Thomas Süβe (Suesse)
Thomas Süβe (Suesse)
Senior lecturer in statistics, University of Wollongong
Verified email at - Homepage
Cited by
Cited by
New concepts of multiple tests and their use for evaluating high-dimensional EEG data
C Hemmelmann, M Horn, T Süsse, R Vollandt, S Weiss
Journal of neuroscience methods 142 (2), 209-217, 2005
Multivariate tests for the evaluation of high-dimensional EEG data
C Hemmelmann, M Horn, S Reiterer, B Schack, T Süsse, S Weiss
Journal of Neuroscience Methods 139 (1), 111-120, 2004
Identifying mutual information transfer in the brain with differential-algebraic modeling: Evidence for fast oscillatory coupling between cortical somatosensory areas 3b and 1
J Haueisen, L Leistritz, T Süsse, G Curio, H Witte
Neuroimage 37 (1), 130-136, 2007
Graphical diagnostics to check model misspecification for the proportional odds regression model
I Liu, B Mukherjee, T Suesse, D Sparrow, SK Park
Statistics in medicine 28 (3), 412-429, 2009
On the spatio-temporal organisation of quadratic phase-couplings in ‘trace alternant’EEG pattern in full-term newborns
H Witte, P Putsche, K Schwab, M Eiselt, M Helbig, T Suesse
Clinical neurophysiology 115 (10), 2308-2315, 2004
Coupled oscillators for modeling and analysis of EEG/MEG oscillations
L Leistritz, P Putsche, K Schwab, W Hesse, T Süße, J Haueisen, H Witte
Biomedizinische Technik 52 (1), 83-89, 2007
The analysis of stratified multiple responses
I Liu, T Suesse
Biometrical Journal: Journal of Mathematical Methods in Biosciences 50 (1 …, 2008
Bayesian nonparametric reliability analysis for a railway system at component level
P Mokhtarian, MR Namzi-Rad, TK Ho, T Suesse
2013 IEEE International Conference on Intelligent Rail Transportation …, 2013
Marginalized exponential random graph models
T Suesse
Journal of Computational and Graphical Statistics 21 (4), 883-900, 2012
Capturing multivariate spatial dependence: Model, estimate and then predict
N Cressie, S Burden, W Davis, PN Krivitsky, P Mokhtarian, T Suesse, ...
Statistical Science 30 (2), 170-175, 2015
Computational aspects of the EM algorithm for spatial econometric models with missing data
T Suesse, A Zammit-Mangion
Journal of Statistical Computation and Simulation 87 (9), 1767-1786, 2017
Marginal maximum likelihood estimation of SAR models with missing data
T Suesse
Computational Statistics & Data Analysis 120, 98-110, 2018
Modelling Strategies for Repeated Multiple Response Data
T Suesse, I Liu
International Statistical Review 81 (2), 230-248, 2013
Mantel–Haenszel estimators of odds ratios for stratified dependent binomial data
T Suesse, I Liu
Computational Statistics & Data Analysis 56 (9), 2705-2717, 2012
Estimation of spatial autoregressive models with measurement error for large data sets
T Suesse
Computational Statistics 33 (4), 1627-1648, 2018
Methods for parameter identification in oscillatory networks and application to cortical and thalamic 600 Hz activity
L Leistritz, T Suesse, J Haueisen, B Hilgenfeld, H Witte
Journal of Physiology-Paris 99 (1), 58-65, 2006
Estimating cross-classified population counts of multidimensional tables: an application to regional Australia to obtain pseudo-census counts
T Suesse, MR Namazi-Rad, P Mokhtarian, J Barthélemy
Journal of Official Statistics 33 (4), 1021-1050, 2017
Relationship between learning in the engineering laboratory and student evaluations
S Nikolic, TF Suesse, T Goldfinch, TJ McCarthy
Assessing the fit of finite mixture distributions
T Suesse, JCW Rayner, O Thas
Australian & New Zealand Journal of Statistics 59 (4), 463-483, 2017
Maximising resource allocation in the teaching laboratory: understanding student evaluations of teaching assistants in a team-based teaching format
S Nikolic, TF Suesse, TJ McCarthy, TL Goldfinch
European Journal of Engineering Education 42 (6), 1277-1295, 2017
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