User Sergio

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Is highly correlated factors in a prediction model a problem?

answered May 15, 2014 at 11:03

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How can I recognize dramatic changes in a set of observations?

answered May 16, 2014 at 17:38

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Naive Line Search for Gradient Descent

answered May 26, 2014 at 19:39

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Autocorrelation, Durbin-Watson and non time-series data

answered May 28, 2014 at 6:58

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Predicting based upon categorical data and one numeric datatype

answered May 28, 2014 at 9:43

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Problem in computing the Variance of Regression Estimator

answered May 28, 2014 at 10:26

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Understanding regression model with and without intercepts

answered Jul 15, 2021 at 23:15

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Setting a proper prior distribution on sigma for Bayesian Regression

answered May 29, 2014 at 11:00

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How can I apply LR with non-linear features?

answered May 21, 2014 at 10:12

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Using all categorical values as regression predictors in R

answered Jun 3, 2014 at 20:24

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Expectation of binomial distribution

answered May 13, 2014 at 6:46

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Hyper-geometric Probability Distribution in item defect problem

answered May 12, 2014 at 10:24

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OLS Coefficient estimator; Transformation from Matrix to sum of matrices form

answered May 13, 2014 at 13:57

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Sample mean of independent, normally-distributed variables

answered May 17, 2014 at 21:05

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Introduction to statistical learning Ch. 3 Pages 65-66

answered Jul 14, 2021 at 22:36

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How to show that the variance of an estimator of a model without intercept is neccessary smaller than the var of one with an intercept

answered Jan 27, 2021 at 13:20

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linearity in parameter assumption - implication for the Gauss-Markov theorem

answered Mar 22, 2021 at 23:43

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Intuition for relationship between variance of geometric and exponential distributions

answered Sep 29, 2020 at 10:25

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Show change of expression of sample variance and explain the distribution

answered Sep 15, 2020 at 16:56

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Unintuitive result: Multiple Linear Regression coefficients

answered Sep 11, 2020 at 21:06

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Why should we compare estimates of generalized linear model with its corresponding standard errors?

answered Jul 20, 2020 at 15:37

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Covariance matrix for p dimensional vector

answered Jul 29, 2020 at 22:38

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How to intuitively visualize measure theory concepts via diagrams?

answered Aug 2, 2020 at 13:25

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Why is sample mean talked about when the sample is not a random variable?

answered Jun 12, 2020 at 11:53

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How to interpret multiple calls of rnorm() function in R?

answered Jul 13, 2020 at 8:46

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Why do sources claim that linear regression assumes little to no multicollinearity, among other "assumptions"?

answered May 22, 2020 at 7:16

Stack Exchange Network

146 Answers

Is highly correlated factors in a prediction model a problem?

How can I recognize dramatic changes in a set of observations?

Naive Line Search for Gradient Descent

Autocorrelation, Durbin-Watson and non time-series data

Predicting based upon categorical data and one numeric datatype

Problem in computing the Variance of Regression Estimator

Understanding regression model with and without intercepts

Setting a proper prior distribution on sigma for Bayesian Regression

How can I apply LR with non-linear features?

Using all categorical values as regression predictors in R

Expectation of binomial distribution

Hyper-geometric Probability Distribution in item defect problem

OLS Coefficient estimator; Transformation from Matrix to sum of matrices form

Sample mean of independent, normally-distributed variables

Introduction to statistical learning Ch. 3 Pages 65-66

How to show that the variance of an estimator of a model without intercept is neccessary smaller than the var of one with an intercept

linearity in parameter assumption - implication for the Gauss-Markov theorem

Intuition for relationship between variance of geometric and exponential distributions

Show change of expression of sample variance and explain the distribution

Unintuitive result: Multiple Linear Regression coefficients

Why should we compare estimates of generalized linear model with its corresponding standard errors?

Covariance matrix for p dimensional vector

How to intuitively visualize measure theory concepts via diagrams?

Why is sample mean talked about when the sample is not a random variable?

How to interpret multiple calls of rnorm() function in R?

Why do sources claim that linear regression assumes little to no multicollinearity, among other "assumptions"?