Fast and Robust Surrogate Variable Analysis
Introduces a fast and efficient Surrogate Variable Analysis algorithm that captures variation of unknown sources (batch effects) for high-dimensional data sets. The algorithm is built on the 'irwsva.build' function of the 'sva' package and proposes a revision on it that achieves more than 10 times faster running time while trading no accuracy loss in return.

Introduces a fast and efficient Surrogate Variable Analysis algorithm that captures variation of unknown sources (batch effects) for high-dimensional data sets. The algorithm is built on the 'irwsva.build' function of the 'sva' package and proposes a revision on it that achieves an order of magnitude faster running time while trading no accuracy loss in return.

Online Unsupervised Outlier Detection Using Finite Mixtures with
Discounting Learning Algorithms
Addressing the problem of outlier detection from the viewpoint of statistical learning theory. This method is proposed by Yamanishi, K., Takeuchi, J., Williams, G. et al. (2004) <DOI:10.1023/B:DAMI.0000023676.72185.7c>. It learns the probabilistic model (using a finite mixture model) through an on-line unsupervised process. After each datum is input, a score will be given with a high one indicating a high possibility of being a statistical outlier.

A set of tools developed by the Foundation SmarterPoland.pl
Tools for accessing and processing datasets presented on
the blog SmarterPoland.pl.

Tools for Accessing Various Datasets Developed by the Foundation
SmarterPoland.pl
Tools for accessing and processing datasets presented on the blog SmarterPoland.pl. Among all: functions for downloading data from eurostat database, coordinates from Google Maps and data from GUS (Central Statistical Office of Poland).
R (>= 2.10), rjson, ggplot2, httr, htmltools

Tools for accessing and processing datasets prepared by the Foundation SmarterPoland.pl. Among all: access to API of Google Maps, Central Statistical Office of Poland, MojePanstwo, Eurostat, WHO and other sources.