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ORCIDStatistics and Computing, Volume 36
Volume 36, Number 1, February 2026
- Gaorong Li
, Liugen Xue, Riquan Zhang:
Penalized robust estimating equation and variable selection in a partially linear single-index varying-coefficient model. 1 - Nadhir Ben Rached, Erik von Schwerin, Gaukhar Shaimerdenova, Raúl Tempone:
Importance sampling for rare event tracking within the ensemble Kalman filtering framework. 2 - Volodymyr Melnykov, Salvatore Ingrassia:
Uncertain model selection criteria for mixture modeling. 3 - Martina Boschi, Ernst C. Wit:
Goodness of fit in relational event models. 4 - Jinzhao Liu, Chao Liu, Jian Qing Shi, Tom Nye:
Wrapped Gaussian Process Functional Regression Model for Batch Data on Riemannian Manifolds. 5 - Li-Pang Chen:
Inverse probability weighting estimation under ultrahigh-dimensional error-prone covariates and misclassified treatments. 6 - Riccardo Corradin, Luca Danese, Wasiur R. KhudaBukhsh, Andrea Ongaro:
Model-based clustering of time-dependent observations with common structural changes. 7 - M. E. J. Newman:
Fast sampling and model selection for Bayesian mixture models. 8 - Theodoros Perdikis, Giovanni Celano, Subhabrata Chakraborti:
Practical Considerations for Implementing the Isolation Forest EWMA Control Chart in Phase II Process Monitoring. 9 - Amparo Baíllo, Javier Cárcamo:
Bootstrap tests for almost goodness-of-fit. 10 - Fanqun Li, Houwu Wu, Sanying Feng, Yan Fan, Mingtao Zhao:
A model identification and selection method for varying coefficient EV models with missing responses. 11 - Muhammad Qasim, Kristofer Månsson, Narayanaswamy Balakrishnan:
Best-subset instrumental variable selection method using mixed integer optimization with applications to health-related quality of life and education-wage analyses. 12 - Frédéric Cérou, Patrick Héas, Mathias Rousset:
Adaptive Reduced Multilevel Splitting. 13 - Santiago Marin, Bronwyn Loong, Anton H. Westveld:
BOB: Bayesian optimized bootstrap for approximate posterior sampling in Gaussian mixture models. 14 - Zhen Qi, Xu Guo, Haobo Qi:
Distributed learning for high-dimensional factor augmented regression models. 15
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