Searched for: subject%3A%22Bayesian%22
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Vinatselas, Theodoros (author)
This thesis discusses the characterization of the undrained shear strength, S_u from the net cone resistance, q_net of clay in Dutch sites using Hierarchical Bayesian Modelling (HBM). The performance of the HBM is compared with the current practice methods of the site characterization which propose either the use of only site–specific...
master thesis 2023
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Ahmad, Amna (author)
The Bayesian approach is a very important approach for tackling problems in statistics. It involves choosing a distribution that reflects the prior knowledge and  thus takes all knowledge into account in contrast to the frequentist approach. It also assumes that the parameters (the regression coefficients) follow a distribution called the...
bachelor thesis 2023
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Bertazzi, A. (author)
This thesis studies methods to improve the applicability and the performance of Markov Chain Monte Carlo (MCMC) algorithms based on Piecewise Deterministic Markov processes (PDMPs). First, we discuss the key ideas that lay the foundations of the field of MCMC, spanning from the Metropolis-Hastings algorithm to PDMC methods, emphasising a common...
doctoral thesis 2023
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Schriemer, Sterre (author)
Frequentist statistics and Bayesian statistics are the two main approaches to statistical inference. The frequentist approach is commonly integrated into academic curricula, while the Bayesian approach is less frequently employed. However a comparison of the approaches, further investigating their shortcomings and advantages, might give a better...
bachelor thesis 2023
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Janssen, Britt (author)
Quantile regression is a useful method to analyse data such that the estimates are more robust to outliers and the conditional distributions are more reliable for asymmetric distributions with respect to the commonly used ordinary least squares regression. Besides this, the quantile regression analysis might also include extra information on the...
bachelor thesis 2023
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Lindsay, Maxwell (author)
Knowledge of nearshore bathymetry is crucial for every aspect of the blue economy. Currently, it is expensive to obtain nearshore bathymetry at regional scales, and therefore this data is not available for many coasts. The data scarcity occurs especially in the global south and big ocean states that are at the highest risk from climate change....
master thesis 2022
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Oostdam, Oskar Oostdam (author)
The VIX index, which is the expected volatility of the S&P 500 index in 30 days, is of interest to a lot of investors on the US financial market. Allowing the volatility of the financial market to be used as a trading tool gives rise to interesting investment opportunities, such as hedging and speculation. In this thesis we will be creating...
master thesis 2021
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Bonnet, Damiaan (author)
The goal of this thesis is to implement and experiment with a Bayesian way of estimating a (smooth) monotone regression function by applying it to climate data. The method we use is proposed by Neelon and Dunson. This method uses a piece-wise linear model for the unknown regression function and enforces the monotonicity constraint by the...
bachelor thesis 2021
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Schikhof, Phine (author)
Dit project vergelijkt drie verschillende kernels (Random Walk, Langevin en Barker) die gebruikt kunnen worden in het Metropolis-Hastings algoritme aan de hand van voorbeelden.
bachelor thesis 2021
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Koune, Jan (author)
Bayesian system identification, including parameter estimation and model selection, is widely used to infer partially known, unobservable parameters of the models of physical systems when measurement data is available. A common assumption in the Bayesian system identification...
master thesis 2021
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van der Bent, Isa (author)
Bij schaken wordt een rating system gebruikt om te bepalen hoe goed een schaker is. In deze bachelor thesis is onderzocht of er een rating system gemaakt kan worden voor zeilwedstrijden. Hierbij is gebruik gemaakt van Bayesiaanse statistiek en de theorie achter het rating systeem voor schakers. Het bedachte rating systeem is bedoeld voor drie...
bachelor thesis 2021
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Wiessner, Manfred (author), Angerer, Paul (author), van der Zwaag, S. (author), Gamsjäger, Ernst (author)
We describe the analysis of in-situ HT-XRD data of a dual phase stainless steel exposed to a complex thermal cycle of heating, holding and cooling. For the conditions used only low quality diffraction data could be collected. Peak positions, peak areas and peak broadening are modeled by the Rietveld method. The low signal-to noise ratio and...
journal article 2021
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van Driel, W.D. (author), Bikker, J.W. (author), Tijink, M. (author)
It is known that quantitative measures for the reliability of software systems can be derived from software reliability models. And, as such, support the product development process. Over the past four decades, research activities in this area have been performed. As a result, many software reliability models have been proposed. It was shown...
journal article 2021
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Göbbels, Joost (author)
In today’s complex, modern world, where more data and knowledge is available then ever before, consensus over approaches in statistics is far away. To understand what this means for forensic statistics, both the frequentist and Bayesian approach are considered in quantifying evidence. Classical frequentist approaches are elaborated according to...
bachelor thesis 2019
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Kaak, Davey (author)
During a digital fraud investigation the search for relevant information in mailboxes of custodians is like finding a needle in a haystack. This time consuming task can, on various levels, be improved and made more efficient. Technology Assisted Review (TAR) is already one of the available machine learning algorithms that helps speeding up the...
master thesis 2019
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Wang, Tianxiang (author)
The rapid development in statistics, information technology, and computational power have en- abled numerous innovative methods to emerge in Structural Health Monitoring (SHM) for structural damage detection, both in practical application and research. The intention of such methods is to use the data obtained from the monitoring system to...
master thesis 2018
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Zoutendijk, Joran (author)
This thesis is on the subject of modelling the probability of default in a low default portfolio. In these portfolios there is a high risk of underestimating the true probability of default. Two models are considered, a Gaussian one factor model and a Poisson model with Gamma mixture. Classical estimation methods as the maximum likelihood are...
master thesis 2018
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Bierkens, G.N.J.C. (author), Bouchard-Côté, Alexandre (author), Doucet, Arnaud (author), Duncan, Andrew B. (author), Fearnhead, Paul (author), Lienart, Thibaut (author), Roberts, Gareth (author), Vollmer, Sebastian J. (author)
Piecewise Deterministic Monte Carlo algorithms enable simulation from a posterior distribution, whilst only needing to access a sub-sample of data at each iteration. We show how they can be implemented in settings where the parameters live on a restricted domain.
journal article 2018
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Fearnhead, Paul (author), Bierkens, G.N.J.C. (author), Pollock, Murray (author), Roberts, Gareth O. (author)
Recently, there have been conceptually new developments in Monte Carlo methods through the introduction of new MCMC and sequential Monte Carlo (SMC) algorithms which are based on continuous-time, rather than discrete-time, Markov processes. This has led to some fundamentally new Monte Carlo algorithms which can be used to sample from, say, a...
journal article 2018
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Thijssen, B. (author), Dijkstra, Tjeerd M.H. (author), Heskes, Tom (author), Wessels, L.F.A. (author)
Background<br/>Computational models in biology are characterized by a large degree of uncertainty. This uncertainty can be analyzed with Bayesian statistics, however, the sampling algorithms that are frequently used for calculating Bayesian statistical estimates are computationally demanding, and each algorithm has unique advantages and...
journal article 2016
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