# Posts Tagged ‘ regression ’

## Studying joint effects in a regression

October 7, 2010
By We've seen in the previous post (here)  how important the *-cartesian product to model joint effected in the regression. Consider the case of two explanatory variates, one continuous (, the age of the driver) and one qualitative (, gasoline ve...

## Visualization of regression coefficients (in R)

July 2, 2010
By Update (07.07.10): The function in this post has a more mature version in the “arm” package. See at the end of this post for more details. * * * * Imagine you want to give a presentation or report of your latest findings running some sort of regression analysis. How would you do it? This was exactly the question...

## Analysis of Covariance – Extending Simple Linear Regression

April 28, 2010
By The simple linear regression model considers the relationship between two variables and in many cases more information will be available that can be used to extend the model. For example, there might be a categorical variable (sometimes known as a covariate) that can be used to divide the data set to fit a separate linear

## Simple Linear Regression

April 23, 2010
By One of the most frequent used techniques in statistics is linear regression where we investigate the potential relationship between a variable of interest (often called the response variable but there are many other names in use) and a set of one of more variables (known as the independent variables or some other term). Unsurprisingly there

## Social Media Analytics Research Toolkit ([email protected]) Is Moving Into Private Beta

March 31, 2010
By

Download "Getting Started with the Social Media Analytics Research Toolkit" (pdf, 1.25 megabytes) Download the Social Media Analytics Research Toolkit My Social Media Analytics Research Toolkit is about to move into private beta. What's in the release?...

## In a nls star things might be different than the lm planet…

March 10, 2010
By

The nls() function has a well documented (and discussed) different behavior compared to the lm()’s. Specifically you can’t just put an indexed column from a data frame as an input or output of the model. __ nls(data ~ c + expFct(data,beta), data = time.data, + start = start.list) Error in parse(text = x) : unexpected

## CRU graph yet again (with R)

December 13, 2009
By IowaHawk has a excellent article attempting to reproduce the infamous CRU climate graph using OpenOffice: Fables of the Reconstruction. We thought we would show how to produced similarly bad results using R. If the re-constructed technique is close to what was originally done then so many bad moves were taken that you can’t learn much Related posts:The cranky guide...

## Introducing Influence.ME: Tools for detecting influential data in mixed models

April 29, 2009
By

I’m highly excited to announce that influence.ME is now available. Influence.ME is a new software package for R, providing statistical tools for detecting influential data in mixed models. It has been developed by Rense Nieuwenhuis, Ben Pelzer, a...

## R: Calculating all possible linear regression models for a given set of predictors

February 6, 2009
By Although the graphic at the left might not seem a 100% appropriate, it gives a hint to what I am about to do. I want to calculate all possible linear regression models with one dependent and several independent variables. I do not want to address bias and fitting issues or the question if this

## How to Recover the Missing X(1) for the USL Scalability Model

July 29, 2008
By When it comes to assessing application scalability, controlled measurements of the type that can be obtained with tools like Grinder or LoadRunner, are very useful because they provide a direct measurement of the throughput, X(N), as a function of the...
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