![Consider a random sample from the Poisson(0) distribution (e.g. this setup could apply to the number of arrests example from class) You may take it as given that if X ~Poisson(0) then E[X_ θ)41-30 +θ (rememeber this is this is the 4th central moment or one of the definitions of kuutosis 3- (this is another commonly used definition of the kurtosis) (no need to show any of these) a. You wish to estimate E[X-0)4] Since E(X) 392 + θ. Lets call this moment w.i.e. 2 -6, you are considering the estimator3 2 X (In other words, vou have replaced θ- the population mean in the expression of w, by analogy, with X- the sample mean - in the expression of the estimator Show that is consistent forw. Is this estimator unbiased? Can you tell what is the direction of its bias? Hint: To show consistency you need to show that lim(a) w.This follows immediately since g(X) is continuous and we can apply Slutskys theorem Regrading the direction of the bias, you need to check whether the function g(X) 3X2+X is convex or concave, meaning you can use Jensens inequality. If g(X) is neither convex, nor concave you cannot determine the direction of the bias](http://img.homeworklib.com/questions/1742db60-a893-11ec-baa2-758ad99d1d3a.png?x-oss-process=image/resize,w_560)
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steps? Thanks!
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Could you please give detailed
steps? Thanks!
Consider a random sample from the Poisson(0) distribution (e.g....
Please give detailed steps. Thank you. 5. Let {X, : i-1..n^ denote a random sample of...
Please give detailed steps. Thank you.
5. Let {X, : i-1..n^ denote a random sample of size n from a population described by a random varaible X following a Poisson(θ) distribution with PDF given by θ and var(X) θ (i.e. you do not You may take it as given that E(X) need to show these) a. Recall that an estimator is efficient, if it satisfies 2 conditions: 2) it achieves the Cramer-Rao Lower Bound (CLRB) for unbiased estimators: Show that...
Please give detailed steps. Thank you. 5. Let {X1, X2,..., Xn) denote a random sample of...
Please give detailed steps. Thank you.
5. Let {X1, X2,..., Xn) denote a random sample of size N from a population d escribed by a random variable X. Let's denote the population mean of X by E(X) - u and its variance by Consider the following four estimators of the population mean μ : 3 (this is an example of an average using only part of the sample the last 3 observations) (this is an example of a weighted average)...
If X, X2,..., Xn constitute a random sample from the population with pdf ffx) 0 elsewhere...
If X, X2,..., Xn constitute a random sample from the population with pdf ffx) 0 elsewhere a) ind the E(X) and hence show that X is a biased estimator of 0. What is the bias? b)What estimator based on X would be an unbiased estimator of 0? Why? nen( y1-0) y, > c Given g(y,)- show that Yı= min ( X1, X2, Х. ) is a consistent 0 otherwise estimator of the parameter 0 d) Obtain the mean of Y,....
linear stat modeling & regression please , i need the solution for Q3, but i copy Q2 because you need info from Q2 in order to answer Q3. 2) Suppose you have multiple regression set up YxXB...
linear stat modeling & regression
please ,
i need the solution for Q3, but i copy Q2 because you need
info from Q2 in order to answer Q3.
2) Suppose you have multiple regression set up YxXBp The ridge regression estimator is given by Here, llell'-Σ.< where is a vector of Vik. a) Find the expectation and variance-covariance matrix of Bridge, when X'X is a diagonal matrix with each diagonal entry is eqal to. Com pare these variances with the...
This is related to Machine Learning Problem We have talked about the fact that the sample...
This is related to Machine
Learning Problem
We have talked about the fact that the sample mean estimator X = 1 , X, is an unbiased estimator of the mean u for identically distributed X1, X2, ..., Xn: E(X) = p. The sample variance, on the other hand, is not an unbiased estimate of the true variance o2: for V = 12-1(X; - X), we get that E[V] = (1 - 02. Instead, the following bias-corrected sample variance estimator is...
2. Suppose XX2,X is a random sample from an exponential distribution with . Let X(1) minX1,X2,...
2. Suppose XX2,X is a random sample from an exponential distribution with . Let X(1) minX1,X2, Xn), the minimum of the sample mean (a) Show that the estimator 6nx is an unbiased estimator of 8. (hint: you were asked to derive the distribution of X for a random sample from an exponential distribution on assignment 2 -you may use the result) (b) X, the sample mean, is also an unbiased estimator of . Which of the unbiased estimators, or X,...
QUESTION 2 Let Xi.. Xn be a random sample from a N (μ, σ 2) distribution,...
QUESTION 2 Let Xi.. Xn be a random sample from a N (μ, σ 2) distribution, and let S2 and Š-n--S2 be two estimators of σ2. Given: E (S2) σ 2 and V (S2) - ya-X)2 n-l -σ (a) Determine: E S2): (l) V (S2); and (il) MSE (S) (b) Which of s2 and S2 has a larger mean square error? (c) Suppose thatnis an estimator of e based on a random sample of size n. Another equivalent definition of...
Please provide your answer with a detailed description on how you came to that answer please!...
Please provide your answer with a detailed description on how you
came to that answer please!
ECN 702 Econometrics II HW2 Due: Jan 29 1. Suppose the true conditional mean function is but by mistake, a researcher ran least square regression without the x term as in Assume cov (X,, U,)s 0, E [Xn]-O and E [x?J-1. Is hisher estimate consistent for Anf not, show which OLS assumption fails and discuss potential solutions. 2. Assume the structural equation is where...
I am looking for a solution for question number 2 ONLY with steps please, so I...
I am looking for a solution for question number 2 ONLY with steps
please, so I can find my mistake.
1. Suppose the true conditional mean function is but by mistake, a researcher ran least square regression without the X term as in Assume cov (Xi. Ui)s 0, E [Xn] = 0 and E [x?] = 1 . Is his/her estimate consistent for β? If not, show which OLS assumption fails and discuss potential solutions 2. Assume the structural equation...
2. Let X1,.n be a random sample from the density 0 otherwise Suppose n = 2m+...
2. Let X1,.n be a random sample from the density 0 otherwise Suppose n = 2m+ 1 for some integer m. Let Y be the sample median and Z = max(Xi) be the sample maximum (a) Apply the usual formula for the density of an order statistic to show the density of Y is (b) Note that a beta random variable X has density f(x) = TaT(可 with mean μ = α/(a + β) and variance σ2 = αβ/((a +s+...
Please give detailed steps. Thank you.
5. Let {X, : i-1..n^ denote a random sample of size n from a population described by a random varaible X following a Poisson(θ) distribution with PDF given by θ and var(X) θ (i.e. you do not You may take it as given that E(X) need to show these) a. Recall that an estimator is efficient, if it satisfies 2 conditions: 2) it achieves the Cramer-Rao Lower Bound (CLRB) for unbiased estimators: Show that...
Please give detailed steps. Thank you.
5. Let {X1, X2,..., Xn) denote a random sample of size N from a population d escribed by a random variable X. Let's denote the population mean of X by E(X) - u and its variance by Consider the following four estimators of the population mean μ : 3 (this is an example of an average using only part of the sample the last 3 observations) (this is an example of a weighted average)...
If X, X2,..., Xn constitute a random sample from the population with pdf ffx) 0 elsewhere a) ind the E(X) and hence show that X is a biased estimator of 0. What is the bias? b)What estimator based on X would be an unbiased estimator of 0? Why? nen( y1-0) y, > c Given g(y,)- show that Yı= min ( X1, X2, Х. ) is a consistent 0 otherwise estimator of the parameter 0 d) Obtain the mean of Y,....
linear stat modeling & regression
please ,
i need the solution for Q3, but i copy Q2 because you need
info from Q2 in order to answer Q3.
2) Suppose you have multiple regression set up YxXBp The ridge regression estimator is given by Here, llell'-Σ.< where is a vector of Vik. a) Find the expectation and variance-covariance matrix of Bridge, when X'X is a diagonal matrix with each diagonal entry is eqal to. Com pare these variances with the...
This is related to Machine
Learning Problem
We have talked about the fact that the sample mean estimator X = 1 , X, is an unbiased estimator of the mean u for identically distributed X1, X2, ..., Xn: E(X) = p. The sample variance, on the other hand, is not an unbiased estimate of the true variance o2: for V = 12-1(X; - X), we get that E[V] = (1 - 02. Instead, the following bias-corrected sample variance estimator is...
2. Suppose XX2,X is a random sample from an exponential distribution with . Let X(1) minX1,X2, Xn), the minimum of the sample mean (a) Show that the estimator 6nx is an unbiased estimator of 8. (hint: you were asked to derive the distribution of X for a random sample from an exponential distribution on assignment 2 -you may use the result) (b) X, the sample mean, is also an unbiased estimator of . Which of the unbiased estimators, or X,...
QUESTION 2 Let Xi.. Xn be a random sample from a N (μ, σ 2) distribution, and let S2 and Š-n--S2 be two estimators of σ2. Given: E (S2) σ 2 and V (S2) - ya-X)2 n-l -σ (a) Determine: E S2): (l) V (S2); and (il) MSE (S) (b) Which of s2 and S2 has a larger mean square error? (c) Suppose thatnis an estimator of e based on a random sample of size n. Another equivalent definition of...
Please provide your answer with a detailed description on how you
came to that answer please!
ECN 702 Econometrics II HW2 Due: Jan 29 1. Suppose the true conditional mean function is but by mistake, a researcher ran least square regression without the x term as in Assume cov (X,, U,)s 0, E [Xn]-O and E [x?J-1. Is hisher estimate consistent for Anf not, show which OLS assumption fails and discuss potential solutions. 2. Assume the structural equation is where...
I am looking for a solution for question number 2 ONLY with steps
please, so I can find my mistake.
1. Suppose the true conditional mean function is but by mistake, a researcher ran least square regression without the X term as in Assume cov (Xi. Ui)s 0, E [Xn] = 0 and E [x?] = 1 . Is his/her estimate consistent for β? If not, show which OLS assumption fails and discuss potential solutions 2. Assume the structural equation...
2. Let X1,.n be a random sample from the density 0 otherwise Suppose n = 2m+ 1 for some integer m. Let Y be the sample median and Z = max(Xi) be the sample maximum (a) Apply the usual formula for the density of an order statistic to show the density of Y is (b) Note that a beta random variable X has density f(x) = TaT(可 with mean μ = α/(a + β) and variance σ2 = αβ/((a +s+...
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