Essays about: "Markov chain Monte Carlo"
Showing result 1 - 5 of 53 essays containing the words Markov chain Monte Carlo.
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1. Branching Out with Mixtures: Phylogenetic Inference That’s Not Afraid of a Little Uncertainty
University essay from KTH/Matematisk statistikAbstract : Phylogeny, the study of evolutionary relationships among species and other taxa, plays a crucial role in understanding the history of life. Bayesian analysis using Markov chain Monte Carlo (MCMC) is a widely used approach for inferring phylogenetic trees, but it suffers from slow convergence in higher dimensions and is slow to converge. READ MORE
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2. GPU-Based Path Optimization Algorithm in High-Resolution Cost Map with Kinodynamic Constraints : Using Non-Reversible Parallel Tempering
University essay from Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)Abstract : This thesis introduces a GPU-accelerated algorithm for path planning under kinodynamic constraints, focusing on navigation of flying vehicles within a high-resolution cost map. The algorithm operates by creating dynamically feasible initial paths, and a non-reversible parallel tempering Markov chain Monte Carlo scheme to optimize the paths while adhering to the nonholonomic kinodynamical constraints. READ MORE
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3. Predictive Modeling and Statistical Inference for CTA returns : A Hidden Markov Approach with Sparse Logistic Regression
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : This thesis focuses on predicting trends in Commodity Trading Advisors (CTAs), also known as trend-following hedge funds. The paper applies a Hidden Markov Model (HMM) for classifying trends. Additionally, by incorporating additional features, a regularized logistic regression model is used to enhance prediction capability. READ MORE
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4. 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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5. 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