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ORCIDStatistical Analysis and Data Mining, Volume 17
Volume 17, Number 1, February 2024
RESEARCH ARTICLES
- Zhan Liu, Xuesong Chen, Ruohan Li, Lanbao Hou
:
Bayesian inference for nonprobability samples with nonignorable missingness. - Ziwen Geng:
A novel two-step extrapolation-insertion risk model based on the Expectile under the Pareto-type distribution. - Michael P. B. Gallaugher, Xuwen Zhu:
Modeling matrix variate time series via hidden Markov models with skewed emissions. - Zahra Nouri, Vahid Kiani, Hamid Fadishei:
Rarity updated ensemble with oversampling: An ensemble approach to classification of imbalanced data streams. - Florian Combes, Ricardo Fraiman, Badih Ghattas:
Subsampling under distributional constraints. - Juhyeon Kim, Soyoung Park, Alicia L. Carriquiry:
A deep learning approach for the comparison of handwritten documents using latent feature vectors. - Zhuanzhuan Ma, Zifei Han, Souparno Ghosh, Liucang Wu, Min Wang:
Sparse Bayesian variable selection in high-dimensional logistic regression models with correlated priors. - Hana Lee, Alicia L. Carriquiry, Soyoung Park:
An automated alignment algorithm for identification of the source of footwear impressions with common class characteristics. - Jinwen Liang, Maozai Tian:
Imputed quantile vector autoregressive model for multivariate spatial-temporal data. - Wenyu Gao, Inyoung Kim, Wonil Nam, Xiang Ren, Wei Zhou, Masoud Agah:
Nonparametric Bayesian functional clustering with applications to racial disparities in breast cancer. - Laila A. Al-Essa, Shakaiba Shafiq, Deniz Ozonur, Farrukh Jamal:
Study of a bounded interval perks distribution with quantile regression analysis. - Seungha Um, Samrachana Adhikari:
Considerations in Bayesian agent-based modeling for the analysis of COVID-19 data. - Mathias Bourel, Jairo Cugliari, Yannig Goude, Jean-Michel Poggi:
Boosting diversity in regression ensembles. - Niu Xiaoyu, Yuzhu Tian, Man-Lai Tang, Maozai Tian:
Multivariate contaminated normal mixture regression modeling of longitudinal data based on joint mean-covariance model. - Lucas Koepke, Mary Gregg, Michael Frey:
A machine learning oracle for parameter estimation. - Luca Bagnato, Alessio Farcomeni, Antonio Punzo:
The generalized hyperbolic family and automatic model selection through the multiple-choice LASSO. - Andrew Simpson, Semhar Michael, Dylan Borchert, Christopher Saunders, Larry Tang:
Modeling subpopulations for hierarchically structured data. - Junsub Jung, Sungil Kim, Heeyoung Kim:
Spatially-correlated time series clustering using location-dependent Dirichlet process mixture model. - Xiankui Yang, Lu Lu, Christine M. Anderson-Cook:
Input-response space-filling designs incorporating response uncertainty. - Scott A. Vander Wiel, Michael J. Grosskopf, Isaac J. Michaud, Denise Neudecker:
Driving mode analysis - How uncertain functional inputs propagate to an output. - Eric A. E. Gerber, Bruce A. Craig:
Residuals and diagnostics for multinomial regression models. - Maximilian Autenrieth, David A. Van Dyk, Roberto Trotta, David C. Stenning:
Stratified learning: A general-purpose statistical method for improved learning under covariate shift. - Maoyu Zhang, Wenlin Dai:
On difference-based gradient estimation in nonparametric regression.
Volume 17, Number 2, April 2024
RESEARCH ARTICLES
- Sean Xinyang Feng, Aya A. Mitani:
Marginal clustered multistate models for longitudinal progressive processes with informative cluster size. - Arkaprabha Ganguli, Tapabrata Maiti, David Todem:
Error-controlled feature selection for ultrahigh-dimensional and highly correlated feature space using deep learning. - Yujie Gai, Kang Meng, Xiaodi Wang:
Online learning for streaming data classification in nonstationary environments. - Raydonal Ospina, Ranah Duarte Costa, Leandro Chaves Rêgo, Fernando Marmolejo-Ramos:
Application of nonparametric quantifiers for online handwritten signature verification: A statistical learning approach. - Xiaojun Zheng, Simon Mak, Liyan Xie, Yao Xie:
eRPCA: Robust Principal Component Analysis for Exponential Family Distributions. - Kevin R. Quinlan, Jagadeesh Movva, Brad Perfect:
Non-uniform active learning for Gaussian process models with applications to trajectory informed aerodynamic databases. - Yuhao Zhang, Lu Tang, Yuxiao Huang, Yan Ma:
Smart data augmentation: One equation is all you need. - Marilena Furno, Francesco Caracciolo:
The finite mixture model for the tails of distribution: Monte Carlo experiment and empirical applications. - Runze Li, Jin Mu, Songshan Yang, Cong Ye, Xiang Zhan:
Compositional variable selection in quantile regression for microbiome data with false discovery rate control. - Aleksandar Tomcic, Milos Savic, Milos Radovanovic:
Hub-aware random walk graph embedding methods for classification. - Isaac J. Michaud, Michael Grosskopf, Jesson Hutchinson, Scott A. Vander Wiel:
Expert-in-the-loop design of integral nuclear data experiments. - Hao Xue, Sounak Chakraborty, Tanujit Dey:
Bayesian shrinkage models for integration and analysis of multiplatform high-dimensional genomics data. - Zhigen Zhao, Tong Wang, Bo Ji:
Randomized multiarm bandits: An improved adaptive data collection method. - Eugene Laska, Ziqiang Lin, Carole Siegel, Charles Marmar:
A treeless absolutely random forest with closed-form estimators of expected proximities. - Hina Shaheen, Roderick Melnik, Sundeep Singh, Alzheimer's Disease Neuroimaging Initiative:
Data-driven stochastic model for quantifying the interplay between amyloid-beta and calcium levels in Alzheimer's disease. - Mengqi Xie, Tao Hu, Jie Zhou:
Transfer learning under the Cox model with interval-censored data. - Yuzhu Tian, Chun-Ho Wu, Ling-Nan Tai, Zhibao Mian, Maozai Tian:
Bayesian relative composite quantile regression approach of ordinal latent regression model with L1/2 regularization.
Volume 17, Number 3, June 2024
RESEARCH ARTICLES
- Sanyou Wu, Fuying Wang, Long Feng:
Individualized image region detection with total variation. - Ron S. Kenett, Chris Gotwalt:
The analysis of association rules: Latent class analysis.
Volume 17, Number 4, August 2024
RESEARCH ARTICLES
- Xiaoyi Wen:
Two-sample testing for random graphs.
Volume 17, Number 5, October 2024
Research Article
- Max Sampson, Kung-Sik Chan:
Conformal Multi-Target Hyperrectangles. - Christopher Qian, Tyler Ganter, Joshua Michalenko, Feng Liang, Jason Adams:
Quantifying Epistemic Uncertainty in Binary Classification via Accuracy Gain. - Zengyou He, Jun Lou, Yan Liu, Lianyu Hu, Mudi Jiang:
Node Centrality Inference via Hypothesis Testing. - Yanran Wei, William Myers, Xinwei Deng:
An Efficient Filtering Approach for Model Estimation in Sparse Regression.
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