Essays about: "Gibbs sampling"
Showing result 1 - 5 of 14 essays containing the words Gibbs sampling.
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1. Reconstruction of Fire Spread with a Markov Random Field Mixture Model
University essay from Lunds universitet/Matematisk statistikAbstract : This thesis revolves around reconstructing fire sizes for historical fires in Jämtgaveln, Sweden based on data of fire scars in trees. We propose a Hidden Markov Model (HMM), where the domain is divided into quadratic grid cells of 250 $\times$ 250 m and with these grid cells we associate a binary Markov random field taking values 0 or 1 corresponding to no fire and fire respectively. READ MORE
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2. 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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3. Towards Deep Learning Accelerated Sparse Bayesian Frequency Estimation
University essay from Lunds universitet/Matematisk statistikAbstract : The Discrete Fourier Transform is the simplest way to obtain the spectrum of a discrete complex signal. This thesis concerns the case when the signal is known to contain a small (unknown) number of frequencies, not limited to the discrete Fourier frequencies, embedded in complex Gaussian noise. READ MORE
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4. Spatial Statistical Modelling of Insurance Claim Frequency
University essay from Lunds universitet/Matematisk statistikAbstract : In this thesis a fully Bayesian hierarchical model that estimates the number of aggregated insurance claims per year for non-life insurances is constructed using Markov chain Monte Carlo based inference with Riemannian Langevin diffusion. Some versions of the model incorporate a spatial effect, viewed as the relative spatial insurance risk that originates from a policyholder's geographical location and where the relative spatial insurance risk is modelled as a continuous spatial field. 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
