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Zhang, L.; Zhu, T.; Zhang, J. T., Two-sample Behrens-Fisher problems for high-dimensional data: A normal reference scale-invariant test, J. Appl. Stat, 456-476 (2023) · Zbl 07697886 |
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Pustokhin, D.; Pustokhina, I.; Dinh, P.; Phan, S.; Nguyen, G.; Joshi and, G.; Shankar, K., An effective deep residual network based class attention layer with bidirectional LSTM for diagnosis and classification of COVID-19, J. Appl. Stat., 477-494 (2023) · Zbl 07697887 |
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Yuan, Mi.; Wen, Q., A practical two-sample test for weighted random graphs, J. Appl. Stat, 495-511 (2023) · Zbl 07697888 |
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Zhao, M.; Xu, X.; Zhu, Y.; Zhang, K.; Zhou, Y., Model estimation and selection for partial linear varying coefficient EV models with longitudinal data, J. Appl. Stat., 512-534 (2023) · Zbl 07697889 |
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Weber, M.; Striaukas, J.; Schumacher, M.; Binder, H., Regularized regression when covariates are linked on a network: The 3CoSE algorithm, J. Appl. Stat., 535-554 (2023) · Zbl 07697890 |
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Xie, X.; Shi, J.; Song, K., A distributed multiple sample testing for massive data, J. Appl. Stat, 555-573 (2023) · Zbl 07697891 |
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Thielmann, A.; Weisser, C.; Krenz, A.; Säfken, B., Unsupervised document classification integrating web scraping, one-class SVM and LDA topic modelling, J. Appl. Stat, 574-591 (2023) · Zbl 07697892 |
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Fan, F.; Chu, S.-C.; Pan, J.-S.; Lin, C.; Zhao, H., An optimized machine learning technology scheme and its application in fault detection in wireless sensor networks, J. Appl. Stat., 592-609 (2023) · Zbl 07697893 |
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Zhang Wu, M.; Luo, J.; Fang, X.; Xu, M.; Zhao, P., Modeling multivariate cyber risks: Deep learning dating extreme value theory, J. Appl. Stat, 610-630 (2023) · Zbl 07697894 |
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Zhang, W.; Wu, C. O.; Ma, X.; Tian, X.; Li, Q., Analysis of multivariate longitudinal data using dynamic lasso-regularized copula models with application to large pediatric cardiovascular studies, J. Appl. Stat., 631-658 (2023) · Zbl 1518.62014 |
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Zhi, X.; Yu, T.; Bi, L.; Li, Y., Noise-insensitive discriminative subspace fuzzy clustering, J. Appl. Stat, 659-674 (2023) · Zbl 07697896 |
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Kang, I.; Park, C.; Yoon, Y. J.; Park, C.; Kwon, S.-S.; Choi, H., Classification of histogram-valued data with support histogram machines, J. Appl. Stat, 675-690 (2023) · Zbl 07697897 |
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Liu, X.; Tian, G.; Liu, Z., Identification of novel genes for triple-negative breast cancer with semiparametric gene-based analysis, J. Appl. Stat., 691-702 (2023) · Zbl 07697898 |
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Zhi, X.; Liu, J.; Wu, S.; Niu, C., A generalized l_2,p-norm regression based feature selection algorithm, J. Appl. Stat., 703-723 (2023) |
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Cheng, Y.; Li, Y.; Smith, M. L.; Li, C.; Shen, Y., Analyzing evidence-based falls prevention data with significant missing information using variable selection after multiple imputation, J. Appl. Stat., 724-743 (2023) · Zbl 07697900 |
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Zhou, M.; Yao, W., Sensitivity analysis of unmeasured confounding in causal inference based on exponential tilting and super learner, J. Appl. Stat., 744-760 (2023) · Zbl 07697901 |
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Dagdoug, M.; Goga, C.; Haziza, D., Model-assisted estimation in high-dimensional settings for survey data, J. Appl. Stat., 761-785 (2023) · Zbl 07697902 |
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Chen, S.; Xu, C., Handling high-dimensional data with missing values by modern machine learning techniques, J. Appl. Stat., 786-804 (2023) · Zbl 07697903 |
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Jin, J.; Zhang, L.; Leng, E.; Metzger, G. J.; Koopmeiners, J. S., Multi-resolution super learner for voxel-wise classification of prostate cancer using multi-parametric MRI, J. Appl. Stat., 805-826 (2023) · Zbl 07697904 |
