Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 56 for “"monte carlo algorithm"”.
-
Private Random Variate Sampling for Secure and Federated Polygenic Risk Scores
… a secure and federated implementation of a Monte Carlo algorithm for PRS, enabling collaborations that respect data regulations. To implement a Monte Carlo algorithm in a privacy-preserving context, our work exhibits techniques for sampling random variates with cryptographically private …
-
Novel Quantum Monte Carlo Approaches for Quantum Liquids
Quantum Monte Carlo methods are a powerful suite of techniques for solving the quantum many-body problem. By using random numbers to stochastically sample quantum properties, QMC methods are capable of studying low-temperature quantum systems well beyond the reach of conventional deterministic …
-
Aspects of population Markov chain Monte Carlo and reversible jump Markov chain Monte Carlo
… ideas of two new population Markov chain Monte Carlo algorithms and an automatic proposal mechanism for the Reversible jump Markov chain Monte Carlo algorithm.
-
Impact ionization and high-field transport in semiconductors
… transport are computed by a full-band Monte Carlo algorithm for Si and several III-V materials. Furthermore, a new interpretation of hot carrier luminescence spectra is given which can explain important features of hot electron distribution functions in MOSFETs.
-
Dynamic Critical Phenomena of the Superconducting Transition
One of the reasons why the Monte Carlo results do not accurately reproduce the dynamic exponent of the system is that a key assumption is found not to hold true. Equating Monte Carlo time to real time is believed to reproduce relaxational dynamics, but this is found not to be the case for the …
-
From Hypernuclei to Hypermatter: a Quantum Monte Carlo Study of Strangeness in Nuclear Structure and Nuclear Astrophysics
… work presents the recent developments in Quantum Monte Carlo calculations for nuclear systems including strange degrees of freedom. The Auxiliary Field Diffusion Monte Carlo algorithm has been extended to the strange sector by the inclusion of the lightest among the hyperons, the Λ particle. …
-
Monte Carlo methods for parallel processing of diffusion equations
A Monte Carlo algorithm for solving simple linear systems using a random walk is demonstrated and analyzed. The described algorithm solves for each element in the solution vector independently. Furthermore, it is demonstrated that this algorithm is easily parallelized. To reduce error, each …
-
Optimizing Pollution Routing Problem
… project is to implement different optimization algorithms to solve this problem. A basic model is created using the Vehicle Routing Problem (VRP) which is further extended to the Pollution Routing Problem (PRP). The basic model is updated using a Monte Carlo Algorithm (MCA). The data set …
-
Some Model-Based and Distance-Based Clustering Methods for Characterization of Regional Ecological Stressor-Response Patterns and Regional Environmental Quality Trends
… the posterior distribution using a Markov chain Monte Carlo algorithm. Two general approaches to the label-switching problem are considered, each leading to procedures that we apply in data analyses. Two applications are presented. We explore some relationships among priors with a Dirichlet …
-
Tree-based Methods for Learning Probability Distributions
… is efficiently explored with a new sequential Monte Carlo algorithm. The new ensemble method discussed in Chapter 3 is proposed under a new addition rule defined for probability distributions. The new rule based on cumulative distribution functions and their generalizations enables us to …
-
Multilevel modelling of determinants of contraceptive method choice among women in South Africa
… by the use of the state of the art Hamiltonian Monte Carlo algorithm (HMC), as implemented in the RStan package in the R statistical software. The Bayesian nal model was selected based on Watanabe{Akaike information criterion (WAIC), which has been shown to outperform conventional …
-
An Adaptive Bayesian Approach to Bernoulli-Response Clinical Trials
… asymmetric jumping rules inside the Markov chain Monte Carlo algorithm. An order restricted Metropolis-Hastings algorithm is implemented to account for these limitations. Modeling clinical trials in a Bayesian framework allows the experiment to be adaptive. In this adaptive design batches of …
-
A Bayesian Framework for the Unified Model for Assessing Cognitive Abilities: Blending Theory With Practicality
… the discussion in Chapter 2 of the Markov Chain Monte Carlo algorithm used to estimate the RUM model parameters. Then, the estimation accuracy of the algorithm and the robustness of the estimation is assessed in Chapter 3 with a series of simulation studies. Chapter 4 presents a cognitive …
-
Recurrent-Event Models for Change-Points Detection
… is a Dirichlet distribution and a Markov chain Monte Carlo algorithm is developed to sample from the posterior distributions. DIC is used to determine the best number of clusters. Based on the simulation study, the model gives fine results under different scenarios. For the Naturalist Teenage …
-
Decision support tools for urban air quality management
… dataset on gas-phase precursors. A Markov Chain Monte Carlo algorithm was combined with the equilibrium inorganic aerosol model ISORROPIA to produce a powerful tool to analyze aerosol data and predict gas phase concentrations where these are unavailable. The method directly incorporates …
-
Atomistic simulations of elastic-plastic deformation of amorphous polymers
… network was numerically constructed using a Monte Carlo algorithm and then subjected to uniaxial deformation over a wide range of strain rates and temperatures using Molecular Dynamics. The model exhibits many experimentally observed characteristics such as an initial elastic response …
-
Applications of Markov Chain Monte Carlo methods to continuous gravitational wave data analysis
A new algorithm for the analysis of gravitational wave data from rapidly rotating neutron stars has been developed. The work is based on the Markov Chain Monte Carlo algorithm and features enhancements specifically targeted to this problem. The algorithm is tested on both synthetic data and …
-
Contributions to modeling parasite dynamics and dimension reduction
… We estimate the model by a Markov chain Monte Carlo algorithm with data augmentation. We present simulation studies and an application to an infection study about the parasite Giardia lamblia among children in Kenya. The second project focuses on supervised dimension reduction. The goal …
-
Bayesian Active Structure Learning for Gaussian Process Probabilistic Programs
… active learning setting. We present a sequential Monte Carlo algorithm for Bayesian active learning for GPs with a novel objective function, Kernel Information Gain (IG-K), to reduce uncertainty over model structure and parameters. As a baseline for comparison, we also formulate a second objective …
-
A Fast Clustering Algorithm Merging The Expectation Maximization Algorithm and Markov Chain Monte Carlo
… methods, of which the Expectation-Maximization algorithm (EM) is the most common. In this work we present an algorithm merging Markov Chain Monte Carlo methods with the EM algorithm to find qualitatively better solutions for the clustering problem. We present brief introductions to two popular …
Page 1 of 3