# 1923 search results for "regression"

February 6, 2014
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## Solutions for Multicollinearity in Regression(1)

February 3, 2014
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In multiple regression analysis, multicollinearity is a common phenomenon, in which two or more predictor variables are highly correlated. If there is an exact linear relationship (perfect multicollinearity) among the independent variables, the rank of X is less than k+1(assume the number of predictor variables is k), and the matrix will not be invertible. So the strong correlations … Continue reading...

## Princeton’s guide to linear modeling and logistic regression with R

January 31, 2014
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If you're new to the R language but keen to get started with linear modeling or logistic regression in the language, take a look at this "Introduction to R" PDF, by Princeton's Germán Rodríguez. (There's also a browsable HTML version.) In a crisp 35 pages it begins by taking you through the basics of R: simple objects, importing data,...

## Spurious Regression of Time Series

December 30, 2013
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## Twelve Days 2013: LASSO Regression

December 19, 2013
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Day Eight: LASSO Regression TL/DR LASSO regression (least absolute shrinkage and selection operator) is a modified form of least squares regression that penalizes model complexity via a regularization parameter. It does so by including a term proportional to $||\beta||_{l_1}$ in the objective function which shrinks coefficients towards zero, and can even eliminate them entirely. In that light, LASSO is a...

## Twelve Days 2013: LASSO Regression

December 19, 2013
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Day Eight: LASSO Regression TL/DR LASSO regression (least absolute shrinkage and selection operator) is a modified form of least squares regression that penalizes model complexity via a regularization parameter. It does so by including a term proportional to $||beta||_{l_1}$ in the objective function which shrinks coefficients towards zero, and can even eliminate them entirely. In that light, LASSO is a...

## Logistic Regression with R: step by step implementation part-2

December 8, 2013
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Welcome to the second part of series blog posts! In previous part, we discussed on the concept of the logistic regression and its mathematical formulation. Now, we will apply that learning here and try to implement step by step in R. (If you know concept of logistic regression then move ahead in this part, otherwise The post Logistic...

## Using R to replicate common SPSS multiple regression output

December 4, 2013
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(This article was first published on Jeromy Anglim's Blog: Psychology and Statistics, and kindly contributed to R-bloggers) The following post replicates some of the standard output you might get from a multiple regression analysis in SPSS. A copy of the code in RMarkdown format is available on github. The post was motivated by this previous post that discussed using...