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 “"Sequential Monte Carlo"”.
-
Haplotype Inference through Sequential Monte Carlo
… of information. In this thesis we present a Sequential Monte Carlo framework (TDS) and tailor it to address instances of haplotype inference and frequency estimation problems. Specifically, we first adjust our framework to perform haplotype inference in trio families resulting in a …
-
Composite system reliability evaluation using sequential Monte Carlo simulation
Monte Carlo simulation methods can be effectively used to assess the adequacy of composite power system networks. The sequential simulation approach is the most fundamental technique available and can be used to provide a wide range of indices. It can also be used to provide estimates which can …
-
Finite Sample Bounds and Path Selection for Sequential Monte Carlo
<p>Sequential Monte Carlo (SMC) samplers have received attention as an alternative to Markov chain Monte Carlo for Bayesian inference problems due to their strong empirical performance on difficult multimodal problems, natural synergy with parallel computing environments, and accuracy when …
-
An information-theoretic analysis of resampling in Sequential Monte Carlo
Sequential Monte Carlo (SMC) methods form a popular class of Bayesian inference algorithms. While originally applied primarily to state-space models, SMC is increasingly being used as a general-purpose Bayesian inference tool. Traditional analyses of SMC algorithms focus on their usage for …
-
Maximum likelihood parameter estimation in time series models using sequential Monte Carlo
… When a time series model is to be fitted to some sequentially observed data, it is essential to decide on the value of the parameter that describes the data best, a procedure generally called parameter estimation. This thesis comprises novel contributions to the methodology on parameter estimation …
-
Sequential Monte Carlo Methods with Applications to Positioning and Tracking in Wireless Networks
… state-space models together with applications of Sequential Monte Carlo (also called particle filtering) methods to the positioning in wireless networks. The aim of the first paper is to study the performance of particle filtering techniques in mobile positioning using signal strength …
-
Formally justified and modular Bayesian inference for probabilistic programs
… to several variants of Markov chain Monte Carlo and Sequential Monte Carlo methods and formally prove a notion of correctness for these algorithms in the context of probabilistic programming. We also show that the semantic construction can be directly mapped to an implementation using …
-
Using probability density functions to analyze the effect of external threats on the reliability of a South African power grid
… evaluation technique that is based on the sequential Monte Carlo simulation. The technique applies a time-dependent probabilistic modelling approach to network reliability parameters. The approach uses the Beta probability density functions to model stochastic network parameters while …
-
Modelling probabilities of corporate default
… from our pseudo-likelihood estimation by using Sequential Monte Carlo techniques and pseudo-Bayesian inference. With these techniques, we significantly improve upon our original parameter estimates. The increase in accuracy is most significant when using few samples which mimics real world data …
-
Localization and separation of concurrent talkers based on principles of auditory scene analysis and multi-dimensional statistical methods
… it. To implement these, Bayesian estimation, sequential Monte Carlo methods, and statistical evaluation of speech databases are used. Three on-line algorithms are developed and tested, which run partly in real-time. They allow for a robust, efficient and exact sound localization even at low …
-
Calibrating high frequency trading data to agent based models using approximate Bayesian computation
We consider Sequential Monte Carlo Approximate Bayesian Computation (SMC ABC) as a method of calibration for the use of agent based models in market micro-structure. To date, there are no successful calibrations of agent based models to high frequency trading data. Here we test whether a more …
-
Latent variable models for understanding user behavior in software applications
… is valuable. Finally, by combining sequential Monte Carlo and variational inference, I propose a new inference scheme which has better convergence properties than other reasonable baselines.
-
PRACTICAL INVESTIGATIONS ON BAYESIAN INVERSE PROBLEMS
… are two-fold. We present a novel adaptive sequential Monte Carlo method and its application to the groundwater-flow problem. Here, we observe significant time-savings compared to previous SMC approaches. We also observe, however, that this method is still too slow to be used in practice. …
-
Tree-based Methods for Learning Probability Distributions
… tree space 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 …
-
Particle Filter Based Mosaicking for Forest Fire Tracking
… Uncertainty Mosaic (GUM), in which we utilize a Sequential Monte Carlo method (a particle filter) to resolve that uncertainty and construct a georeferenced mosaic that simultaneously shows size, shape, geolocation, and uncertainty information about the fire.
-
GPU accelerated risk quantification
… risks and has been implemented as a sequential Monte Carlo simulation in the RiskLens and FAIR-U applications. Monte Carlo simulations employ random sampling techniques to model certain systems through the course of many iterations. Due to their sequential nature, FAIR simulations in …
-
Optimal approximations of coupling in multidisciplinary models
… of the discipline couplings. An adaptive sequential Monte Carlo sampling-based technique is used to efficiently search the combinatorial model space of different discipline couplings. Finally, an algorithm for optimal model selection is presented and combined with three tractable …
-
Integrated System Model Reliability Evaluation and Prediction for Electrical Power Systems: Graph Trace Analysis Based Solutions
… operation conditions are considered. Sequential Monte Carlo simulation is used to evaluate the reliability changes for different system configurations, including distributed generation and transmission lines. Historical weather records and loading are used to update the component …
-
Topics in Genomic Signal Processing
… description of the problem is used and a sequential Monte Carlo method is applied for the inference. Finally, the phasing of haplotypes for diploid organisms is introduced, where a novel mathematical model is proposed. The haplotypes that are used to reconstruct the observed genotypes of a …
Page 1 of 3