# Posts Tagged ‘ glm ’

## Memory Management in R, and SOAR

May 8, 2012
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The more I’ve worked with my really large data set, the more cumbersome the work has become to my work computer.  Keep in mind I’ve got a quad core with 8 gigs of RAM.  With growing irritation at how slow … Continue reading →

## Confidence interval for predictions with GLMs

November 4, 2011
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Consider a (simple) Poisson regression . Given a sample where , the goal is to derive a 95% confidence interval for given , where is the prediction. Hence, we want to derive a confidence interval for the prediction, not the potential observation...

## Test Difference between Two Proportions & Plot Confidence Intervals

August 11, 2011
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..an illustrative example for testing proportions and presenting the results.the data: number of indigenous and alien plant species with and without vegetative reproduction. Hypothesis: The proportion of species with vegetative reproduction is differen...

## Model Validation: Interpreting Residual Plots

July 18, 2011
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When conducting any statistical analysis it is important to evaluate how well the model fits the data and that the data meet the assumptions of the model. There are numerous ways to do this and a variety of statistical tests to evaluate deviations from model assumptions. However, there is little general acceptance of any of the statistical tests. Generally...

## My residuals look weird… aren’t they ?

November 3, 2010
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Since I got the same question twice, let us look at it quickly....  Some students show me a graph (from a Poisson regression) which looks like that, and they asked "isn't it weird ?", i.e."residuals are null or positive... this is not what we...

## Studying joint effects in a regression

October 7, 2010
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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...

## R Commander – logistic regression

June 23, 2010
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We can use the R Commander GUI to fit logistic regression models with one or more explanatory variables. There are also facilities to plot data and consider model diagnostics. The same series of menus as for linear models are used to fit a logistic regression model. Fast Tube by Casper The “Statistics” menu provides access to various

## Measuring the length of time to run a function

March 16, 2010
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When writing R code it is useful to be able to assess the amount of time that a particular function takes to run. We might be interested in measuring the increase in time required by our function as the size of the data increases. To illustrate using the system.time function to calculate the time taken to

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