Searched for: author%3A%22van+der+Meulen%2C+F.H.%22
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Gomaz, L. (author), van Trigt, B. (author), van der Meulen, F.H. (author), Veeger, H.E.J. (author)
The baseball pitch is a repetitive, full-body throwing motion that exposes the elbow to significant loads, leading to a high incidence of elbow injuries. Elbow injuries in pitching are often attributed to high external valgus torques as these are generally considered to be a good proxy for the load on the Ulnar Collateral Ligament. The aim of...
journal article 2024
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Bierkens, G.N.J.C. (author), Grazzi, S. (author), van der Meulen, F.H. (author), Schauer, M.R. (author)
We construct a new class of efficient Monte Carlo methods based on continuous-time piecewise deterministic Markov processes (PDMPs) suitable for inference in high dimensional sparse models, i.e. models for which there is prior knowledge that many coordinates are likely to be exactly 0. This is achieved with the fairly simple idea of endowing...
journal article 2023
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Corstanje, M.A. (author), van der Meulen, F.H. (author), Schauer, M.R. (author)
A continuous-time Markov process X can be conditioned to be in a given state at a fixed time T>0 using Doob's h-transform. This transform requires the typically intractable transition density of X. The effect of the h-transform can be described as introducing a guiding force on the process. Replacing this force with an approximation...
journal article 2022
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Mészáros, L. (author), van der Meulen, F.H. (author), Jongbloed, G. (author), El Serafy, G.Y.H. (author)
Coastal climate impact studies make increasing use of multi-source and multi-dimensional atmospheric and environmental datasets to investigate relationships between climate signals and the ecological response. The large quantity of numerically simulated data may, however, include redundancy, multi-colinearity and excess information not relevant...
journal article 2022
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Hageman, R.B. (author), van der Meulen, F.H. (author), Rouhan, A. (author), Kaminski, M.L. (author)
In order to obtain valuable information from an Hull Structure Monitoring system, a large data set and consistent analysis of that data is required. The monitoring requires significant efforts over multiple years and as a result, uncertainties obtained from in-service measurements are rarely published. Instead, researchers have to rely on...
journal article 2022
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Arnaudon, Alexis (author), van der Meulen, F.H. (author), Schauer, Moritz (author), Sommer, Stefan (author)
Stochastically evolving geometric systems are studied in shape analysis and computational anatomy for modeling random evolutions of human organ shapes. The notion of geodesic paths between shapes is central to shape analysis and has a natural generalization as diffusion bridges in a stochastic setting. Simulation of such bridges is key to...
journal article 2022
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Jongbloed, G. (author), van der Meulen, F.H. (author), Pang, L. (author)
We consider the current status continuous mark model where, if an event takes place before an inspection time T a “continuous mark” variable is observed as well. A Bayesian nonparametric method is introduced for estimating the distribution function of the joint distribution of the event time (X) and mark variable (Y). We consider two...
journal article 2021
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Gomaz, L. (author), Veeger, H.E.J. (author), van der Graaff, E. (author), van Trigt, B. (author), van der Meulen, F.H. (author)
Ball velocity is considered an important performance measure in baseball pitching. Proper pitching mechanics play an important role in both maximising ball velocity and injury-free participation of baseball pitchers. However, an individual pitcher’s characteristics display individuality and may contribute to velocity imparted to the ball. The...
journal article 2021
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Mészáros, L. (author), van der Meulen, F.H. (author), Jongbloed, G. (author), El Serafy, G.Y.H. (author)
Spring phytoplankton blooms in the southern North Sea substantially contribute to annual primary production and largely influence food web dynamics. Studying long-term changes in spring bloom dynamics is therefore crucial for understanding future climate responses and predicting implications on the marine ecosystem. This paper aims to study...
journal article 2021
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Mider, Marcin (author), Schauer, Moritz (author), van der Meulen, F.H. (author)
Suppose X is a multivariate diffusion process that is observed discretely in time. At each observation time, a transformation of the state of the process is observed with noise. The smoothing problem consists of recovering the path of the process, consistent with the observations. We derive a novel Markov Chain Monte Carlo algorithm to sample...
journal article 2021
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Bierkens, G.N.J.C. (author), Grazzi, S. (author), van der Meulen, F.H. (author), Schauer, M.R. (author)
We introduce the use of the Zig-Zag sampler to the problem of sampling conditional diffusion processes (diffusion bridges). The Zig-Zag sampler is a rejection-free sampling scheme based on a non-reversible continuous piecewise deterministic Markov process. Similar to the Lévy–Ciesielski construction of a Brownian motion, we expand the...
journal article 2021
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Mészáros, L. (author), van der Meulen, F.H. (author), Jongbloed, G. (author), El Serafy, G.Y.H. (author)
Available climate change projections, which can be used for quantifying future changes in marine and coastal ecosystems, usually consist of a few scenarios. Studies addressing ecological impacts of climate change often make use of a low- (RCP2.6), moderate- (RCP4.5) or high climate scenario (RCP8.5), without taking into account further...
journal article 2020
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Bierkens, G.N.J.C. (author), van der Meulen, F.H. (author), Schauer, M.R. (author)
Suppose X is a multidimensional diffusion process. Assume that at time zero the state of X is fully observed, but at time 0$ ]]> only linear combinations of its components are observed. That is, one only observes the vector for a given matrix L. In this paper we show how samples from the conditioned process can be generated. The main...
journal article 2020
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Gugushvili, Shota (author), Mariucci, Ester (author), van der Meulen, F.H. (author)
Suppose that a compound Poisson process is observed discretely in time and assume that its jump distribution is supported on the set of natural numbers. In this paper we propose a nonparametric Bayesian approach to estimate the intensity of the underlying Poisson process and the distribution of the jumps. We provide a Markov chain Monte Carlo...
journal article 2019
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Mészáros, L. (author), van der Meulen, F.H. (author), Jongbloed, G. (author), El Serafy, G.Y.H. (author)
Traditionally, quantifying climate change induced uncertainty in ecological indicators requires stochastic simulation with a chain of physically-based models describing various processes such as hydrodynamics, waves, sediment transport and ecology. Such Monte Carlo based simulation on the entire model chain, especially with large sample size, is...
abstract 2018
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Schauer, M.R. (author), van der Meulen, F.H. (author), Van Zanten, Harry (author)
A Monte Carlo method for simulating a multi-dimensional diffusion process conditioned on hitting a fixed point at a fixed future time is developed. Proposals for such diffusion bridges are obtained by superimposing an additional guiding term to the drift of the process under consideration. The guiding term is derived via approximation of the...
journal article 2017
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van der Meulen, F.H. (author), Schauer, M.R. (author), van Waaij, Jan (author)
We consider the problem of nonparametric estimation of the drift of a continuously observed one-dimensional diffusion with periodic drift. Motivated by computational considerations, van der Meulen et al. (Comput Stat Data Anal 71:615–632, 2014) defined a prior on the drift as a randomly truncated and randomly scaled Faber–Schauder series...
journal article 2017
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van der Meulen, F.H. (author), Schauer, M.R. (author)
Estimation of parameters of a diffusion based on discrete time observations poses a difficult problem due to the lack of a closed form expression for the likelihood. From a Bayesian computational perspective it can be casted as a missing data problem where the diffusion bridges in between discrete-time observations are missing. The...
journal article 2017
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van der Meulen, F.H. (author), Schauer, M.R. (author)
We present a general framework for Bayesian estimation of incompletely observed multivariate diffusion processes. Observations are assumed to be discrete in time, noisy and incomplete. We assume the drift and diffusion coefficient depend on an unknown parameter. A data-augmentation algorithm for drawing from the posterior distribution is...
journal article 2017
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Gugushvili, Shota (author), van der Meulen, F.H. (author), Spreij, Peter (author)
Given a sample from a discretely observed compound Poisson process, we consider non-parametric estimation of the density f0 of its jump sizes, as well as of its intensity λ0. We take a Bayesian approach to the problem and specify the prior on f0 as the Dirichlet location mixture of normal densities. An independent prior for λ0 is assumed to be...
journal article 2016
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