Update: Statistical Analysis with R is now available!I recently submitted the final drafts of all chapters of my R Beginner's Guide book, which is to be published through Packt. The official publishing timeline is set to December 2010, although the boo...
1042 search results for "regression"
Example 8.7: Hosmer and Lemeshow goodness-of-fit
The Hosmer and Lemeshow goodness of fit (GOF) test is a way to assess whether there is evidence for lack of fit in a logistic regression model. Simply put, the test compares the expected and observed number of events in bins defined by the predicted p...
Example 8.6: Changing the reference category for categorical variables
How can we change the reference category for a categorical variable? This question comes up often in a consulting practice.When including categorical covariates in regression models, there is a question of how to incorporate the categories. One simpl...
Data Mining in A Nutshell
# The following code may look rough, but simply paste into R or# a text editor (especially Notepad++) and it will look# much better.# PROGRAM NAME: MACHINE_LEARNING_R# DATE: 4/19/2010# AUTHOR : MATT BOGARD# PURPOSE: BASIC EXAMPLES OF MACHINE LEAR...
Principal Component Analysis (PCA) vs Ordinary Least Squares (OLS): A Visual Explanation
Over at stats.stackexchange.com recently, a really interesting question was raised about principal component analysis (PCA). The gist was “Thanks to my college class I can do the math, but what does it MEAN?” I felt like this a number of times in my life. Many of my classes were focused on the technical implementations they kinda
A Not Quite Random Number Generator (NQRNG)
I connected the instrumentation amplifier described in an earlier post to a piezoelectric transducer (buzzer) and made recordings at 5000 gain. The plot below shows 1000 such measurements over 1.0 seconds. There is a 4.0 second (at 1000Hz) sample of the data here piezo.csv. There is a clear sinusoidal signal in these data of about
10w2170, Banff [2]
![10w2170, Banff [2]](http://www.r-bloggers.com/wp-content/uploads/2010/09/img_7477-e1284331010214.jpg?w=450&h=293)
Over the two days of the Hierarchical Bayesian Methods in Ecology workshop, we managed to cover normal models, testing, regression, Gibbs sampling, generalised linear models, Metropolis-Hastings algorithms and of course a fair dose of hierarchical modelling. At the end of the Saturday marathon session, we spent one and half discussing some models studied by the 
Missing Data in R
Probably all of us have met the issue of handling missing data, from the basic portfolio correlation matrix estimation, to advanced multiple factor analysis, how to impute missing data remains a hot topic. Missing data are unavoidable, and more encompassing than the ubiquitous association of the term, irgoring missing data will generally lead to biased estimates. The...
Confidence Bands for Universal Scalability Models
In the recent GDAT class, confidence intervals (CI) for performance data were discussed. Their generalization to confidence bands (CB) for scalability projections using the USL model also came up informally. I showed a prototype plot but it was an ugly hack. Later requests from GDAT attendees to apply CBs to their own data meant I had...
Confidence Bands for Universal Scalability Models
In the recent GDAT class, confidence intervals (CI) for performance data were discussed. Their generalization to confidence bands (CB) for scalability projections using the USL model also came up informally. I showed a prototype plot but it was an ugly hack. Later requests from GDAT attendees to apply CBs to their own data meant I had...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
