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المساهمون: Mathematics, Amsterdam Neuroscience - Systems & Network Neuroscience, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Complex Trait Genetics
المصدر: 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 Statisticsمصطلحات موضوعية: Statistics and Probability, Contact process, Resampling, Stochastic modelling, Asymptotic approximation, Population development, Statistical inference, Van Zwet, Probability and statistics, Statistics, Probability and Uncertainty, Mathematical economics, Mathematics
وصف الملف: application/pdf
URL الوصول: 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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المؤلفون: Mathisca C. M. de Gunst, Mehran Aflakparast
المساهمون: Mathematics, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Systems & Network Neuroscience
المصدر: 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-Blackwellمصطلحات موضوعية: Statistics and Probability, Clustering high-dimensional data, Data Integration, Data collection, Computer science, Bayesian probability, Feature selection, Regression analysis, Latent variable, Bayesian inference, computer.software_genre, Bayesian lasso, ComputingMethodologies_PATTERNRECOGNITION, Mixture regression, Markov chain Monte Carlo (MCMC), Data mining, Statistics, Probability and Uncertainty, computer, Data integration
وصف الملف: application/pdf
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المساهمون: Mathematics, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Complex Trait Genetics, Stochastics (KDV, FNWI)
المصدر: 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.مصطلحات موضوعية: Statistics and Probability, Background process, education.field_of_study, Multivariate statistics, Estimation theory, Applied Mathematics, Population, Markov process, Population process, Unobservable, symbols.namesake, Modeling and Simulation, symbols, Applied mathematics, Statistics::Methodology, Routing (electronic design automation), education, Mathematics
وصف الملف: application/pdf
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المؤلفون: Mathisca C. M. de Gunst, Mehran Aflakparast, Geert Geeven
المساهمون: Mathematics, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Systems & Network Neuroscience
المصدر: 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 Bioinformaticsمصطلحات موضوعية: Pluripotent Stem Cells, Pluripotency, Chromatin Immunoprecipitation, Bayesian analysis, Context (language use), Computational biology, lcsh:Computer applications to medicine. Medical informatics, 01 natural sciences, Biochemistry, Mice, 010104 statistics & probability, 03 medical and health sciences, Structural Biology, Mixture regression, Gene expression, Transcriptional regulation, Animals, 0101 mathematics, lcsh:QH301-705.5, Molecular Biology, Transcription factor, Gene, Embryonic Stem Cells, 030304 developmental biology, 0303 health sciences, Genome, biology, Methodology Article, Applied Mathematics, Bayes Theorem, Transcription regulation, Chromatin, Computer Science Applications, Histone, Gene Expression Regulation, lcsh:Biology (General), biology.protein, Regression Analysis, lcsh:R858-859.7, Data integration, DNA microarray, Transcription Factors
وصف الملف: image/pdf; text/plain
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المساهمون: Amsterdam Neuroscience - Complex Trait Genetics, Epidemiology and Data Science, Mathematics, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Cellular & Molecular Mechanisms
المصدر: 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 ONEمصطلحات موضوعية: 0301 basic medicine, Computer science, Gaussian, Statistics as Topic, Social Sciences, Elections, computer.software_genre, 01 natural sciences, 010104 statistics & probability, Sociology, Lasso (statistics), Graphical model, Materials, computer.programming_language, Multidisciplinary, Covariance, Applied Mathematics, Simulation and Modeling, Social Communication, Social Networks, Physical Sciences, symbols, Medicine, Data mining, Network Analysis, Algorithms, Research Article, Scheme (programming language), Computer and Information Sciences, Political Science, Science, Twitter, Materials Science, Bayesian probability, Research and Analysis Methods, 03 medical and health sciences, symbols.namesake, Computer Graphics, SDG 7 - Affordable and Clean Energy, 0101 mathematics, Models, Statistical, Bayes Theorem, Random Variables, Probability Theory, Communications, 030104 developmental biology, Mixtures, Predictive power, Social Media, computer, Mathematics
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المؤلفون: 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
المساهمون: Leday, Gwenael [0000-0002-3753-4060], Apollo - University of Cambridge Repository, Epidemiology and Data Science, Other Research, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Mathematics, Amsterdam Neuroscience - Complex Trait Genetics
المصدر: 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 Statisticsمصطلحات موضوعية: 0301 basic medicine, Statistics and Probability, FOS: Computer and information sciences, Computer science, Bayesian inference, Inference, Machine learning, computer.software_genre, 01 natural sciences, Conjugate prior, Article, Methodology (stat.ME), 010104 statistics & probability, 03 medical and health sciences, Bayes' theorem, Prior probability, 0101 mathematics, Statistics - Methodology, Network model, Hyperparameter, business.industry, undirected gene network, Thresholding, 030104 developmental biology, shrinkage, ComputingMethodologies_PATTERNRECOGNITION, Modeling and Simulation, variational approximation, Artificial intelligence, Statistics, Probability and Uncertainty, business, computer, Algorithm, empirical Bayes
وصف الملف: application/pdf
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd2d76120354660542fe3a0801c8c48b
https://research.vu.nl/en/publications/60cd2f5d-5649-4938-8933-ca628d90883f -
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المساهمون: Epidemiology and Data Science, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, CCA - Cancer biology and immunology, NCA - Brain mechanisms in health and disease, Other Research, Mathematics, Amsterdam Neuroscience - Complex Trait Genetics
المصدر: 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.201700102مصطلحات موضوعية: Statistics and Probability, Computer science, Gaussian, Normal Distribution, 01 natural sciences, Omics data, 010104 statistics & probability, 03 medical and health sciences, symbols.namesake, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Interaction network, Expectation–maximization algorithm, Humans, Gene Regulatory Networks, Graphical model, 0101 mathematics, Models, Statistical, Computational Biology, General Medicine, Ridge (differential geometry), Molecular network, Cross-Sectional Studies, 030220 oncology & carcinogenesis, Homogeneous group, symbols, Statistics, Probability and Uncertainty, Algorithm
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المؤلفون: Jan C. de Munck, Beata Roś, Mathisca C. M. de Gunst, Fetsje Bijma
المساهمون: Physics and medical technology, NCA - Brain imaging technology, Mathematics, Neuroscience Campus Amsterdam - Brain Imaging Technology
المصدر: 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.مصطلحات موضوعية: Adult, Male, Covariance function, Iterative method, Cognitive Neuroscience, Physics::Medical Physics, Electroencephalography, Machine learning, computer.software_genre, Young Adult, symbols.namesake, medicine, Humans, Computer Simulation, Mathematics, Kronecker product, Brain Mapping, Likelihood Functions, medicine.diagnostic_test, Quantitative Biology::Neurons and Cognition, business.industry, Covariance matrix, Brain, Magnetoencephalography, Reproducibility of Results, Estimator, Signal Processing, Computer-Assisted, Pattern recognition, Covariance, Brain Waves, Magnetic Resonance Imaging, Noise, Neurology, symbols, Female, Artificial intelligence, business, computer, Algorithms
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المؤلفون: Fetsje Bijma, Jan C. de Munck, Beata Roś, Mathisca C. M. de Gunst
المساهمون: Physics and medical technology, Mathematics, Amsterdam Neuroscience - Brain Imaging
المصدر: 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.2015.05.019مصطلحات موضوعية: Statistics and Probability, Covariance function, Mathematics - Statistics Theory, Statistics Theory (math.ST), 02 engineering and technology, 01 natural sciences, Combinatorics, 010104 statistics & probability, symbols.namesake, Estimation of covariance matrices, Scatter matrix, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Applied mathematics, Rational quadratic covariance function, Statistics::Methodology, 0101 mathematics, Mathematics, Kronecker product, Numerical Analysis, 020206 networking & telecommunications, Covariance, Matrix addition, symbols, Law of total covariance, 62H12, Statistics, Probability and Uncertainty
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المساهمون: Stochastics, Biological Psychology, Mathematics
المصدر: 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 Pressمصطلحات موضوعية: Netherlands Twin Register (NTR), data analysis, Twins, biometry, genetic analysis, heritability, newborn, environmental factor, Models, genetic variability, Twins, Dizygotic, Longitudinal Studies, Genetics (clinical), Netherlands, Body Height/genetics, Age Factors, Obstetrics and Gynecology, Gestational age, Growth curve (biology), Explained variation, Jerk, female, growth rate, Twins/genetics, Algorithms, Monozygotic/genetics, Adult, Adolescent, heredity, Dizygotic twin, sex difference, Twins, Monozygotic/genetics, Gestational Age, Biology, Twins, Dizygotic/genetics, monozygotic twins, male, Genetic, Body Weight/genetics, Genetic model, Humans, dizygotic twins, Genetic variability, infancy, Models, Genetic, Body Weight, Infant, Newborn, Dizygotic/genetics, Infant, Twins, Monozygotic, Heritability, Newborn, major clinical study, Body Height, Pediatrics, Perinatology and Child Health, Demography, growth curve
وصف الملف: application/pdf
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7e30b9a8fc9bebfb41bc4fdf2588266
http://www.tweelingenregister.org/nederlands/verslaggeving/NTR_publicaties_2004/Van_Dommelen_growth_TR2004.pdf