Monte-carlo-simulation Libraries

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Monte-carlo-simulation Libraries

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GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to address parameter and model uncertainties.

Open-source, implicit 3D structural geological modeling in Python. We provide the latest release version of GemPy via PyPi package services. We highly recommend using PyPi, The following versions are…

UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.

To engage in conversations about uncertainty quantification, or ask question about UQpy usage and functionality refer to the UQpy's discussions tab: UQpy (Uncertainty Quantification with python) is a…

Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning

Here you find my IPython (Jupyter) notebooks from my blog (ipythonquant.wordpress.org). Feel free to download the samples and play around with them.

Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.

Required Files: Linear regression is a linear approach to model the relationship between a scalar response (dependent varaible) and one or more explanatory variables (independent variables). The case…

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