lcqfly's Stars
rlabbe/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
rlabbe/filterpy
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
uncertainty-toolbox/uncertainty-toolbox
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
mavillan/py-hausdorff
Fast computation of Hausdorff distance in Python
PredictiveScienceLab/uq-course
Introduction to Uncertainty Quantification
pygpc-polynomial-chaos/pygpc
A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method
cossan-working-group/OpenCossan
OpenCossan is an open and free toolbox for uncertainty quantification and management.
tyliu22/Fractional-Kalman-filter-algorithms
fractional Kalman filter algorithms source code for SISO fractional order systems, including: fractional extended Kalman filter (FEKF), fractional central Kalman filter (FCDKF), fractional unscented Kalman filter (FUKF) and fractional particle filter (FPF)
dmitriy-kats/LevelSetSwirlFEMandFVM
Level set modeling of multi-phase flow in a velocity field using the finite element and finite volume methods
Genesis2011/Fractional-Order_Differential_Equations
分数阶微分方程实例求解
davidnsousa/mcsd
MATLAB/Octave tool for Monte-Carlo simulations of diffusion in biological tissues
galenwilkerson/statistical-mechanics
Jupyter Notebooks of Leonard Susskind's Statistical Mechanics lectures
jgomezdans/eoldas
An Earth Observation Land Data Assimilation System (EO-LDAS)
Ivan-LIEBGOTT/Livre_2018a_English
Book 2018a English
magudelo/DataAssimilationToolboxMatlab
Svdvoort/OpenPC
An open source multi-element generalized polynomial chaos toolbox for matlab
Andrewpensoneault/Lorenz_63_Stochastic_Galerkin_EnKF
PCE-EnKF base on Dongbin Xiu's paper "A Generalized Polynomial Chaos Based Ensemble Kalman Filter"
ifgovh/Anomalous-diffusion-dynamics-of-SGD
code for paper "Anomalous diffusion dynamics of learning in deep neural networks"
zhouyifan233/Split-Merge-MCMC-for-Gaussian-Mixture-Model.matlab
A matlab implementation of "A Split-Merge Markov Chain Monte Carlo Procedure for the Dirichlet Process Mixture Model"
behzadasd/Open-Channel-Hydraulics-GUI
Open Channel Flow Hydraulics tool with PSO Solver and Graphical User Interface
hammouc/Parametric_Uncertainty_Quantification_option_pricing
This repository includes Matlab codes/routines that were used in my Bachelor thesis entitled "Numerical Methods For Uncertainty Quantification In Option Pricing" that can be found in: https://www.researchgate.net/publication/330005261_Numerical_Methods_For_Uncertainty_Quantification_In_Option_Pricing.
harshravishukla/LDI
These codes are used to test the leakage detection index method on a buried pipeline.
mscipio/MATLABtools___nbin_mu
Negative Binomial Distribution: update of the Matlab functions related to NBin distribution so that it can be defined with respect to mu (mean) and alpha (dispersion) parameters
suryakiranmg/Stochastic-Simulations-Proj8-Markov-Chain-Monte-Carlo-Optimisation-Minimum-path
Stratification and importance sampling in Monte Carlo Estimation Simulation, Gibbs Sampling, Optimisation using Schwefel fuction - global minimum using simulated annealing, Simulation using exponential, polynomial and logarithmic colling schedule, Simulated annealing simulation to determine a minimal path between 48 US state capitals by road beginning from Sacramento, California.
UNSW-CEEM/MC-ELECT
MC-ELECT (Monte Carlo Electricity Generation Portfolio Assessment Tool)
Andrewpensoneault/EKF-Parameter-Estimation
Extended Kalman Filter (Currently only contains OLS for Lotka–Volterra equation ODE)
AnnGareeva/Monte-Carlo-Simulation-
Monte‐Carlo Simulation Generate distribution of 0.01 quantile (1% percentile) of 10-‐days overlapping proportional returns obtained from the 3-‐years timeseries (750 observations) of 1-‐day returns. Original timeseries is generated using stable distribution with the following parameters: alpha = 1.7; beta = 0.0; gamma = 1.0; delta = 1.0. Show, either numerically or theoretically, that the chosen number of Monte-‐ Carlo trials is sufficient. Requirements: The task must be solved in R. Program code should be clearly written and well commented. Code must be presented along with report comprising all necessary mathematical expressions, description of results and conclusions. Hint: 1-‐day returns: r1 = Pi+1 − Pii P , i=1…751 i and Pi is price at i-‐th day. n-‐days returns: rni = Pi+n − Pi P i
awetscherek/bloodMC
Monte Carlo simulation for diffusion in blood
ICHydro/MCAT
Monte-Carlo Analysis Toolbox
PunnagC/Structural-Analysis-with-Transfer-Matrix-Method
Structural analysis functions required for Transfer matrix Method Implementation