KEYNOTE TALKS
| Keynote talk I | Tuesday 25.8.2026 | 09:40 - 10:30 | Room: 101 |
| Distributionally robust invariance learning for domain generalization and adaptation | |||
| Speaker: P. Buehlmann | Chair: Cristian Gatu | ||
| Keynote talk II | Thursday 27.8.2026 | 17:40 - 18:30 | Room: 101 |
| Small area estimation of employment indicators under area-level mixed models | |||
| Speaker: D. Morales Co-authors: E. Cabello, M. Esteban, T. Hobza, A. Perez | Chair: Ana Colubi | ||
| Keynote talk III | Friday 28.8.2026 | 12:10 - 13:00 | Room: 101 |
| Time-dependent effects in survival analyses | |||
| Speaker: M. Mittlboeck | Chair: Ioannis Demetriou | ||
PARALLEL SESSIONS
| Parallel session B: COMPSTAT2026 | Tuesday 25.8.2026 | 11:00 - 12:30 |
| Session CI017 | Room: 101 |
| Statistics in the big data era | Tuesday 25.8.2026 11:00 - 12:30 |
| Chair: Dimitris Karlis | Organizer: Dimitris Karlis |
| CI1212: C. Salvatore, A. Moretti, R. Markwitz | |
| Small area estimation with big data covariates | |
| CI1217: V. Chasiotis, L. Wang, D. Karlis | |
| A two-stage subsampling approach for big data | |
| CI1223: L. Wang | |
| Influence-guided Subsampling |
| Session CO032 | Room: 103 |
| Discrete random structures for Bayesian learning | Tuesday 25.8.2026 11:00 - 12:30 |
| Chair: Beatrice Franzolini | Organizer: Giovanni Rebaudo |
| CO1152: B. Franzolini, F. Gaffi | |
| Complexity bounds for Dirichlet process slice samplers | |
| CO1185: R. Corradin, F. Leisen | |
| Autocompound random measures | |
| CO1238: A. Cremaschi, M. De Iorio, G. Page, A. Jasra | |
| Latent modularity in multi-view data | |
| CO1276: F. Denti | |
| Bayesian nonparametric priors and discrete random structures for high-dimensional biological inference |
| Session CO076 | Room: 104 |
| Advances in statistical inference for complex testing problems | Tuesday 25.8.2026 11:00 - 12:30 |
| Chair: Luca Insolia | Organizer: Luca Insolia |
| CO1418: S. Orso, M. Karemera, S. Guerrier, M.-P. Victoria-Feser, M.-G. Xie | |
| Second-order accurate percentile inference with the implicit bootstrap | |
| CO1420: D.-L. Couturier, B. Jiang, T. Jaki | |
| Futility bounds for drop-the-losers designs | |
| CO1425: L. Insolia, Y. Ma, Y. Boulaguiem, S. Guerrier | |
| Partial optimality and applicability for multivariate equivalence testing | |
| CO1417: G. Bakalli, O. Scaillet, S. Guerrier | |
| Equivalence of mutual funds performance |
| Session CO026 | Room: 102 |
| Precision and smart health | Tuesday 25.8.2026 11:00 - 12:30 |
| Chair: Chun-houh Chen | Organizer: Chun-houh Chen |
| CO1192: H.-C. Yang, Y.-J. Huang, Y.-J. Shieh, C.-H. Chen | |
| Unlocking precision and smart health: Insights from genetics, medical imaging, and multimodal AI integration | |
| CO1244: Y.-J. Lee, S.-L. Tsai, C.-W. Chen, S.-K. Chu, C.-T. Yang, J.-H. Yang, Y.-J. Liang, Y.-C. Lin, H.-N. Hsieh, S.-Y. Hu, T.-J. Yen, C.-H. Chen, H.-C. Yang | |
| XGBoost-based prediction of self-reported diseases and QTs from multimodal image reports and PRS in Taiwan biobank | |
| CO1272: S.-K. Chu | |
| Modeling interactions for precision medicine: From long range epistasis to image genomic fusion in neurological disease | |
| CO1310: H. Chen, Y.-M. Yeh, Y. Chang, H.-Y. Chen | |
| Image-based whole-transcriptome deep learning predicts prognosis in lung adenocarcinoma |
| Session CC048 | Room: 201 |
| Multivariate analysis | Tuesday 25.8.2026 11:00 - 12:30 |
| Chair: Maria Brigida Ferraro | Organizer: COMPSTAT |
| CC1165: K. Adachi | |
| A nesting relation among principal component and factor analysis procedures | |
| CC1181: P. Jiang, Y. Uematsu, T. Yamagata | |
| Bias correction in factor-augmented regression models with weak factors | |
| CC1380: M. Herp | |
| Location-scale graphical model | |
| CC1401: K. Uno, T. Nakagawa, T. Kawashima | |
| Assessing and comparing rotation methods using Thurstone's simple structure criteria |
| Parallel session C: COMPSTAT2026 | Tuesday 25.8.2026 | 14:00 - 15:00 |
| Session CO033 | Room: 102 |
| Learning for high-dimensional, longitudinal, and multimodal data | Tuesday 25.8.2026 14:00 - 15:00 |
| Chair: Karel Hron | Organizer: Xinyuan Song |
| Session CO028 | Room: 101 |
| Statistical methods for the analysis of economic data | Tuesday 25.8.2026 14:00 - 15:00 |
| Chair: Massimiliano Caporin | Organizer: Massimiliano Caporin |
| CO1252: M.M. Dickson, Y. Tille, F. Santi, D. Giuliani, G. Espa | |
| Achieving global and within-group spatial spreading in survey sampling | |
| CO1296: M. Costola, M. Billio, G. Bean | |
| Forecasting residential mortgage default: The role of energy efficiency | |
| CO1232: M. Caporin, S. Paterlini, P. Duttilo | |
| Range-based signed volatility estimation and the goodvol/bad vol conundrum |
| Session CC052 | Room: 103 |
| Biostatistics | Tuesday 25.8.2026 14:00 - 15:00 |
| Chair: Anuradha Roy | Organizer: COMPSTAT |
| CC1353: T. Perez-Perez, R. Muddiman, E. Medrano, E. McClenaghan, J. Tazare, F. Boland, E. Wallace, T. Fahey, L. Wei, C. Hughes, A. Doherty, F. Moriarty | |
| Causal inference for tapering strategies in deprescribing using target trial emulation: A simulation study | |
| CC1390: P. Lai, T. Sit | |
| Quantile recurrence time model with time-dependent covariates | |
| CC1396: T. Anzai, K. Takahashi | |
| Detection of ADR signals in spontaneous reporting systems under potential reporting rate changes |
| Session CC061 | Room: 104 |
| Statistical modelling | Tuesday 25.8.2026 14:00 - 15:00 |
| Chair: Maria Brigida Ferraro | Organizer: COMPSTAT |
| CC1284: N. Nakhaeirad, T. Mohan, S. Skhosana, S.Y. Samadi | |
| A circular linear interval-valued regression model | |
| CC1381: D. Bracale, G. Michailidis | |
| Equilibrium and pricing in consumer networks with nonlinear utilities: An online shape-constrained learning approach | |
| CC1251: F. Caeiro | |
| A tail-based estimation approach for the shape parameter of the three-parameter log-logistic distribution |
| Session CC081 | Room: 201 |
| Computational inference | Tuesday 25.8.2026 14:00 - 15:00 |
| Chair: Chun-houh Chen | Organizer: COMPSTAT |
| CC1186: E.T. Paterson Hughes | |
| Efficient Bayesian filtering and inference for integro-difference equation models | |
| CC1373: H. Pechoux, R. Azais, B. Henry | |
| Leveraging one-step transitions to improve Markov chain inference | |
| CC1402: L. Brusa, C. Matias | |
| Scalable variational inference for hypergraph stochastic blockmodels via sample-to-population approximation |
| Parallel session D: COMPSTAT2026 | Tuesday 25.8.2026 | 15:30 - 17:30 |
| Session CO041 | Room: 102 |
| Advances in distributional data analysis | Tuesday 25.8.2026 15:30 - 17:30 |
| Chair: Luke Barratt | Organizer: Luke Barratt |
| CO1297: N. Georgakis | |
| Entropic optimal transport beyond product reference couplings: The Gaussian case on Euclidean space | |
| CO1271: P. Mueller, Y. Ni, K. Nguyen | |
| Bayesian multivariate density-density regression (DDR) | |
| CO1292: L. Barratt, J. Aston | |
| Schools and house prices: Spatiotemporal regression of quantile functions on categorical covariates | |
| CO1319: J. Park | |
| Frechet regression of multivariate distributions with nonparanormal transport | |
| CO1352: Y. Jiang, J. Bigot | |
| Wasserstein auto-regressive models for modeling multivariate distributional time series |
| Session CO023 | Room: 101 |
| Advances on the analysis of large-scale bibliographic database | Tuesday 25.8.2026 15:30 - 17:30 |
| Chair: Frederick Kin Hing Phoa | Organizer: Frederick Kin Hing Phoa |
| CO1193: W.-C. Chiang, F.K.H. Phoa, H. Hamada | |
| Hierarchical clustering of subject co-occurrence networks: A robustness-based journal interdisciplinarity assessment | |
| CO1262: T. Kunt | |
| Detecting communities of authors using clique relaxations in large bibliographic databases | |
| CO1391: T.-Y. Chen, F.K.H. Phoa | |
| Modeling academic collaboration networks using hypergraph theory: A large-scale scientometric analysis of Scopus data | |
| CO1395: F.K.H. Phoa, H. Jung, S.-H. Kim | |
| Preferential attachment hypergraph model with randomized hyperedge count and size | |
| CO1398: Y. Yasui, J. Nakano | |
| Analyzing patent citations using a stochastic generative model |
| Session CO034 | Room: 103 |
| Emerging trends in machine learning and data-driven science | Tuesday 25.8.2026 15:30 - 17:30 |
| Chair: Christian Acal | Organizer: Christian Acal |
| CO1250: P.P. Jurado-Bascon, J.A. Villatoro Garcia, P. Carmona Saez | |
| Meta-analysis for the integration of multi-omics data: Development and application of package GSEMA | |
| CO1236: H. Ortiz, C. Acal, F. Fortuna, A. Naccarato, A.M. Aguilera | |
| A functional independent component analysis approach for clustering functional data | |
| CO1249: J.L. Rueda Sanchez, M.D.M. Rueda, B. Cobo Rodriguez, R. Ferri-Garcia | |
| Sample integration using the bootstrap method and machine learning algorithms | |
| CO1245: A. Garcia-Burgos, B. Gonzalez-Alzaga, M. Lacasana, P. Paraggio, N. Rico-Castro, D. Romero-Molina | |
| Imputation of fetal growth trajectories: A comparison between GLS models and the non-homogeneous lognormal process | |
| CO1263: F. Navas, M.L. Gamiz, R. Nozal, R.-M. Rocio | |
| Unsupervised anomaly analysis in structural data and spatio-temporal trajectories |
| Session CC058 | Room: 201 |
| Statistical learning | Tuesday 25.8.2026 15:30 - 17:30 |
| Chair: Garth Tarr | Organizer: COMPSTAT |
| CC1248: S. Adhikari, M. Loecher, A. Gevaert, B. Pfeifer, A. Holzinger | |
| The revival of bagged trees: Hierarchical shrinkage as a regularization tool | |
| CC1383: T. Shimamura | |
| Skip-zeros variational inference with factored experts for ultra-huge single-cell RNA data | |
| CC1357: S. Alharbi, S. Peiris, R. Hunt | |
| Avoiding future data leakage in lag-based machine learning models for time series forecasting: An XGBoost case study | |
| CC1403: T. Berger | |
| Fitting well but filtering poorly: Residual diagnostics for recurrent neural networks in volatility modeling | |
| CC1405: M. Norouzirad, M. Lopes, T. Bandeira | |
| Correlation-informed adaptive regularization for multiclass glioma subtype prediction |
| Session CC079 | Room: 104 |
| Copulas | Tuesday 25.8.2026 15:30 - 17:30 |
| Chair: Dimitris Karlis | Organizer: COMPSTAT |
| CC1350: N. Luo, O. Grothe | |
| Wasserstein transport between copulas via a Benamou-Brenier-type dynamical formulation | |
| CC1355: A. Nalpantidi, D. Karlis | |
| A pairwise likelihood framework for multivariate ordinal time series | |
| CC1361: N. Zhang | |
| Network-filtered copula segmentation for correlation break detection | |
| CC1387: S. Cakar, C. Yozgatligil | |
| A copula-based mixed-effects model for spatio-temporal dependence in fNIRS data | |
| CC1392: R. Dettoni | |
| Identification and inference in triangular models with flexible copula dependence |
| Parallel session E: COMPSTAT2026 | Wednesday 26.8.2026 | 09:00 - 10:30 |
| Session CI019 | Room: 101 |
| Feature selection and statistical learning for structured data | Wednesday 26.8.2026 09:00 - 10:30 |
| Chair: Garth Tarr | Organizer: Garth Tarr |
| CI1345: N. Krstic, G. Cohen Freue | |
| HFG LASSO: A method for models with hierarchical categorical predictors | |
| CI1348: M. Evangelou, F. Feser | |
| Bayesian sparse-group SLOPE for controlling the false discovery rate | |
| CI1220: K. Mylona, S. Han, S. Gilmour, R. Zhou | |
| Hierarchical orthogonal subsampling |
| Session CO029 | Room: 103 |
| Reliable feature extraction and analysis for complex data | Wednesday 26.8.2026 09:00 - 10:30 |
| Chair: Mika Sato-Ilic | Organizer: Mika Sato-Ilic |
| CO1213: M. Yamamura, H. Yanagihara | |
| An individually optimizable smoothing spline GMANOVA model | |
| CO1254: Y. Yamamoto, H. Kubomatsu, S. Yamada, T. Imanishi | |
| Analysis of disease similarities and bacterial co-occurrences from electronic health records | |
| CO1279: M. Sato-Ilic, P. Ilic | |
| Latent feature extraction based on asymmetric degree of reliability for fuzzy clustering | |
| CO1293: R. Moriya, K. Tanioka, H. Yadohisa | |
| Unfolding of asymmetric dissimilarity data based on clustered lasso |
| Session CO024 | Room: 102 |
| Advances in multivariate and time series data analysis | Wednesday 26.8.2026 09:00 - 10:30 |
| Chair: Zihao Pu | Organizer: Philip Yu |
| CO1183: B. Su, K. Zhu | |
| Inference for the panel ARMA--GARCH model when both N and T are large | |
| CO1189: Z. Pu, B. Su, K. Zhu | |
| Testing for second-order cross-sectional dependence and serial dependence in large dynamic panel models | |
| CO1188: Y. Zhang, K. Zhu, C. Yu | |
| Tensor double autoregressive model with application to heavy-tailed tensor time series data | |
| CO1325: P. Yu, O. Wong | |
| Forecasting job market demand in Hong Kong using time series foundation models |
| Session CC080 | Room: 201 |
| Computational statistics | Wednesday 26.8.2026 09:00 - 10:30 |
| Chair: Andreas Artemiou | Organizer: COMPSTAT |
| CC1344: G. Inan, I. Goksel | |
| A leakage-free nested cross-validation approach for adaptive penalized Cox models | |
| CC1359: R. Dyckerhoff, E. Mendros, S. Nagy | |
| Computing halfspace depth in $O(n^{d-1})$ via topological sweep | |
| CC1393: P. Hadjidoukas, E.-M. Kontopoulou, E. Gallopoulos | |
| Task-parallel model selection and numerical optimization in R | |
| CC1399: J. Machalova | |
| Spline approximation of probability density functions in Bayes spaces |
| Session CC055 | Room: 104 |
| Applied statistics and econometrics | Wednesday 26.8.2026 09:00 - 10:30 |
| Chair: Luke Barratt | Organizer: COMPSTAT |
| CC1210: K. Trzcinska | |
| Income and wealth inequality by gender: An empirical analysis | |
| CC1174: A. Ptak-Chmielewska, P. Kopciuszewski | |
| New modelling method based on data augmentation applied to binary variables | |
| CC1412: A. Seshagiri, S. Deb, T. Das | |
| Does economic strength or political and civil freedom improve international tourism? An econometric analysis | |
| CC1369: H. Tan | |
| Econometric modeling of doctors knowledge contribution in online healthcare platforms |
| Parallel session F: COMPSTAT2026 | Wednesday 26.8.2026 | 11:00 - 12:30 |
| Session CI020 | Room: 101 |
| Design and analysis of experiments | Wednesday 26.8.2026 11:00 - 12:30 |
| Chair: Kalliopi Mylona | Organizer: Kalliopi Mylona |
| CI1151: C. Tommasi, A. Cia-Mina, L. Deldossi, J. Lopez-Fidalgo | |
| Analytical inclusion probabilities for optimal subsampling under misspecification | |
| CI1229: S. Georgiou, S. Stylianou, D. Athanasaki | |
| Orthogonal composite designs for response surface modeling | |
| CI1324: H. Evangelaras, E. Androulakis | |
| A class of efficient order-of-addition experiments for the pairwise ordering regression model |
| Session CO043 | Room: 104 |
| Computational methods for industrial statistics | Wednesday 26.8.2026 11:00 - 12:30 |
| Chair: Johan Lim | Organizer: Johan Lim |
| CO1187: J. Im, C. Lee, J.H.T. Kim, N. Kang | |
| Structure-preserving time series synthesis | |
| CO1256: S. Lee, J. Lim, S. Ahn | |
| Monte Carlo estimation of ARL with censored data | |
| CO1295: W. Jang | |
| Bayesian and empirical Bayes approaches for wildlife abundance estimation using aggregated camera-trap data | |
| CO1274: J.-H. Won | |
| Partial correlation network estimation by semismooth Newton methods |
| Session CO030 | Room: 102 |
| Advances in functional and high-dimensional data analysis | Wednesday 26.8.2026 11:00 - 12:30 |
| Chair: Ioannis Kalogridis | Organizer: Stefan Van Aelst, Ioannis Kalogridis |
| CO1172: I. Kalogridis | |
| Penalized spline M-estimators for discretely sampled functional data: Existence and asymptotics | |
| CO1224: S. Nagy, T. Mrkvicka, A. Elias | |
| On boxplots for functional data | |
| CO1237: M. Cavazzutti, E. Arnone, S. Nagy, L. Sangalli | |
| Finite elements based data depths for the analysis of functional data over non-convex domains | |
| CO1240: S. Van Aelst, M. Salibian-Barrera | |
| Robust bootstrap inference for nonparametric regression |
| Session CO070 | Room: 103 |
| Discrete events: Spatiotemporal modelling and high-dimensional inference | Wednesday 26.8.2026 11:00 - 12:30 |
| Chair: Carolina Euan | Organizer: Carolina Euan |
| CO1253: I. Martinez-Hernandez | |
| Point process model for human activity data: Detecting changepoints | |
| CO1285: W. Yue, I. Martinez-Hernandez, J. Tawn | |
| Statistical inference for induced seismicity using covariate-driven ETAS models | |
| CO1298: L. Rimella | |
| Scalable calibration of individual-based epidemic models through categorical approximations | |
| CO1308: C. Euan | |
| Modelling neural connectivity with Bernoulli autoregressive processes |
| Session CP001 | Room: 201 |
| Poster Session | Wednesday 26.8.2026 11:00 - 12:30 |
| Chair: Jose Grana Colubi | Organizer: COMPSTAT |
| Parallel session G: COMPSTAT2026 | Wednesday 26.8.2026 | 14:00 - 15:30 |
| Session CI018 | Room: 101 |
| Special invited session IV | Wednesday 26.8.2026 14:00 - 15:30 |
| Chair: Yoshikazu Terada | Organizer: Hiroshi Yadohisa |
| CI1226: D. Kurisu, T. Otsu | |
| Empirical likelihood for manifolds | |
| CI1261: S. Huckemann | |
| Non-euclidean statistics for learning structural biology | |
| CI1337: Y. Terada, A. Yara | |
| A theory of nonparametric covariance function estimation |
| Session CO012 | Room: 102 |
| New challenges in high-dimensional and complex data inference | Wednesday 26.8.2026 14:00 - 15:30 |
| Chair: Anuradha Roy | Organizer: Anuradha Roy |
| CO1239: K. Hirose | |
| Computing the compatibility constant for the lasso by numerical optimization | |
| CO1154: H. Raubenheimer, T. Verster, G. Breed, A. Coop | |
| Incomplete inference model to impute loss given default within a regulatory capital model: A South African case study | |
| CO1218: C. Drago | |
| Kernel densities as symbolic data for interval-valued composite indicators | |
| CO1203: A. Roy, F. Montes | |
| Hypothesis testing of mean interval for p-dimensional interval-valued data |
| Session CO069 | Room: 103 |
| Advances in learning complex data models | Wednesday 26.8.2026 14:00 - 15:30 |
| Chair: Mauro Bernardi | Organizer: Mauro Bernardi |
| CO1243: M. Borriero, M. Lupparelli, G.M. Marchetti, V. Vinciotti | |
| Invariant causal prediction under causal insufficiency | |
| CO1389: M. Bernardi, A. Canale, M. Stefanucci | |
| Scalable convex clustering with adaptive sparse weights | |
| CO1404: C. Busatto, M. Bernardi, M. Cattelan, A. Roverato | |
| Bayesian covariance matrix estimation in high dimensions | |
| CO1414: G. Luzzatto, M. Bernardi, M. Bertolini, R. Canesi, L. Doretti, D. Gamannossi Degl\'Innocenti | |
| Bayesian variable selection for structured quantile regression |
| Session CC057 | Room: 201 |
| Spatial statistics | Wednesday 26.8.2026 14:00 - 15:30 |
| Chair: Luke Barratt | Organizer: COMPSTAT |
| CC1207: M. Savery, S. Luca | |
| Tensions in ecological data collection: Integrating data sources in Bayesian design for species distribution modelling | |
| CC1374: K. Takahashi, H. Shimadzu | |
| Identifying multiple hotspot clusters via within-cluster heterogeneity | |
| CC1153: Y.-T. Hwang | |
| Modeling zero-inflated spatial proportion data with a structured beta spatial regression model | |
| CC1386: T. Ohnishi | |
| Large-scale comparison and clustering of spatial point patterns using the two-dimensional Kolmogorov-Smirnov statistic |
| Session CC060 | Room: 104 |
| Machine learning in applications | Wednesday 26.8.2026 14:00 - 15:30 |
| Chair: Andreas Artemiou | Organizer: COMPSTAT |
| CC1336: J. Chu | |
| Extreme value-informed multi-modal transfer learning for blockchain fraud detection | |
| CC1415: J. Arevalo, J. Escobar | |
| A snow water equivalent retrieval method from satellite-based passive microwave observations using machine learning | |
| CC1416: J. Karlowska-Pik | |
| DNA-based predictive models for human appearance characteristics in forensic science | |
| CC1408: M. Ortu, L. Frigau, G. Contu, F. Mola | |
| Geometry-aware semantic complexity indices for legal texts in transformer embedding spaces |
| Parallel session H: COMPSTAT2026 | Thursday 27.8.2026 | 09:00 - 10:00 |
| Session CV046 | Room: Virtual R01 |
| Computational and methodological statistics | Thursday 27.8.2026 09:00 - 10:00 |
| Chair: Andreas Artemiou | Organizer: COMPSTAT |
| CV1338: F. Demaria, M. Cavicchioli, A. Nigri | |
| Estimation methods and empirics of hidden Markov switching models with skew-normal innovations | |
| CV1347: T. Moriyama | |
| Extreme value theory-based kernel smoothing for tail probability estimation | |
| CV1382: C.-E. Rabier, C. Delmas | |
| The likelihood ratio test for gene mapping in the general framework of location-scale families |
| Session CO074 | Room: 101 |
| Discrete values time series | Thursday 27.8.2026 09:00 - 10:00 |
| Chair: Dimitris Karlis | Organizer: Dimitris Karlis |
| CO1242: K. Fokianos | |
| Inference and applications of multivariate integer-valued time series | |
| CO1282: L. Sousa, M. Monteiro, I. Pereira, D. Karlis | |
| K-INGARCH clustering for discrete-valued time series | |
| CO1334: J. Peyhardi, D. Karlis | |
| INAR processes based on convolution thinning operator with dependent innovations |
| Session CC056 | Room: 103 |
| Bayesian statistics | Thursday 27.8.2026 09:00 - 10:00 |
| Chair: Andrea Cremaschi | Organizer: COMPSTAT |
| CC1201: T. Kettlewell, Y. Cheng, T. Otto, V. Macaulay, M. Gupta | |
| Bayesian regression using zero-inflated, high-kurtosis count data featuring data augmentation | |
| CC1354: A. Damoulaki, I. Ntzoufras | |
| Scalable Bayesian variable selection without MCMC | |
| CC1202: B. Van Velthoven, S. Luca | |
| Bayesian structural modelling of environmental extremes |
| Session CC082 | Room: 104 |
| Design and survey methodology | Thursday 27.8.2026 09:00 - 10:00 |
| Chair: Kalliopi Mylona | Organizer: COMPSTAT |
| CC1195: C.-Y. Lin | |
| Efficient and robust block designs for order-of-addition experiments | |
| CC1424: M. Smeets, H.J. Boonstra | |
| A widely applicable sampling method for spreading the survey burden in business surveys | |
| CC1385: J. Sakshaug | |
| Bayesian integration of probability and nonprobability survey data |
| Session CC085 | Room: 201 |
| COMPSTAT short talks | Thursday 27.8.2026 09:00 - 10:00 |
| Chair: Louisa Kontoghiorghes | Organizer: COMPSTAT |
| CV1433: R. Ozkan, C. Hirsch | |
| Large deviations for linear-region counts in randomly initialized deep piecewise-linear networks | |
| CC1432: Z. Michna, K. Debicki, E. Hashorva | |
| Distributional and extremal behaviour of Brownian motion with exponential resetting |
| Session CC049 | Room: 102 |
| High-dimensional statistics | Thursday 27.8.2026 09:00 - 10:00 |
| Chair: Ana Belen Ramos-Guajardo | Organizer: COMPSTAT |
| Parallel session I: COMPSTAT2026 | Thursday 27.8.2026 | 10:30 - 12:30 |
| Session CI016 | Room: 101 |
| Special invited session II | Thursday 27.8.2026 10:30 - 12:30 |
| Chair: Konstantinos Fokianos | Organizer: Konstantinos Fokianos |
| CI1307: E. Bura, D. Kapla | |
| Generalized multilinear models for sufficient dimension reduction on tensor-valued predictors | |
| CI1309: R. Fried, L. Betting, M. Jeschke | |
| On periodic and Markov switching models for electric load time series of households | |
| CI1231: D. Karlis | |
| Modelling count spatio-temporal data |
| Session CO027 | Room: 102 |
| Data-driven discovery from complex data | Thursday 27.8.2026 10:30 - 12:30 |
| Chair: Garth Tarr | Organizer: Samuel Muller |
| CO1215: J. Vazquez, Y. Ma, K. Marder, T. Garcia | |
| Matching Estimators to censoring rate improves inference with outcome-dependent right-censored covariates | |
| CO1221: G. Tarr, R. Shankar, T. Garcia, J. Ormerod | |
| Feature selection in censored-covariate regression models | |
| CO1225: M. Nouraie, H. Zhu, S. Muller | |
| A stable lasso | |
| CO1260: X. Sun, H. Zhu, G. Tarr, S. Muller | |
| False discovery rate controlled robust variable selection under cellwise contamination | |
| CO1267: J. Freestone, G. Tarr, S. Muller, U. Keich | |
| Response-guided knockoffs for directional FDR control in linear models |
| Session CO035 | Room: 103 |
| HiTEc session: Theory and practice of functional statistics | Thursday 27.8.2026 10:30 - 12:30 |
| Chair: Enea Bongiorno | Organizer: Kwo Lik Lax Chan, Enea Bongiorno |
| CO1211: D. Diz-Castro, M. Febrero-Bande, W. Gonzalez-Manteiga | |
| A kernel-based goodness-of-fit test for functional regression models | |
| CO1227: T. Masak, K. Waghmare, V. Panaretos | |
| The functional graphical lasso | |
| CO1235: H. Ranosova, D. Hlubinka | |
| Time reversibility testing for stochastic processes | |
| CO1277: B. Matteo | |
| Infinite-dimensional spherical kernel ridge regression | |
| CO1283: T. Bortolotti, A. Menafoglio, S. Vantini | |
| Normalized functional conformal prediction for adaptive anomaly detection in spaceborne ground displacement data |
| Session CO031 | Room: 201 |
| Inference of complex structure in network data | Thursday 27.8.2026 10:30 - 12:30 |
| Chair: Pierpaolo De Blasi | Organizer: Pierpaolo De Blasi |
| CO1209: L. Arts | |
| Consistent estimation of the number of clusters in multi-layer and dynamic stochastic block models | |
| CO1281: M. Contisciani | |
| Multiscale network modeling of migration flows in Austria | |
| CO1290: N. Corsini, M. Fop | |
| A Bayesian actor-attribute latent space model for social influence | |
| CO1299: L. Santi, N. Friel | |
| The Bradley-Terry stochastic block model | |
| CO1304: P. De Blasi, M. Amongero | |
| Bayesian nonparametric community detection in assortative stochastic block models |
| Session CC053 | Room: 104 |
| Econometric methods | Thursday 27.8.2026 10:30 - 12:30 |
| Chair: Tatyana Krivobokova | Organizer: COMPSTAT |
| CC1163: I. Casas | |
| Local blockwise wild bootstrap inference for multivariate time-varying coefficient models | |
| CC1326: L. Garcia-Jorcano, L. Sanchis-Marco | |
| An angular combination of forecasting distributions in the energy market | |
| CC1358: A.M. Kabiri, Y. Shi, Z. Jin | |
| Robust volatility forecasting with score-driven MIDAS models: Evidence from commodity futures | |
| CC1407: S. Nagata | |
| Robust variance estimation and inference for spatial panel data without weight matrices | |
| CC1150: E. Iglesias, G. Phillips, D. Wang | |
| Bias approximations for LIML and FLIML in the dynamic simultaneous equation model |
| Parallel session J: COMPSTAT2026 | Thursday 27.8.2026 | 14:00 - 15:30 |
| CO1266: R. Maitra, S. Pal | |
| Tensor-on-tensor time series regression | |
| CO1303: K. Dorman, S. Vijendran, T. Anderson, O. Eulenstein | |
| PREMISE: A quality-aware probabilistic framework for high resolution pathogen resolution in diagnostic sequence samples | |
| CO1312: F. Palumbo, C. Tortora | |
| Probabilistic distance clustering for complex data structures | |
| CO1269: K.L.L. Chan, A. Goia | |
| Enhancing performance in functional nonparametric regression and classification using weighted pseudo-metrics |
| Session CO014 | Room: 103 |
| Recent advances in experimental designs | Thursday 27.8.2026 14:00 - 15:30 |
| Chair: Po Yang | Organizer: Po Yang |
| CO1200: Y. Xiao | |
| Uniform position designs for order-of-addition experiments | |
| CO1204: P. Yang | |
| Model-robust process optimization for data with a multistratum structure | |
| CO1208: S. Xu, Y. Zhou, Z. Zhou | |
| Minimax designs for misspecified linear models with $L_{\infty}$-norm bounded departures | |
| CO1219: C. Shi, L. Wang | |
| Axis-neighbor geometry and length-scale identifiability in Gaussian process models |
| Session CO040 | Room: 102 |
| HiTEc session: Models and computation | Thursday 27.8.2026 14:00 - 15:30 |
| Chair: Andreas Artemiou | Organizer: Andreas Artemiou |
| CO1180: T. Krivobokova, R.A. Morariu | |
| Hierarchical Lasso for multi-factor designs | |
| CO1278: S. Schoenbuchner, R. Daniel, D. Farewell | |
| Regression by composition | |
| CO1302: A. Makrides, A. Karagrigoriou, N. Galanopoulos | |
| Grey and Markov Chain Grey modelling for insurance loss forecasting | |
| CO1339: A. Zverovich | |
| Sparse approximation of functions using stochastic particle flows |
| Session CC063 | Room: 201 |
| Data analysis | Thursday 27.8.2026 14:00 - 15:30 |
| Chair: Domingo Morales | Organizer: COMPSTAT |
| CC1176: N.-H. Chen | |
| Psychological mechanisms of food waste reduction across generations: An integrated value-cognition framework | |
| CC1182: R. Cao, B. Wang, N. Suzen | |
| Gaussian process regression with transfer learning under distribution shift: A joint probability neural kernel approach | |
| CC1397: I. Kanovsky, D. Deinega, B. Barzel | |
| A commonality measure for overlapping clusters detections | |
| CC1169: A.J. Queiroz Sarnaglia, M. Pereira Antunes, R. Moreira Sant Anna, E. Alves Araujo, A. Lucas de Paula, L. Dellaqua Bergamin, D.R. Colombo Dias, B. Zamprogno | |
| A novel BPPIT model for educational forecasting: Projecting SAEB scores via school-level data |
| Session CC083 | Room: 104 |
| Financial econometrics | Thursday 27.8.2026 14:00 - 15:30 |
| Chair: Konstantinos Fokianos | Organizer: COMPSTAT |
| CC1246: P. Jasko | |
| Alternative models for cointegrated time series: Theoretical and empirical study from the Polish stock market | |
| CC1286: D. Stafylas, A. Azevedo, T. Vu | |
| Recent advances in the relationship between stock liquidity and informed trading | |
| CC1363: X. Xie | |
| Regime-specific return predictability in quantiles | |
| CC1378: X. Wang | |
| Testing linearity in functional cointegrating regression |
| Parallel session K: COMPSTAT2026 | Thursday 27.8.2026 | 16:00 - 17:30 |
| Session CO071 | Room: Virtual R01 |
| Methods and applications in network data analysis | Thursday 27.8.2026 16:00 - 17:30 |
| Chair: Riddhi Pratim Ghosh | Organizer: Riddhi Pratim Ghosh |
| CO1216: X. Jin, K. Chan, I. Barnett, R.P. Ghosh | |
| Testing large random graphs of unequal size with applications to fMRI data | |
| CO1222: T.M. Le | |
| Network-based modeling for plant disease dynamics: Data-driven inference and management insights | |
| CO1230: R.P. Ghosh, J.-P. Onnela, I. Barnett | |
| A generalized estimating equation approach to network regression |
| Session CO022 | Room: 101 |
| IASC-LARS IPS: Theoretical and methodological contributions | Thursday 27.8.2026 16:00 - 17:30 |
| Chair: Alba Martinez-Ruiz | Organizer: Alba Martinez-Ruiz |
| CO1257: J. Trejos, V. Bazan | |
| Multidimensional scaling by particle swarm optimization | |
| CO1291: A. Martinez-Ruiz | |
| Global optimization approach for multiblock methods: Applications to large-scale data | |
| CO1170: D.F. Munoz | |
| A simulation-based approach for the optimal order size of new products under uncertainty on forecast parameters | |
| CO1179: P. Canas Rodrigues | |
| Multivariate reconciliation for hierarchical time series |
| Session CO077 | Room: 104 |
| Computational methods for high-dimensional Bayesian models | Thursday 27.8.2026 16:00 - 17:30 |
| Chair: Somak Dutta | Organizer: Somak Dutta |
| Session CO042 | Room: 103 |
| New inference tools for high-dimensional spatial and temporal applications | Thursday 27.8.2026 16:00 - 17:30 |
| Chair: Ranjan Maitra | Organizer: Ranjan Maitra |
| CO1333: C. Llosa, D.M. Dunlavy, R.B. Lehoucq, J. Myers, T. Ma | |
| Reduced-rank generalized tensor-on-tensor regression | |
| CO1300: M. Bhattacharjee, A. Bose | |
| Eliciting core spatial association from spatial time series: A random matrix approach | |
| CO1313: A. Thomas, R. Maitra | |
| Nested sequential inference for hotspot detection in noisy images with cubical persistent homology | |
| CO1314: W. Meiring, R. Liu, C. Zhang, C. Tran, S. Achard, A. Petersen | |
| A mixed model approach for estimating regional functional connectivity from voxel-level BOLD signals |
| Session CO013 | Room: 102 |
| Recent advances in high dimensional statistics | Thursday 27.8.2026 16:00 - 17:30 |
| Chair: Aranyak Acharyya | Organizer: Aranyak Acharyya |
| CO1258: S. Nandy, A. Chakraborty, S. Chatterjee | |
| PriME: Privacy-aware membership profile estimation in networks | |
| CV1316: A. Acharyya, J. Agterberg, Y. Park, C. Priebe | |
| Investigating finite-sample properties of vector embeddings of black-box LLMs | |
| CO1317: N. Chakraborty, S. Karmakar, H. Koul | |
| A bootstrap two sample test for high-dimensional covariance matrices | |
| CO1320: S. Roy | |
| FLIPHAT: Joint differential privacy for high dimensional linear bandits |
| Session CC084 | Room: 201 |
| Inference for complex models | Thursday 27.8.2026 16:00 - 17:30 |
| Chair: Alessandra Amendola | Organizer: COMPSTAT |
| CC1241: G. Uwimpuhwe, R. Drikvandi | |
| Testing of variance components in nonlinear mixed models with penalized splines | |
| CC1368: A.M. Pailden, M.D. Lucagbo | |
| Nonparametric bootstrap solution to the multivariate inverse regression problem | |
| CC1171: L. Wu | |
| Joint models in longitudinal studies for efficient and robust inferences | |
| CC1384: H. Shimadzu | |
| Estimating parameters in allometric growth differential-equation models |
| Parallel session M: COMPSTAT2026 | Friday 28.8.2026 | 09:00 - 10:30 |
| Session CI015 | Room: 101 |
| Dimensionality reduction of complex data structures | Friday 28.8.2026 09:00 - 10:30 |
| Chair: Maria Brigida Ferraro | Organizer: Maria Brigida Ferraro |
| CI1275: A. Artemiou | |
| Extending Real-time sufficient dimension reduction for complex data structures | |
| CI1305: A.B. Ramos-Guajardo, G. Gonzalez-Rodriguez | |
| A geometric discriminant framework for classification of fuzzy data | |
| CO1323: E. Bongiorno, G. Aletti | |
| Embedding zero-inflated data: A Hilbert space PCA approach |
| Session CO067 | Room: 201 |
| HiTEc session: Topic models, network analysis, and constrained estimation | Friday 28.8.2026 09:00 - 10:30 |
| Chair: Kalliopi Mylona | Organizer: Ana Colubi |
| CO1294: V. Batagelj | |
| Variations on projection of 2-mode network | |
| CO1422: I. Demetriou | |
| Shape-constrained estimation of diminishing returns in the global literacy-income relationship. | |
| CO1419: L. Kontoghiorghes | |
| Assessing consistency in Poisson NMF estimation for topic models | |
| CO1273: A. Staszewska-Bystrova, P. Winker, V. Bystrov | |
| A statistical framework for topic modeling |
| Session CO037 | Room: 102 |
| Statistical depth and hypothesis testing | Friday 28.8.2026 09:00 - 10:30 |
| Chair: Bojana Milosevic | Organizer: Bojana Milosevic |
| CO1287: B. Milosevic, J. Zivkovic | |
| Testing central symmetry: A data depth approach | |
| CO1301: D. Gaigall, P. Wuebbolding | |
| Aspects of statistical testing with incomplete observations | |
| CO1329: V. Gotovac Dogas | |
| Comparison of random sets distributions via statistical depths | |
| CO1306: F. Bocinec, S. Nagy, H. Yeon | |
| Projection depth for functional data |
| Session CO072 | Room: 103 |
| Spatial cluster detection and spatial autocorrelation analysis | Friday 28.8.2026 09:00 - 10:30 |
| Chair: Fumio Ishioka | Organizer: Fumio Ishioka |
| CO1233: F. Ishioka | |
| Statistical detection of arbitrarily shaped spatial clusters in continuous data | |
| CO1206: S. Kajinishi, T. Oribe, Y. Takemura, F. Ishioka | |
| Detecting spatial clusters of MLB batters' hot and cold spots using scan statistics | |
| CO1259: Y. Takemura, F. Ishioka, K. Kurihara | |
| Application of a reliability evaluation method for space-time clusters using a hierarchical structure | |
| CO1194: T. Kubota | |
| Spatial autocorrelation and regional disparities in household welfare in Indonesia |
| Session CO073 | Room: 104 |
| Modern semiparametric methods for causal inference and provider profiling | Friday 28.8.2026 09:00 - 10:30 |
| Chair: Fan Li | Organizer: Fan Li |
| CO1331: G. Wang | |
| Robust trial augmentation for survival outcomes | |
| CO1328: G. Tong | |
| Where to weight: Estimating population causal effects with weighted double score matching in complex surveys | |
| CO1330: W. Wu, F. Li, I. Diaz | |
| Design-based provider profiling via constrained double/debiased deep learning |
| Parallel session N: COMPSTAT2026 | Friday 28.8.2026 | 11:00 - 12:00 |
| Session CV078 | Room: Virtual R01 |
| Computational statistics in applications | Friday 28.8.2026 11:00 - 12:00 |
| Chair: Ana Belen Ramos-Guajardo | Organizer: COMPSTAT |
| CV1199: A. Verhasselt | |
| Quantile regression for 2022 New York City marathon data | |
| CV1411: C. Tangin, M.D. Lucagbo | |
| Regression-based robust simultaneous prediction intervals | |
| CV1410: M. Diaz | |
| Thematic coding meets AI |
| Session CO044 | Room: 201 |
| HiTEc session: Sensitivity and Robustness in Complex Regression Models | Friday 28.8.2026 11:00 - 12:00 |
| Chair: Matus Maciak | Organizer: Matus Maciak |
| CO1157: J. Kalina | |
| From robust neural networks toward robust nonlinear quantile estimation | |
| CO1318: R. Alzbutas, E. Juozapaitis | |
| Global sensitivity analysis of a nonlinear battery replica model for design under uncertainty | |
| CO1341: K. Dvorakova, J. Kalina | |
| Robust regularized regression with a labor market application |
| Session CO075 | Room: 104 |
| Advanced computational mediation methods for complex data | Friday 28.8.2026 11:00 - 12:00 |
| Chair: Guangyu Tong | Organizer: Guangyu Tong |
| Session CO068 | Room: 102 |
| CMStatistics session | Friday 28.8.2026 11:00 - 12:00 |
| Chair: Alessandra Amendola | Organizer: Erricos Kontoghiorghes |
| CO1234: C. Gatu, M. Hofmann, M. Demosthenous, E. Kontoghiorghes | |
| Algorithms for exact variable selection in regression | |
| CO1198: A. Amendola, V. Candila, L. Aldieri | |
| ESG-based global minimum variance portfolios: Allocation weights, performance metrics and stochastic dominance | |
| CO1288: C. Erlwein-Sayer, S. Kepezkaya, N. Packham, A. Petukhina | |
| Sentiment-driven forecasting of fractional trading activity |
| Session CO039 | Room: 101 |
| HiTEc session: Recent advance in machine learning methods | Friday 28.8.2026 11:00 - 12:00 |
| Chair: Weining Wang | Organizer: Weining Wang |
| CO1315: W. Wang | |
| Transformer-based CoVaR: Systemic risk in textual information | |
| CO1322: M. Xu, T. Otsu, K. Shinoda | |
| Semiparametric and nonparametric instrumental variable estimation with first stage isotonic regression | |
| CO1335: J.M. Rodriguez-Poo, D. Henderson, A. Soberon, S. Sperlich | |
| Nonparametric time-varying gravity models with three-way fixed effects |
| Session CO005 | Room: 103 |
| HiTEc session: Complex data | Friday 28.8.2026 11:00 - 12:00 |
| Chair: Enea Bongiorno | Organizer: Ana Colubi |
| CO1247: K. Hron, J. Neslehova, C. Genest, A. Czolkova, O. Ulicny | |
| A semiparametric approach to multivariate density decomposition in Bayes spaces | |
| CO1255: T.B.T. Ngo, J. Park | |
| Incomplete trajectories with covariates | |
| CC1427: J. Grana Colubi | |
| Estimation and inference in regression models for random star-shaped sets |