Sökning: "bayesian hierarchical model"

Visar resultat 1 - 5 av 14 uppsatser innehållade orden bayesian hierarchical model.

1. 1. BAYESIAN HIERARCHICAL LINEAR MODELS FOR DIFFERENTIAL PROTEIN EXPRESSION ANALYSIS

   Master-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Siri Voghera; [2023]
   Nyckelord :Bayesian hierarchical modeling; differential protein expression analysis; proteomics;

   Sammanfattning : It is evident that the study of proteins is crucial for a deeper understanding of how drug treatments affect the body. However, differential protein expression analysis, which can be described as the method of finding which proteins are affected by a treatment, faces some major challenges. LÄS MER

3. 2. Towards Deep Learning Accelerated Sparse Bayesian Frequency Estimation

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Mika Persson; [2022]
   Nyckelord :Bayesian Statistics; Deep Learning; Frequency Estimation; Generative Adversarial Networks; Artificial Neural Networks; Statistical Modelling; Mathematics and Statistics;

   Sammanfattning : 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. LÄS MER

4. 3. Inverse Uncertainty Quantification for Sounding Rocket Dispersion

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Tove Ågren; [2022]
   Nyckelord :Uncertainty quantification; Bayesian inference; Rocket dispersion; Neural networks; Markov Chain Monte Carlo.; Osäkerhetskvantifiering; Bayesiansk inferens; Raketspridning; Neurala nätverk; Markovkedje-Monte Carlo;

   Sammanfattning : Sounding rocket impact points are subject to dispersion due to uncertainties in simulation model parameters and perturbations of the rocket trajectory during flight. Estimating the area of dispersion assumes that associated model uncertainties and magnitude of perturbations have already been inferred. LÄS MER

5. 4. Spatial Statistical Modelling of Insurance Claim Frequency

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Daniel Faller; [2022]
   Nyckelord :Insurance risk; claim frequency; Markov chain Monte Carlo MCMC ; Riemann manifold Metropolis adjusted Langevin algorithm MMALA ; spatial statistics; Gaussian Markov random field GMRF ; preconditioned Crank Nicolson Langevin algorithm pCNL ; Gibbs sampling; Bayesian hierarchical modelling; high dimensional; shrinkage prior; horseshoe prior; regularisation.; Mathematics and Statistics;

   Sammanfattning : 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. LÄS MER

7. 5. Non-Intrusive Load Monitoring to Assess Retrofitting Work

   Master-uppsats, KTH/Matematisk statistik

   Författare :Julien Zucchet; [2022]
   Nyckelord :NILM; retrofitting work assessment; hierarchical Bayesian mixture model; NILM; hierarkisk Bayesiansk blandningsmodell; utvärdering av renoveringsarbetens effektivitet;

   Sammanfattning : Non-intrusive load monitoring (NILM) refers to a set of statistical methods for inferring information about a household from its electricity load curve, without adding any additional sensor. The aim of this master thesis is to adapt NILM techniques for the assessment of the efficiency of retrofitting work to provide a first version of a retrofitting assessment tool. LÄS MER