Question

Assessing bias and consistency of modified OLS estimator

score 36 · Answer 1 · 2021-11-18 22:13:58

36

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Assessing bias and consistency of modified OLS estimator

Published on 18 Nov 2021 - 22:13

score 27 · Answer 2 · 2021-11-28 11:38:11

27

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What happens to $\operatorname{Var}\left(\varepsilon_{i} \mid x_{i}\right)$ if there is heteroscedasticity?

Published on 28 Nov 2021 - 11:38

score 521 · Answer 3 · 2021-11-29 08:15:25

521

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The least squares estimators $\hat{\beta_0}$ and $\hat{\beta_1}$ are uncorrelated.

Published on 29 Nov 2021 - 8:15

score 378 · Answer 4 · 2026-03-26 22:15:00

378

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Variance of ridge regression estimator

Published on 26 Mar 2026 - 22:15

score 316 · Answer 5 · 2021-12-01 21:57:57

316

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Least Square Estimation of Linear Regression

Published on 01 Dec 2021 - 21:57

score 83 · Answer 6 · 2021-12-02 13:14:16

83

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Transform linear regression model with non-constant variance to constant variance

Published on 02 Dec 2021 - 13:14

score 948 · Answer 7 · 2026-03-26 22:14:08

948

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Bias of ridge estimator

Published on 26 Mar 2026 - 22:14

score 145 · Answer 8 · 2021-12-10 08:57:56

145

Views

$\text{MSE}$ as an unbiased estimator for $\sigma^2$

Published on 10 Dec 2021 - 8:57

score 47 · Answer 9 · 2021-12-14 01:57:13

47

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How to perform a two-way linear regression?

Published on 14 Dec 2021 - 1:57

score 56 · Answer 10 · 2021-12-17 23:07:27

56

Views

What's wrong with solving the least-squares problem here? (Simple question)

Published on 17 Dec 2021 - 23:07

score 30 · Answer 11 · 2021-12-19 23:52:18

Conceptual similarity between the normal equation in linear regression to find best parameters and an orthagonal projection in linear algebra?

score 23 · Answer 12 · 2021-12-21 14:23:17

23

Views

Which method would you use to ascertain the most important independent variables?

Published on 21 Dec 2021 - 14:23

score 127 · Answer 13 · 2026-03-27 04:23:31

127

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Working out the derivative of the log-likelihood for group LASSO

Published on 27 Mar 2026 - 4:23

score 143 · Answer 14 · 2021-12-23 19:44:11

143

Views

diagonalising (I-X(X^TX)^-1X^T where X is rank n-k, a square matrix dimension nxn, into a matrix with n-k 1 along the diagonal, and then zeros.

Published on 23 Dec 2021 - 19:44

score 41 · Answer 15 · 2026-02-23 15:32:45

41

Views

How to find out if two variables are independent

Published on 23 Feb 2026 - 15:32

List Question

Assessing bias and consistency of modified OLS estimator

What happens to $\operatorname{Var}\left(\varepsilon_{i} \mid x_{i}\right)$ if there is heteroscedasticity?

The least squares estimators $\hat{\beta_0}$ and $\hat{\beta_1}$ are uncorrelated.

Variance of ridge regression estimator

Least Square Estimation of Linear Regression

Transform linear regression model with non-constant variance to constant variance

Bias of ridge estimator

$\text{MSE}$ as an unbiased estimator for $\sigma^2$

How to perform a two-way linear regression?

What's wrong with solving the least-squares problem here? (Simple question)

Conceptual similarity between the normal equation in linear regression to find best parameters and an orthagonal projection in linear algebra?

Which method would you use to ascertain the most important independent variables?

Working out the derivative of the log-likelihood for group LASSO

diagonalising (I-X(X^TX)^-1X^T where X is rank n-k, a square matrix dimension nxn, into a matrix with n-k 1 along the diagonal, and then zeros.

How to find out if two variables are independent

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