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Autor: Friedrich Götze, Mathisca C. M. de Gunst, Marta Fiocco, Peter J. Bickel

Publikováno v: Bickel, P, Fiocco, M, de Gunst, M & Götze, F 2021, ' Willem van Zwet’s research ', Annals of Statistics, vol. 49, no. 5, pp. 2439-2447 . https://doi.org/10.1214/21-AOS2060
Annals of Statistics, 49(5), 2439-2447. Institute of Mathematical Statistics

Willem van Zwet made deep and influential contributions to probability and statistics, which we review in this paper. Bickel and Götze collaborated with him on his major contributions to higher order asymptotics of nonlinear statistics and on resamp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff971f522b4c7e405509856f51a08690
https://hdl.handle.net/1871.1/ec08535b-0e57-4da0-bfe2-eca2d96b79c8

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Data integrative Bayesian inference for mixtures of regression models

Autor: Mathisca C. M. de Gunst, Mehran Aflakparast

Publikováno v: Aflakparast, M & de Gunst, M C M 2019, ' Data integrative Bayesian inference for mixtures of regression models ', Journal of the Royal Statistical Society: Series C (Applied Statistics), vol. 68, no. 4, pp. 941-962 . https://doi.org/10.1111/rssc.12346
Journal of the Royal Statistical Society: Series C (Applied Statistics), 68(4), 941-962. Wiley-Blackwell

Summary Modern data collection techniques, which often produce different types of relevant information, call for new statistical learning methods that are adapted to cope with data integration. In the paper Bayesian inference is considered for mixtur

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35b8eb978510a7fa7a256859a997491c
https://research.vu.nl/en/publications/667e93f8-9781-4a6f-9369-07a4f62ae65e

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Parameter estimation for multivariate population processes

Autor: Mathisca C. M. de Gunst, Sophie Hautphenne, Birgit Sollie, Michel Mandjes

Publikováno v: de Gunst, MCM, Hautphenne, S, Mandjes, M & Sollie, B 2020, ' Parameter estimation for multivariate population processes: a saddlepoint approach ', Stochastic Models, vol. 37, no. 1, pp. 168-196 . https://doi.org/10.1080/15326349.2020.1832895
Stochastic Models, 37(1), 168-196. Taylor and Francis Ltd.
Stochastic Models, 37(1):168-196. Taylor and Francis Ltd.

The setting considered in this paper concerns a discrete-time multivariate population process under Markov modulation. Our objective is to estimate the model parameters, based on periodic observations of the network population vector. These parameter

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https://doi.org/10.1080/15326349.2020.1832895

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Bayesian mixture regression analysis for regulation of Pluripotency in ES cells

Autor: Mathisca C. M. de Gunst, Mehran Aflakparast, Geert Geeven

Publikováno v: BMC Bioinformatics, 21:3, 1-13. BioMed Central
Aflakparast, M, Geeven, G & De Gunst, M C M 2020, ' Bayesian mixture regression analysis for regulation of Pluripotency in ES cells ', BMC Bioinformatics, vol. 21, 3, pp. 1-13 . https://doi.org/10.1186/s12859-019-3331-2
BMC Bioinformatics, 21(1). BioMed Central
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-13 (2020)
BMC Bioinformatics

Background Observed levels of gene expression strongly depend on both activity of DNA binding transcription factors (TFs) and chromatin state through different histone modifications (HMs). In order to recover the functional relationship between local

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https://research.vu.nl/en/publications/dd55fd2c-bef3-4912-9375-234baef5712d

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Analysis of Twitter data with the Bayesian fused graphical lasso

Autor: Wessel N. van Wieringen, Mehran Aflakparast, Mathisca C. M. de Gunst

Publikováno v: PLoS ONE, Vol 15, Iss 7, p e0235596 (2020)
Aflakparast, M, de Gunst, M & van Wieringen, W 2020, ' Analysis of Twitter data with the Bayesian fused graphical lasso ', PLoS ONE, vol. 15, no. 7 July, e0235596, pp. e0235596 . https://doi.org/10.1371/journal.pone.0235596
PLoS ONE, 15(7 July):e0235596. Public Library of Science
PLoS ONE, 15(7):e0235596, 1-28. Public Library of Science
Aflakparast, M, de Gunst, M & van Wieringen, W 2020, ' Analysis of Twitter data with the Bayesian fused graphical lasso ', PLoS ONE, vol. 15, no. 7, e0235596, pp. 1-28 . https://doi.org/10.1371/journal.pone.0235596
PLoS ONE

We propose a method to simplify textual Twitter data into understandable networks of terms that can signify important events and their possible changes over time. The method allows for common characteristics of the networks across time periods and ea

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https://doaj.org/article/580e4ce7e3444f60ad6ff455770f0223

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Gene network reconstruction using global-local shrinkage priors

Autor: Mark A. van de Wiel, Aad van der Vaart, Wessel N. van Wieringen, Mathisca C. M. de Gunst, Gwenaël G. R. Leday, Gino B. Kpogbezan

Publikováno v: Leday, G G R, De Gunst, M C M, Kpogbezan, G B, Van Der Vaart, A W, Van Wieringen, W N & Van De Wiel, M A 2017, ' Gene network reconstruction using global-local shrinkage priors ', Annals of Applied Statistics, vol. 11, no. 1, pp. 41-68 . https://doi.org/10.1214/16-AOAS990
Annals of Applied Statistics, 11(1), 41-68. Institute of Mathematical Statistics
Ann. Appl. Stat. 11, no. 1 (2017), 41-68
Annals of Applied Statistics, 11(1), 41-68
Leday, G G R, de Gunst, M C M, Kpogbezan, G B, van der Vaart, A W, van Wieringen, W N & van de Wiel, M A 2017, ' Gene network reconstruction using global-local shrinkage priors ', The Annals of Applied Statistics, vol. 11, no. 1, pp. 41-68 . https://doi.org/10.1214/16-AOAS990
The Annals of Applied Statistics, 11(1), 41-68. Institute of Mathematical Statistics
Annals of Applied Statistics

Reconstructing a gene network from high-throughput molecular data is often a challenging task, as the number of parameters to estimate easily is much larger than the sample size. A conventional remedy is to regularize or penalize the model likelihood

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https://research.vu.nl/en/publications/60cd2f5d-5649-4938-8933-ca628d90883f

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Reconstruction of molecular network evolution from cross-sectional omics data

Autor: Mathisca C. M. de Gunst, Wessel N. van Wieringen, Mehran Aflakparast

Publikováno v: Biometrical Journal, 60(2). Wiley-VCH Verlag
Biometrical Journal, 2017(3), 1-17. Wiley-VCH Verlag
Aflakparast, M, de Gunst, M C M & van Wieringen, W N 2017, ' Reconstruction of molecular network evolution from cross-sectional omics data ', Biometrical Journal, vol. 2017, no. 3, pp. 1-17 . https://doi.org/10.1002/bimj.201700102
Aflakparast, M, de Gunst, M & van Wieringen, WN 2018, ' Reconstruction of molecular network evolution from cross-sectional omics data ', Biometrical Journal, vol. 60, no. 2, pp. 547 . https://doi.org/10.1002/bimj.201700102

Cross-sectional studies may shed light on the evolution of a disease like cancerthrough the comparison of patient traits among disease stages. This problem is especially challenging when a gene–gene interaction network needs to be reconstructed fro

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https://research.vumc.nl/en/publications/5c104148-6893-40a2-bb98-b50405e317db

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A three domain covariance framework for EEG/MEG data

Autor: Jan C. de Munck, Beata Roś, Mathisca C. M. de Gunst, Fetsje Bijma

Publikováno v: Ros, B P, Bijma, F, de Gunst, M C M & de Munck, J C 2015, ' A three domain covariance framework for EEG/MEG data ', NeuroImage, vol. 119, pp. 305-315 . https://doi.org/10.1016/j.neuroimage.2015.06.020
NeuroImage, 119, 305-315. Academic Press Inc.

In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance m

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https://doi.org/10.1016/j.neuroimage.2015.06.020

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Existence and uniqueness of the maximum likelihood estimator for models with a Kronecker product covariance structure

Autor: Fetsje Bijma, Jan C. de Munck, Beata Roś, Mathisca C. M. de Gunst

Publikováno v: Ros, B P, Bijma, F, de Munck, J C & de Gunst, M C M 2016, ' Existence and uniqueness of the maximum likelihood estimator for models with a Kronecker product covariance structure ', Journal of Multivariate Analysis, vol. 143, doi.org/10.1016/j.jmva.2015.05.019, pp. 345-361 . https://doi.org/10.1016/j.jmva.2015.05.019
Journal of Multivariate Analysis, 143, 345-361. Academic Press Inc.
Journal of Multivariate Analysis, 143:doi.org/10.1016/j.jmva.2015.05.019, 345-361. Academic Press Inc.
Ros, B P, Bijma, F, de Munck, J C & de Gunst, M C M 2016, ' Existence and uniqueness of the maximum likelihood estimator for models with a Kronecker product covariance structure ', Journal of Multivariate Analysis, vol. 143, pp. 345-361 . https://doi.org/10.1016/j.jmva.2015.05.019

This paper deals with multivariate Gaussian models for which the covariance matrix is a Kronecker product of two matrices. We consider maximum likelihood estimation of the model parameters, in particular of the covariance matrix. There is no explicit

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https://research.vu.nl/en/publications/89f568a1-0f03-475c-a3c2-f192292b3f16

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Genetic study of the height and weight process during infancy

Autor: Aad van der Vaart, Paula van Dommelen, Dorret I. Boomsma, Mathisca C. M. de Gunst

Publikováno v: Twin Research, 7(6), 607-16. Australian Academic Press
Twin Research, 6, 7, 607-616
Dommelen, P, de Gunst, M C M, van der Vaart, A W & Boomsma, D I 2004, ' Genetic study of the height and weight process during infancy. ', Twin Research, vol. 7, no. 6, pp. 607-616 . https://doi.org/10.1375/1369052042663805
van Dommelen, P, de Gunst, M C M, van der Vaart, A W & Boomsma, D I 2004, ' Genetic study of the height and weight process during infancy ', Twin Research, vol. 7, no. 6, pp. 607-16 . https://doi.org/10.1375/1369052042663805
Twin Research, 7(6), 607-616. Australian Academic Press

Longitudinal height and weight data from 4649 Dutch twin pairs between birth and 2.5 years of age were analyzed. The data were first summarized into parameters of a polynomial of degree 4 by a mixed-effects procedure. Next, the variation and covariat

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http://www.tweelingenregister.org/nederlands/verslaggeving/NTR_publicaties_2004/Van_Dommelen_growth_TR2004.pdf

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