Consider the zero intercept model given by Yi = B1Xi + ei (i=1,…,n) with the ei...
Consider the zero intercept model given by Yi = B1Xi + ei (i=1,…,n) with the ei normal, independent, with variance sigma^2. For this mode
(i) find the sum of (Yi –Yi-hat).
(ii) find the sum of (Yi – Yi-hat)Xi.
(iii) find the estimator of the error variance, sigma^2.
(iv) is the estimator of the error variance biased?
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Consider the zero intercept model given by Yi =
B1Xi + ei (i=1,…,n) with the
ei...
3. Consider the model Yi = Bo + Bixi +Ei, i = 1,2,3,.., N. Xi =...
3. Consider the model Yi = Bo + Bixi +Ei, i = 1,2,3,.., N. Xi = Oo + Qiyi + Ui, i = 1,2,3,.., N. Find the relationship between the estimates of a and B.
1. Consider a regression model Yi = x;ß +ei, i = 1,...,n. You estimate this model...
1. Consider a regression model Yi = x;ß +ei, i = 1,...,n. You estimate this model using the OLS estimator. (a) Present and discuss assumptions for the OLS estimation.
1) Consider n data points with 3 covariates and observations {xil, Гіг, xī,3, yi); i-1,.,n, and y...
1) Consider n data points with 3 covariates and observations {xil, Гіг, xī,3, yi); i-1,.,n, and you fit the following model, y Bo+B+B32+Br+e that is yi-An + ßiXiut Ali,2 + Asri,3 + Ei where є,'s are independent normal distribution with mean zero and variance ơ2 For a observed covariate vector-(1, ri, ^2, r3) (with the intercept and three regressor variables) and observed yg at that point a) write the expression for estimated variance for the fit zs at z. (Let...
1. Given data on (yi, xi) for i = 1, , n, consider the following least...
1. Given data on (yi, xi) for i = 1, , n, consider the following least square problem for a imple linear regression bo,b We assume the four linear regression model assumptions dicussed in class hold (i) Compute the partial derivatives of the objective function. (ii) Put the derived partial derivatives in (i) equal to zeros. Explain why the resulting equa tions are called normal equation'. (Hin wo n-dimesional vectors (viand (wi)- are normal-orthogonal ) if Σ-1 ui wi-0. )...
1. Suppose that Yi = Bo + B1Xi + €¡ where ; is N(0,0.6), Bo =...
1. Suppose that Yi = Bo + B1Xi + €¡ where ; is N(0,0.6), Bo = 2 and 31 = 1. (a) What are the conditional mean and standard deviation of Yị given that Xi = 1? What is P(Yi < 3|X; = 1)? (b) A regression model is a model for the conditional distribution of Yị given Xị. However, if we also have a model for the marginal distribution of X; then we can find the marginal distribution of...
7) Consider the intercept-only logistic regression model iBinomial (ni, p) i= 1,...,n yi independent log 1-p...
7) Consider the intercept-only logistic regression model iBinomial (ni, p) i= 1,...,n yi independent log 1-p -- ()M a) Find the MLE for o b) Find the Fisher Information I(a)E How would you estimate Var(a)?
7) Consider the intercept-only logistic regression model iBinomial (ni, p) i= 1,...,n yi independent log 1-p -- ()M a) Find the MLE for o b) Find the Fisher Information I(a)E How would you estimate Var(a)?
A simple linear regression model is given as follows Yi = Bo + B1Xi+ €i, for...
A simple linear regression model is given as follows Yi = Bo + B1Xi+ €i, for i = 1, ...,n, where are i.i.d. following N (0, o2) distribution. It is known that x4 n, and x = 0, otherwise. Denote by n2 = n - ni, Ji = 1 yi, and j2 = 1 1. for i = 1, ... ,n1 < n2 Lizn1+1 Yi. n1 Zi=1 1. Find the least squares estimators of Bo and 31, in terms of...
Consider the least-squares residuals ei-yi-yi, 1, 2, . . . , linear regression model. Find the...
Consider the least-squares residuals ei-yi-yi, 1, 2, . . . , linear regression model. Find the variance of the residuals Var(e). Is the vari- ance of the residuals a constant? Discuss. n,from the simple
Exercise5 Consider a linear model with n -2m in which yi Bo Pi^i +ei,i-1,...,m, and Here €1, ,En are 1.1.d. from N(0,ơ)...
Exercise5 Consider a linear model with n -2m in which yi Bo Pi^i +ei,i-1,...,m, and Here €1, ,En are 1.1.d. from N(0,ơ), β-(A ,A, β), and σ2 are unknown parameters, zı, known constants with x1 +... + Xm-Tm+1 + +xn0 , zn are 1, write the model in vector form as Y = Xß+ε describing the entries in the matrix X. 2, Determine the least squares estimator β of β.
Exercise5 Consider a linear model with n -2m in which...
4. Consider the model yi-β +82i + ei. Find the OLS estimator for β.
4. Consider the model yi-β +82i + ei. Find the OLS estimator for β.
3. Consider the model Yi = Bo + Bixi +Ei, i = 1,2,3,.., N. Xi = Oo + Qiyi + Ui, i = 1,2,3,.., N. Find the relationship between the estimates of a and B.
1. Consider a regression model Yi = x;ß +ei, i = 1,...,n. You estimate this model using the OLS estimator. (a) Present and discuss assumptions for the OLS estimation.
1) Consider n data points with 3 covariates and observations {xil, Гіг, xī,3, yi); i-1,.,n, and you fit the following model, y Bo+B+B32+Br+e that is yi-An + ßiXiut Ali,2 + Asri,3 + Ei where є,'s are independent normal distribution with mean zero and variance ơ2 For a observed covariate vector-(1, ri, ^2, r3) (with the intercept and three regressor variables) and observed yg at that point a) write the expression for estimated variance for the fit zs at z. (Let...
1. Given data on (yi, xi) for i = 1, , n, consider the following least square problem for a imple linear regression bo,b We assume the four linear regression model assumptions dicussed in class hold (i) Compute the partial derivatives of the objective function. (ii) Put the derived partial derivatives in (i) equal to zeros. Explain why the resulting equa tions are called normal equation'. (Hin wo n-dimesional vectors (viand (wi)- are normal-orthogonal ) if Σ-1 ui wi-0. )...
1. Suppose that Yi = Bo + B1Xi + €¡ where ; is N(0,0.6), Bo = 2 and 31 = 1. (a) What are the conditional mean and standard deviation of Yị given that Xi = 1? What is P(Yi < 3|X; = 1)? (b) A regression model is a model for the conditional distribution of Yị given Xị. However, if we also have a model for the marginal distribution of X; then we can find the marginal distribution of...
7) Consider the intercept-only logistic regression model iBinomial (ni, p) i= 1,...,n yi independent log 1-p -- ()M a) Find the MLE for o b) Find the Fisher Information I(a)E How would you estimate Var(a)?
7) Consider the intercept-only logistic regression model iBinomial (ni, p) i= 1,...,n yi independent log 1-p -- ()M a) Find the MLE for o b) Find the Fisher Information I(a)E How would you estimate Var(a)?
A simple linear regression model is given as follows Yi = Bo + B1Xi+ €i, for i = 1, ...,n, where are i.i.d. following N (0, o2) distribution. It is known that x4 n, and x = 0, otherwise. Denote by n2 = n - ni, Ji = 1 yi, and j2 = 1 1. for i = 1, ... ,n1 < n2 Lizn1+1 Yi. n1 Zi=1 1. Find the least squares estimators of Bo and 31, in terms of...
Consider the least-squares residuals ei-yi-yi, 1, 2, . . . , linear regression model. Find the variance of the residuals Var(e). Is the vari- ance of the residuals a constant? Discuss. n,from the simple
Exercise5 Consider a linear model with n -2m in which yi Bo Pi^i +ei,i-1,...,m, and Here €1, ,En are 1.1.d. from N(0,ơ), β-(A ,A, β), and σ2 are unknown parameters, zı, known constants with x1 +... + Xm-Tm+1 + +xn0 , zn are 1, write the model in vector form as Y = Xß+ε describing the entries in the matrix X. 2, Determine the least squares estimator β of β.
Exercise5 Consider a linear model with n -2m in which...
4. Consider the model yi-β +82i + ei. Find the OLS estimator for β.
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