Successful investing requires the ability to distinguish long-term trends from the short-term noise that moves stock prices on a minute-to-minute basis. One way to tune out the random oscillations and ...

Successful investing requires the ability to distinguish long-term trends from the short-term noise that moves stock prices on a minute-to-minute basis. One way to tune out the random oscillations and ...

Now that you've got a good sense of how to "speak" R, let's use it with linear regression to make distinctive predictions. The R system has three components: a scripting language, an interactive ...

Our teacher already knows there is a positive relationship between how much time was spent on an essay and the grade the essay gets, but we’re going to need some data to demonstrate this properly.

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

We propose a new method for estimation in linear models. The `lasso' minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant.

This is a preview. Log in through your library . Abstract 1. Residuals from linear regressions are used frequently in statistical analysis, often for the purpose of controlling for unwanted effects in ...

We describe how to conduct a regression analysis for competing risks data. The use of an add-on package for the R statistical software is described, which allows for the estimation of the ...