Sitting with a data set with too many variables? The SVD can be a valuable...

Next topic on logistic regression: the exact and the conditional logistic regressions. Exact logistic regression When the dataset is very small or severely unbalanced, maximum likelihood estimates of coefficients may be biased. An alternative is to use exact logistic regression, available in R with the elrm package. Its syntax is based on an events/trials formulation.

Below are my findings from the second data analysis project in Dr. Jeffery Leek’s John Hopkins Coursera class. Introduction I used the “Human Activity Recognition Using Smartphones Dataset” (UCI, 2013) to build a model. This data was recorded from a Samsung prototype smartphone with a built-in accelerometer. The purpose of my model was to recognize the type

Partial least squares projection to latent structures or PLS is one of my favorite modeling algorithms. PLS is an optimal algorithm for predictive modeling using wide data or data with rows << variables. While there is s a wealth of literature regarding the application of PLS to various tasks, I find it especially useful for biological

Short: I plot the frequency of college hockey championships by state using the maps package, and ggplot2 Note: this example is based heavily on the example provided athttp://www.dataincolour.com/2011/07/maps-with-ggplot2/ data reference:http://en.wikipedia.org/wiki/NCAA_Men%27s_Ice_Hockey_Championship Question of interestAs a good Minnesotan, I've believed for quite some time that the colder, Northern states enjoy a competitive advantage when it...

e-mails with the latest R posts.

(You will not see this message again.)