Fourier-Bayesian estimation of stochastic volatility models
Code used to run the numerical examples of "Bayesian Approach for Parameter estimation of Continuous-Time Stochastic Volatility Models using FFourier Transform Methods" by Merkle, Saporito and Targino (Statistics & Probability Letters, Vol. 156, 2020). Available here https://www.sciencedirect.com/science/article/pii/S0167715219302469 and here https://arxiv.org/abs/1812.10556
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This library was developed in order to facilitate rapid prototyping in Python of predictive machine-learning models using longitudinal medical data from an OMOP CDM-standard database.
📚 Descrição Neste curso da Dell aprofundamos nossos conhecimentos em Machine Learning. 🖥️ Aulas (Em curso) 1.1 - Python aplicado a Data Science 1.2
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River is a Python library for online machine learning. It is the result of a merger between creme and scikit-multiflow. River's ambition is to be the go-to library for doing machine learning on strea
Scikit-Pipes Scikit-Learn useful pre-defined Pipelines Hub Usage: Install scikit-pipes It's advised to install sklearn-genetic using a virtual env, in
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BartPy Introduction BartPy is a pure python implementation of the Bayesian additive regressions trees model of Chipman et al [1]. Reasons to use BART
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