This is an extremely fast implementation of a Naive Bayes classifier. This
package is currently the only package that supports a Bernoulli distribution, a Multinomial
distribution, and a Gaussian distribution, making it suitable for both binary features,
frequency counts, and numerical features. Another feature is the support of a mix of
different event models. Only numerical variables are allowed, however, categorical variables
can be transformed into dummies and used with the Bernoulli distribution.
The implementation is largely based on the paper
"A comparison of event models for Naive Bayes anti-spam e-mail filtering"
written by K.M. Schneider (2003) <doi:10.3115/1067807>. Any issues can be
submitted to: <https://github.com/mskogholt/fastNaiveBayes/issues>.

This is an extremely fast implementation of a Naive Bayes classifier. This
package is currently the only package that supports a Bernoulli distribution, a Multinomial
distribution, and a Gaussian distribution, making it suitable for both binary features,
frequency counts, and numerical features. Another feature is the support of a mix of
different event models. Only numerical variables are allowed, however, categorical variables
can be transformed into dummies and used with the Bernoulli distribution.
The implementation is largely based on the paper
"A comparison of event models for Naive Bayes anti-spam e-mail filtering"
written by K.M. Schneider (2003) <doi:10.3115/1067807.1067848>. Any issues can be
submitted to: <https://github.com/mskogholt/fastNaiveBayes/issues>.

Implementation of a simple algorithm designed for online multivariate changepoint detection of a mean in sparse changepoint settings. The algorithm is based on a modified cusum statistic and guarantees control of the type I error on any false discoveries, while featuring O(1) time and O(1) memory updates per series as well as a proven detection delay.

Foundations and Applications of Statistics Using R
Data sets and utilities to accompany
"Foundations and Applications of Statistics: an Introduction
using R" (R Pruim, published by AMS, 2011), a text covering
topics from probability and mathematical statistics at an advanced
undergraduate level.  R is integrated throughout, and access to all
the R code in the book is provided via the snippet function.
MASS, faraway, Hmisc, DAAG, multcomp, vcd, car, alr3,
corrgram, BradleyTerry2, cubature, Devore7, knitr