User profiles for M. Hinne
Max HinneAssistant professor, Radboud University Nijmegen Verified email at donders.ru.nl Cited by 1971 |
[HTML][HTML] The JASP guidelines for conducting and reporting a Bayesian analysis
Despite the increasing popularity of Bayesian inference in empirical research, few practical
guidelines provide detailed recommendations for how to apply Bayesian procedures and …
guidelines provide detailed recommendations for how to apply Bayesian procedures and …
[HTML][HTML] A tutorial on conducting and interpreting a Bayesian ANOVA in JASP
… under M 1 than under M 0 (ie, support for M 1 versus M 0 ); … occur under M 0 than under M 1
(ie, support for M 0 versus M 1 )… |M 1 ), divided by p(D|M 0 ), or as its reciprocal BF 01 , p(D|M …
(ie, support for M 0 versus M 1 )… |M 1 ), divided by p(D|M 0 ), or as its reciprocal BF 01 , p(D|M …
PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework
AJM Dingemans, M Hinne, KMG Truijen, L Goltstein… - Nature Genetics, 2023 - nature.com
Several molecular and phenotypic algorithms exist that establish genotype–phenotype
correlations, including facial recognition tools. However, no unified framework that investigates …
correlations, including facial recognition tools. However, no unified framework that investigates …
A conceptual introduction to Bayesian model averaging
Many statistical scenarios initially involve several candidate models that describe the data-generating
process. Analysis often proceeds by first selecting the best model according to …
process. Analysis often proceeds by first selecting the best model according to …
[HTML][HTML] Node centrality measures are a poor substitute for causal inference
F Dablander, M Hinne - Scientific reports, 2019 - nature.com
… Max Hinne … The density of a directed acyclic graph is given by d = m/(v(v − 1)), where m
is the … Eichler, M. Causal inference with multiple time series: Principles and problems. Philos…
is the … Eichler, M. Causal inference with multiple time series: Principles and problems. Philos…
[HTML][HTML] Clustering children's learning behaviour to identify self-regulated learning support needs
… This matrix C is of size m × m , where m is the number of ability curves and every C i , j
represents the probability that ability curve i is in the same cluster as ability curve j. …
represents the probability that ability curve i is in the same cluster as ability curve j. …
Wasserstein variational inference
This paper introduces Wasserstein variational inference, a new form of approximate Bayesian
inference based on optimal transport theory. Wasserstein variational inference uses a new …
inference based on optimal transport theory. Wasserstein variational inference uses a new …
Structurally-informed Bayesian functional connectivity analysis
… The G-Wishart is defined for the cone M + (G) of positive-definite symmetric matrices with off-…
0 − 2 / 2 Z G δ 0 D exp − 1 2 D Ω 1 Ω ∈ M + G where δ are the prior degrees of freedom, D a …
0 − 2 / 2 Z G δ 0 D exp − 1 2 D Ω 1 Ω ∈ M + G where δ are the prior degrees of freedom, D a …
[HTML][HTML] The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test
… If an all-or-none decision on the model space is required, we can use the \(P({\mathscr{M}}_{j}
\mid d_{1})\) to select a single model. Once a single model \({\mathscr{M}}_{j}\) is selected, …
\mid d_{1})\) to select a single model. Once a single model \({\mathscr{M}}_{j}\) is selected, …
[HTML][HTML] Validation of structural brain connectivity networks: The impact of scanning parameters
… gradient strength of 600 mT/m. Free fixative was washed … /m and keeping constant gradient
length delta = 8 m s, gradient separation DELTA = 17 m s as well as the echo time TE = 30 m …
length delta = 8 m s, gradient separation DELTA = 17 m s as well as the echo time TE = 30 m …