Search Results for "basic-256"

Less means - more power. The high performance open source package for statistical data analysis and applied mathematics AtteStat is an add-in for desktop versions of the Microsoft Excel spreadsheets. Both 32-bit and 64-bit in one package. The combination of the unsurpassed convenience of spreadsheets and the effective interception of Microsoft Excel exceptions (frontend) and the maximum speed of the C++ programming language (backend). Winner of contest Microsoft Office Extensions (PC...

Putting truth before show-off. The high performance open source package for statistical data analysis and applied mathematics Criterial is an add-in for all desktop versions of the LibreOffice Calc, Apache OpenOffice spreadsheets on any 64-bit operating systems. The combination of the unsurpassed convenience of spreadsheets as frontend and the maximum speed of the C++ programming language as backend. Contains user experience and the best ideas of projects AtteStat and StatAnt. Completely...

PlanetPack is a software tool developed to facilitate the radial-velocity time-series analysis for the goal of exoplanets detection, characterization, and basic dynamical simulations. The description of the main theoretic concepts, statistical methods and algorithms that PlanetPack implements, is given in the following refereed papers: R.V. Baluev 2013, Astronomy & Computing, V. 2, P. 18 (initial release); R.V. Baluev 2018, Astronomy & Computing, V. 25, P. 221 (update 3.0). The technical manual explaining the details of the practical use is available in the download archive here (see the /doc/ subfolder).

Excelsi-R is an Excel add-in that allows Excel spreadsheets to harness the power of the R statistical language by connecting to a running R process. R does not need to be installed on the computer running Excel, but it does require access to an R instance running Rserve (which can be on a remote computer). It supports incorporating R plots and graphs in an Excel workbook.

...Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic networks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems).

That project aims at studying and comparing typical airline IT methods, for instance RM-related algorithms. It works from a Unix/Linux/Mac command-line, and exposes basic APIs. It is being developed in C++, with Python wrappers for some components.

That project aims at studying and comparing typical airline IT methods, for instance RM-related algorithms. It works from a Unix/Linux/Mac command-line, and exposes basic APIs. It is being developed in C++, with Python wrappers for some components.