Search Results for "stochastic"
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Showing 42 open source projects for "stochastic"
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DifferentialEquations.jl
Multi-language suite for high-performance solvers of equations
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research which routinely outperform the “standard” C/Fortran methods, and include algorithms optimized... -
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OrdinaryDiffEq.jl
High performance ordinary differential equation (ODE)
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research that routinely outperform the “standard” C/Fortran methods, and include algorithms optimized... -
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DeepXDE
A library for scientific machine learning & physics-informed learning
...Solving forward/inverse integro-differential equations (IDEs) [SIAM Rev.] fPINN: solving forward/inverse fractional PDEs (fPDEs) [SIAM J. Sci. Comput.] NN-arbitrary polynomial chaos (NN-aPC): solving forward/inverse stochastic PDEs (sPDEs) [J. Comput. Phys.] PINN with hard constraints (hPINN): solving inverse design/topology optimization [SIAM J. Sci. Comput.] Residual-based adaptive sampling [SIAM Rev., arXiv] Gradient-enhanced PINN (gPINN) [Comput. Methods Appl. Mech. Eng.] PINN with multi-scale Fourier features [Comput. Methods Appl. Mech. Eng.] -
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LINE Solver
Queueing Theory Algorithms
LINE is an open-source software package to analyze queueing models via analytical methods and simulation. The solver is available for Java/Kotlin, MATLAB, and Python. LINE features algorithms for the solution of open queueing systems (e.g., M/M/1, M/M/k, M/G/1, ...), open and closed queueing networks, and layered queueing networks. Additional details are available on the project website: http://line-solver.sf.net. -
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XMDS
Fast integrator of stochastic partial differential equations
XMDS is a code generator that integrates equations. You write them down in human readable form in a XML file, and it goes away and writes and compiles a C++ program that integrates those equations as fast as it can possibly be done in your architecture. -
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Java Modelling Tools is a suite of scientific tools for performance analysis and modelling using queueing theory and colored stochastic Petri nets. Models are solved either with analytical, asymptotic or simulation methods; workload characterization tools are also included in the suite. See the project website for more details: http://jmt.sf.net
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Generic data-assimilation toolbox written in java, with native (c and fortran) libraries for high performance computing. Provides tools to couple to your own model and a wide range of algorithms, ranging from parameter calibration to Kalman filters.
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Data Envelopment Analysis using Stata
Unified Data Envelopment Analysis commands for Stata
DEAS provides Data Envelopment Analysis tools for Stata. Version 2.0 is a major update centered on a unified dea command for Stata 16 or later. It consolidates sixteen DEA model families into one interface, keeps backward compatibility with the original inputs = outputs syntax, and adds a fast Mata two-phase revised simplex engine alongside Stata's LinearProgram() IPM engine. The package supports radial technical efficiency (CCR/BCC), SBM, additive model, radial and SBM super-efficiency,... -
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...Zgoubi simulates beam dynamics and polarization in a variety of accelerators (storage ring, synchrotron, cyclotron, betatron, microtron, FFAG, multi-pass ERL, etc) and optical systems (beam lines, magnetic and electrostatic optical components, time-of-flight and mass spectrometers, etc). The code includes built-in fitting procedures with a wide variety of constraints; stochastic SR energy loss; the tracking of synchrotron radiation (SR) Poynting vector; space charge models; various Monte Carlo procedures, etc. Contact: francoisgmeot@gmail.com Documentation (History of accelerators that zgoubi deals with, theory, tutorials): https://link.springer.com/book/10.1007/978-3-031-59979-8 https://link.springer.com/book/10.1007/978-3-031-16715-7, Chap. 14.
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StochSD
CSS package for contin., discrete and combined modelling & simulation
...In particular, StochSD includes features for stochastic modelling and post analysis of multiple simulations followed by presentation of the results in statistical form. Tools for Sensitivity Analysis, Optimization and Statistical Analysis are parts of StochSD. -
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MesoRD is a stochastic and deterministic simulator of coupled chemical reactions and diffusions in space.
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Bridge.jl
A statistical toolbox for diffusion processes
Statistics and stochastic calculus for Markov processes in continuous time, include univariate and multivariate stochastic processes such as stochastic differential equations or diffusions (SDE's) or Levy processes. -
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ABC-SysBio implements likelihood free parameter inference and model selection in dynamical systems. It is designed to work with both stochastic and deterministic models written in Systems Biology Markup Language (SBML).
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MED-FOES
An Agent-Based Simulation of Invasive Pest Insects
MED-FOES is an implementation of a stochastic Agent-Based Simulation (ABS) system for analyzing demographic changes in a single population of Medfly (Ceratitis capitata) over time. The simulation currently takes population extinction as a given because it aims to give us better estimates of necessary quarantine lengths in areas where Medfly is not currently established but does repeatedly invade. -
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StochPy - Stochastistic modeling in Python - is an easy-to-use package, which provides several stochastic simulation algorithms and unique analysis techniques, which can be used for stochastic simulations of biochemical systems.
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Virus QSP Modeling
C++ and Python code for simulating RNA virus replication
Stochastic simulation model of poliovirus Sabin-to-Mahoney genetic state transition (C++ code). Models genotypes, virus populations, and quasispecies cloud. Simulates replication error and copy-choice recombination. Various parameters guiding the model are user-specified. Python code post-processes simulation output to produce report files. -
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RSSA
Rejection-based stochastic simulation algorithm (RSSA)
Rejection-based stochastic simulation algorithm (RSSA) is an efficient exact algorithm for doing stochastic simulation of biochemical reaction systems. RSSA improves over state of the art of stochastic simulations by avoiding and collapsing as much the number of propensity updates. -
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Molecular Measurer
Parallel, Stochastic Measurement of Molecular Surface Area
A program to measure molecular surface area. The algorithm is GPU-accelerated using CUDA and is described in the research paper linked from the project home page. The input to the program is xyzr files, which can be generated from pdb files. -
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abc-sde
approximate Bayesian computation for stochastic differential equations
A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic differential equation models. It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. -
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Technical analysis library with indicators like ADX, MACD, RSI, Stochastic, TRIX... includes also candlestick pattern recognition. Useful for trading application developpers using either Excel, .NET, Mono, Java, Perl or C/C++.
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libSDE
Java library for simulating Stochastic Differential Equations (SDE)
Latest releases: http://tschaffter.ch/projects/libsde/ -
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SPiM2Eclipse
Eclipse plugin for Stochastic Pi Machine
Stochastic Pi Machine (SPiM), created by Microsoft, is a programming language for modeling biological processes. Two tools are available from Microsoft for simulation. A web application Visual SPiM, and a destkop application SPiM Player. Both simulation tools require to be run on a Windows platform. Fortunately Microsoft has also released a command line version for Linux and Mac OS based on OCAML however this version will only output a CSV file for the simulation results. ... -
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simbTUM
Simulation of stochastic processes and ODE models in biology.
SIMulation of Biological systems (developed at the TU Munich) This program allows to define ODE-models or stochastic compartemental models of biological processes, to simulate, to fit data and to do some statistics (fitting and statistics for deterministic models only). -
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SPSens
Stochastic parameter sensitivity analysis for chemical networks
SPSens is a complete software package written in C that estimates parameter sensitivities for stochastic models of chemical and biochemical reaction networks using Monte Carlo (MC) stochastic simulations. It is possible to estimate sensitivities with respect to system parameters using the following algorithms: finite difference methods (crude monte carlo, common reaction path, coupled finite differences); likelihood ratio methods; and regularized pathwise derivatives. ...