Showing 6 open source projects for "process"

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  • 1

    Excelsi-R

    Excel's Interface to R

    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.
    Downloads: 0 This Week
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  • 2
    QPNet

    QPNet

    Synchronous Petri Nets' emulator

    QPNet (Quick Petri Net) is a fast Petri Nets' emulator, created by students of Moscow State Technical University of Radio Engineering, Electronics and Automation. It brings benefits for the educational process, while being under further development and extension. QPNet это быстрый эмулятор сетей Петри, созданный студентами МИРЭА. Он применяется в учебном процессе, а так же продолжает разрабатываться и эволюционировать.
    Downloads: 1 This Week
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  • 3
    phcfM

    phcfM

    R package for modelling anthropogenic deforestation

    ...It was named after the REDD+ pilot-project 'programme holistique de conservation des forêts à Madagascar'. phcfM includes two main functions: (i) demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models and (ii) deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data and Binomial logistic regression models with variable time-intervals between land-cover observations. The two functions use embedded Gibbs samplers written in C++ with the Scythe statistical library to reduce computational time.
    Downloads: 0 This Week
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  • 4
    The project simulates a generic agent based market model. The aim is to explore intimately, by simulation, the process of price formation and the market microstructure.
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  • 5
    T3S Tool

    T3S Tool

    Learning Stochastic Discrete Event Systems

    Stochastic discrete event system analysis and verification are essential in order to ensure reliability in such systems. However, models that cannot be constructed with an hand-made process need to be learned. Thus, the SDES toolbox proposes an automated solution that is embedded in Matlab to learning and analisis generalized semi-Markov processes.
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  • 6
    The CRISP package here developed utilizes an algorithm that describes a many-body intranuclear cascade (INC) and evaporation/fission/multifragmentation competition process.
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