Essays about: "Hamiltonian Monte Carlo"
Showing result 1 - 5 of 8 essays containing the words Hamiltonian Monte Carlo.
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1. Analysing Regime-Switching and Cointegration with Hamiltonian Monte Carlo
University essay from Uppsala universitet/Statistiska institutionenAbstract : The statistical analysis of cointegration is crucial for inferring shared stochastic trends between variables and is an important area of Econometrics for analyzing long-term equilibriums in the economy. Bayesian inference of cointegration involves the identification of cointegrating vectors that are determined up to arbitrary linear combinations, for which the Gibbs sampler is often used to simulate draws from the posterior distribution. READ MORE
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2. Dynamic Covariance Modelling Using Generalised Wishart Processes
University essay from Lunds universitet/Matematisk statistikAbstract : Modern portfolio theory was pioneered by Markowitz who formulated the mean-variance problem, without which any discussion on quantitative approaches to portfolio selection would be incomplete. The framework boils down to finding the expected return $\mu$ and covariance $\Sigma$, after which the solution is proportional to $\Sigma^{-1}\mu$. READ MORE
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3. Evaluation of Probabilistic Programming Frameworks
University essay from Uppsala universitet/Statistiska institutionenAbstract : In recent years significant progress has been made in the area of Probabilistic Programming, contributing to a considerably easier workflow for quantitative research in many fields. However, as new Probabilistic Programming Frameworks (PPFs) are continuously being created and developed, there is a need for finding ways of evaluating and benchmarking these frameworks. READ MORE
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4. Assessment of Modern Statistical Modelling Methods for the Association of High-Energy Neutrinos to Astrophysical Sources
University essay from KTH/Matematisk statistikAbstract : The search for the sources of astrophysical neutrinos is a central open question in particle astrophysics. Thanks to substantial experimental efforts, we now have large-scale neutrino detectors in the oceans and polar ice. READ MORE
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5. Efficient Sampling of Gaussian Processes under Linear Inequality Constraints
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : In this thesis, newer Markov Chain Monte Carlo (MCMC) algorithms are implemented and compared in terms of their efficiency in the context of sampling from Gaussian processes under linear inequality constraints. Extending the framework of Gaussian process that uses Gibbs sampler, two MCMC algorithms, Exact Hamiltonian Monte Carlo (HMC) and Analytic Elliptical Slice Sampling (ESS), are used to sample values of truncated multivariate Gaussian distributions that are used for Gaussian process regression models with linear inequality constraints. READ MORE
