Showing 5 open source projects for "monte carlo simulation"

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  • 1
    Monte Carlo eXtreme (MCX)

    Monte Carlo eXtreme (MCX)

    Physically accurate and validated GPU ray-tracer

    MCX is a GPU-accelerated, general-purpose, physically-accurate and feature-rich 3-D light transport simulator. It is one of the fastest simulators because it can use tens of thousands of GPU threads to simulate photons in parallel.
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    Downloads: 79 This Week
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  • 2
    Blueprint XAS
    Blueprint XAS is a Matlab-based suite designed for the processing and analysis of near-edge x-ray absorption spectroscopy (XAS) data. The suite is designed primarily to assist users in exploring reasonable fit solutions while minimizing user bias.
    Downloads: 3 This Week
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  • 3
    Orbit Determination Toolbox (ODTBX)

    Orbit Determination Toolbox (ODTBX)

    Advanced mission simulation and analysis tool

    The Orbit Determination Toolbox (ODTBX) is developed by the Navigation & Mission Design branch at NASA Goddard Space Flight Center as an advanced mission simulation and analysis tool used for concept exploration, proposal, early design phase, and/or rapid design center environments. ODTBX functions and utilities are combined in a flexible architecture that allows for modular development of navigation algorithms and simulations. The core ODTBX functionality is realized through a set of estimation commands that incorporate Monte Carlo data simulation, linear covariance analysis, and measurement processing at a generic level.
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    Downloads: 5 This Week
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  • 4
    Rand Tree

    Rand Tree

    Random Tree Generator for MatLab

    RandTree is a MatLab based tree simulator program where the algorithm is based on Honda's model. We have used probabilistic generation of branches in order to simulate visually realistic tree structures. This program is designed to generate branching structures with bifurcation branching pattern (sympodial branching). By changing the probabilities and branching angles, you can generate different shapes of trees.
    Downloads: 0 This Week
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  • 5
    ...Actually the parameter estimation methods were already far from the state-of-art when the project began in 2007 (!). The considered implemented parametric and non-parametric Monte Carlo likelihood methods were chosen for their ability to treat both one-dimensional and multivariate SDE systems, although the quality of the inferential results can't match those obtained using more advanced techniques. Nevertheless the toolbox capabilities to simulate numerical solutions of SDE systems are still valid and can serve as a useful starting point to those willing to simulate stochastic dynamical models easily.
    Downloads: 1 This Week
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