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Free and open software for applied statistics. A comparison and a case study in biometrics

Niewiadomska E., Niewiadomski A.

Journal of Applied Computer Science

2011

Vol. 19, nr 1

65-83

This article is intended to be a position paper on advantages of free and open software for statistics and its applications to biometrics and biostatistics. Especially, the authors focus on the R package viewed as a new and still insufficiently recognized or received by the scientists, researchers, students, etc. Sample statistical computations and tests in biometrics are presented, and the most common functions and procedures are analysed and compared. Although this is a position paper from the point of view of applied computer science, the authors briefly present some original results within applied statistics (in particular: biometrics) and related computational methods using dedicated software.

Node assignment problem in Bayesian networks

Polańska J., Borys D., Polański A.

International Journal of Applied Mathematics and Computer Science

2006

Vol. 16, no 2

233-240

This paper deals with the problem of searching for the best assignments of random variables to nodes in a Bayesian network (BN) with a given topology. Likelihood functions for the studied BNs are formulated, methods for their maximization are described and, finally, the results of a study concerning the reliability of revealing BNs’ roles are reported. The results of BN node assignments can be applied to problems of the analysis of gene expression profiles.