show all steps. Use the fact that: Var(Y)-E(P)-(BY)' i-1 b) Find the MVUE of σ.
X denote the mean of a random sample of size 25 from a gamma type distribu- tion with a = 4 and β > 0. Use the Central Limit theorem to find an approximate 0.954 confidence interval for μ, the mean of the gallina distribution. Hint: Use the random variable (X-43)/?7,/432/25. 6. Let Yi < ½ < < }, denote the order statistics of a randon sample of size n from a distribution that has pdf f(z) = 4r3/04, O...
Please consider the following problem:
Yi = Xiß +€; i-lycoon a) Denote the OLS coefficient estimates based on your sample of n observations by bn 6) suppose another observation ExtY3 is acquired. show that b=bot if and only if you can be perfectly predicted on the basis of tot e bo
QUESTION 3 Let Y1, Y2, ..., Yn denote a random sample of size n from a population whose density is given by (Parcto distribution). Consider the estimator β-Yu)-min(n, Y, where β is unknown (a) Derive the bias of the estimator β. (b) Derive the mean square error of B. , Yn).
Problem 2: Let (X1,... Xn) denote a random variable from X having density fx(x) = 1/ β,0 < x < β where β > 0 is an unknown param eter. Explain why the Cramer Rao Theorem cannot be applied to show that an unbiased estimator of β is MVU. (Hint: see slides. Condition (A) of Cramer Rao Theorem)
MA2500/18 8. Let X be a random variable and let 'f(r; θ) be its PDF where θ is an unknown scalar parameter. We wish to test the simple null hypothesis Ho: 0 against the simple alternative Hi : θ-64. (a) Define the simple likelihood ratio test (SLRT) of Ho against H (b) Show that the SLRT is a most powerful test of Ho against H. (c) Let Xi, X2.... , X be a random sample of observations from the Poisson(e)...
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