This article provides a review of software packages for fitting either marginal or random effects models to correlated survival data. Six packages are considered: SAS, Stata, S-Plus and R, MLwiN, and ...

We have conducted a large-scale comparative study of software packages developed in the context of SMLM, including recently developed algorithms. We designed realistic data that are generic and cover ...

SANTA BARBARA, Calif.--(BUSINESS WIRE)--Oxford Instruments Asylum Research today announces the release of AR Maps, a new and powerful data analysis software package for the Jupiter XR atomic force ...

Schools districts can choose from a dizzying array of software products to analyze student-achievement data. Now, three researchers have published a paper to help them make an educated choice. The ...

Researchers at the Department of Energy's Oak Ridge National Laboratory have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning ...

Delmic and Digital Surf are proud to bring to market new CL Workspace software powered by Mountains ® technology, an innovative analysis solution for use with Delmic’s advanced cathodoluminescence (CL ...

The R programming language is quickly gaining popular ground against the traditional statistics packages such as SPSS, SAS and MATLAB, at least according to one data statistician who teaches the ...

Simply put by one of its staunchest advocates, "R is the most powerful statistical computing language on the planet; there is no statistical equation that cannot be calculated in R." Beyond "just" a ...