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ORCIDStatistics and Computing, Volume 34
Volume 34, Number 1, February 2024
- Kin Yap Cheung, Stephen M. S. Lee:
High-dimensional local polynomial regression with variable selection and dimension reduction. 1 - Kipoong Kim, Sungkyu Jung:
Integrative sparse reduced-rank regression via orthogonal rotation for analysis of high-dimensional multi-source data. 2 - Liugen Xue:
Empirical likelihood and estimation in single-index varying-coefficient models with censored data. 3 - Xin Li, Dongya Wu:
Sparse estimation in high-dimensional linear errors-in-variables regression via a covariate relaxation method. 4 - Issam-Ali Moindjié, Sophie Dabo-Niang
, Cristian Preda:
Classification of multivariate functional data on different domains with Partial Least Squares approaches. 5 - Ines Ortega-Fernandez, Marta Sestelo, Nora M. Villanueva:
Explainable generalized additive neural networks with independent neural network training. 6 - Arjun Lakra, Buddhananda Banerjee, Arnab Kumar Laha:
A data-adaptive method for outlier detection from functional data. 7 - Jingjing Jiang, Chunjie Wang, Deng Pan, Xinyuan Song:
Transformation models with informative partly interval-censored data. 8 - Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal, Laurent Heutte:
Random forest kernel for high-dimension low sample size classification. 9 - Hsin-Hsiung Huang, Feng Yu, Xing Fan, Teng Zhang:
A framework of regularized low-rank matrix models for regression and classification. 10 - Dmytro Perepolkin, Benjamin Goodrich, Ullrika Sahlin:
Hybrid elicitation and quantile-parametrized likelihood. 11 - Michaël Allouche, Stéphane Girard, Emmanuel Gobet:
Estimation of extreme quantiles from heavy-tailed distributions with neural networks. 12 - Carlos Tadeu Pagani Zanini, Helio dos Santos Migon, Ronaldo Dias:
Variational inference for Bayesian bridge regression. 13 - Rahul Biswas, Somabha Mukherjee:
Consistent causal inference from time series with PC algorithm and its time-aware extension. 14 - Takahiro Onizuka, Shintaro Hashimoto, Shonosuke Sugasawa:
Fast and locally adaptive Bayesian quantile smoothing using calibrated variational approximations. 15 - Pedro L. Ramos, Nixon Jerez-Lillo, Francisco A. Segovia, Osafu Augustine Egbon, Francisco Louzada:
Power-law distribution in pieces: a semi-parametric approach with change point detection. 16 - Shrijita Bhattacharya, Zihuan Liu, Tapabrata Maiti:
Comprehensive study of variational Bayes classification for dense deep neural networks. 17 - Marco Alfò, Nicola Salvati, Maria Giovanna Ranalli:
Correction to: Finite mixtures of quantile and M-quantile regression models. 18 - Deepak Prajapati, Ayan Pal, Debasis Kundu:
A finite mixture model for multiple dependent competing risks with applications of automotive warranty claims data. 19 - Daniel Rudolf, Philip Schär:
Dimension-independent spectral gap of polar slice sampling. 20 - Lorenzo Zambon, Dario Azzimonti, Giorgio Corani:
Efficient probabilistic reconciliation of forecasts for real-valued and count time series. 21 - María Barroso, Carlos M. Alaíz, José L. Torrecilla, Ángela Fernández:
Functional diffusion maps. 22 - Wanwan Liang, Ben Wu, Bo Zhang:
Modeling volatility for high-frequency data with rounding error: a nonparametric Bayesian approach. 23 - Rongqian Sun, Xinyuan Song:
Bayesian tree-based heterogeneous mediation analysis with a time-to-event outcome. 24 - Luis E. Nieto-Barajas:
Multivariate and regression models for directional data based on projected Pólya trees. 25 - Aisha Fayomi, Yannis Pantazis, Michail Tsagris, Andrew T. A. Wood:
Cauchy robust principal component analysis with applications to high-dimensional data sets. 26 - Alexander Aushev, Thong Tran, Henri Pesonen, Andrew Howes, Samuel Kaski:
Likelihood-free inference in state-space models with unknown dynamics. 27 - Michael Grabchak, Xingnan Zhang:
Representation and simulation of multivariate Dickman distributions and Vervaat perpetuities. 28 - Gavin Collins, Devin Francom, Kellin N. Rumsey:
Bayesian projection pursuit regression. 29 - Jorge Loría, Anindya Bhadra:
SURE-tuned bridge regression. 30 - Daniel Schalk, Bernd Bischl, David Rügamer:
Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models. 31 - Tabea Rebafka:
Model-based clustering of multiple networks with a hierarchical algorithm. 32 - Yaman Kindap, Simon J. Godsill:
Point process simulation of generalised hyperbolic Lévy processes. 33 - Pawel Dlotko, Niklas Hellmer, Lukasz Stettner, Rafal Topolnicki:
Topology-driven goodness-of-fit tests in arbitrary dimensions. 34 - Guanhua Fang, Owen G. Ward, Tian Zheng:
Online estimation and community detection of network point processes for event streams. 35 - Yeonjoo Park, Hee-Seok Oh, Yaeji Lim:
A data-adaptive dimension reduction for functional data via penalized low-rank approximation. 36 - David Oechsler:
Lévy Langevin Monte Carlo. 37 - Rakhi Singh:
Pareto-efficient designs for multi- and mixed-level supersaturated designs. 38 - Liugen Xue:
Doubly robust estimation and robust empirical likelihood in generalized linear models with missing responses. 39 - Chunhui Liang, Wenqing Ma:
Heterogeneous analysis for clustered data using grouped finite mixture models. 40 - Weiwei Wang, Yuqiang Li, Xianyi Wu:
Off-policy evaluation for tabular reinforcement learning with synthetic trajectories. 41 - Marco Alfò, Maria Francesca Marino, Francesca Martella:
Biclustering multivariate discrete longitudinal data. 42 - Yan Chen, Shuixin Fang, Lu Lin:
Renewable composite quantile method and algorithm for nonparametric models with streaming data. 43 - Bernard W. Silverman, Lax Chan, Kyle Vincent:
Bootstrapping multiple systems estimates to account for model selection. 44 - Hanwen Xuan, Luca Maestrini, Feng Chen, Clara Grazian:
Stochastic variational inference for GARCH models. 45 - Jan Vávra, Arnost Komárek, Bettina Grün, Gertraud Malsiner-Walli:
Clusterwise multivariate regression of mixed-type panel data. 46 - Shang-Ying Shiu, Yen-Shiu Chin, Szu-Han Lin, Ting-Li Chen:
Randomized self-updating process for clustering large-scale data. 47 - Peter A. Whalley, Daniel Paulin, Benedict J. Leimkuhler:
Randomized time Riemannian Manifold Hamiltonian Monte Carlo. 48 - Laixu Shang, Qian-Zhen Zheng, Ping-Feng Xu, Na Shan, Man-Lai Tang:
A generalized expectation model selection algorithm for latent variable selection in multidimensional item response theory models. 49 - David J. Warne, Oliver J. Maclaren, Elliot J. Carr, Matthew J. Simpson, Christopher C. Drovandi:
Generalised likelihood profiles for models with intractable likelihoods. 50 - Linh H. Nghiem, Francis K. C. Hui, Samuel Müller, Alan H. Welsh:
Likelihood-based surrogate dimension reduction. 51 - Hung-Kai Pi, Meihui Guo, Ray-Bing Chen, Shih-Feng Huang:
ECOPICA: empirical copula-based independent component analysis. 52 - Marion Naveau, Guillaume Kon Kam King, Renaud Rincent, Laure Sansonnet, Maud Delattre:
Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm. 53 - Etienne David, Jean Bellot, Sylvain Le Corff, Luc Lehéricy:
Identifiability of discrete input-output hidden Markov models with external signals. 54 - Antoine Godichon-Baggioni, Stéphane Robin:
A robust model-based clustering based on the geometric median and the median covariation matrix. 55 - Yuhyeong Jang, Raanju R. Sundararajan, Wagner Barreto-Souza:
A multivariate heavy-tailed integer-valued GARCH process with EM algorithm-based inference. 56 - Noa Kallioinen, Topi Paananen, Paul-Christian Bürkner, Aki Vehtari:
Detecting and diagnosing prior and likelihood sensitivity with power-scaling. 57 - Alexandre Mösching, Lutz Dümbgen:
Estimation of a likelihood ratio ordered family of distributions. 58 - Kai Yang, Masoud Asgharian, Sahir Bhatnagar:
Accelerated gradient methods for sparse statistical learning with nonconvex penalties. 59 - Frank Nielsen, Kazuki Okamura:
On the f-divergences between densities of a multivariate location or scale family. 60 - Filippo Pagani, Augustin Chevallier, Sam Power, Thomas A. House, Simon L. Cotter:
NuZZ: Numerical Zig-Zag for general models. 61 - Luca Brusa, Fulvia Pennoni, Francesco Bartolucci:
Maximum likelihood estimation for discrete latent variable models via evolutionary algorithms. 62 - Naruesorn Prabpon, Kitakorn Homsud, Pat Vatiwutipong:
Nonparametric Bayesian online change point detection using kernel density estimation with nonparametric hazard function. 63
Volume 34, Number 2, April 2024
- Etienne Côme:
Bayesian contiguity constrained clustering. 64 - Cheng-Der Fuh, Chuan-Ju Wang:
Efficient exponential tilting with applications. 65 - Beatrice Foroni, Luca Merlo, Lea Petrella:
Expectile hidden Markov regression models for analyzing cryptocurrency returns. 66 - Chengqian Xian, Camila P. E. de Souza, Wenqing He, Felipe F. Rodrigues, Renfang Tian:
Variational Bayesian analysis of survival data using a log-logistic accelerated failure time model. 67 - Luke Mosley, Tak-Shing T. Chan, Alex J. Gibberd:
The sparse dynamic factor model: a regularised quasi-maximum likelihood approach. 68 - Shan Lu, Wenjing Wang, Rong Guan:
Kent feature embedding for classification of compositional data with zeros. 69 - Hongyu Wu, Jonathan R. Bradley:
Global-local shrinkage multivariate logit-beta priors for multiple response-type data. 70 - Carlos Echegoyen, Aritz Pérez, Guzmán Santafé, Unai Pérez-Goya, María Dolores Ugarte:
Large-scale unsupervised spatio-temporal semantic analysis of vast regions from satellite images sequences. 71 - Keith D. Levin, Brenda Betancourt:
Fast generation of exchangeable sequences of clusters data. 72 - Jose Ameijeiras-Alonso:
A reliable data-based smoothing parameter selection method for circular kernel estimation. 73 - Matheus Castro, Caio L. N. Azevedo, Juvêncio Santos Nobre:
A robust quantile regression for bounded variables based on the Kumaraswamy Rectangular distribution. 74 - Sarat Babu Moka, Benoit Liquet, Houying Zhu, Samuel Müller:
COMBSS: best subset selection via continuous optimization. 75 - Esam Mahdi:
New mixed portmanteau tests for time series models. 76 - Zehan Yang, HaiYing Wang, Jun Yan:
Subsampling approach for least squares fitting of semi-parametric accelerated failure time models to massive survival data. 77 - Ajay Jasra, Hamza M. Ruzayqat, Amin Wu:
Bayesian parameter inference for partially observed stochastic volterra equations. 78 - Yushan Xue, Jie Ren, Bin Yang:
Enmsp: an elastic-net multi-step screening procedure for high-dimensional regression. 79 - Wan Tian, Zhongfeng Qin:
The minimum covariance determinant estimator for interval-valued data. 80 - Francesco Amato, Julien Jacques, Isabelle Prim-Allaz:
Clustering longitudinal ordinal data via finite mixture of matrix-variate distributions. 81 - Nicholas Kissel, Lucas Mentch:
Forward stability and model path selection. 82 - Yannis G. Yatracos:
Do applied statisticians prefer more randomness or less? Bootstrap or Jackknife? 83 - Yuki Takazawa, Tomonari Sei:
Maximum likelihood estimation of log-concave densities on tree space. 84 - Alex Ziyu Jiang, Abel Rodriguez:
Improvements on scalable stochastic Bayesian inference methods for multivariate Hawkes process. 85 - Xin Chen, Chang Deng, Shuaida He, Runxiong Wu, Jia Zhang:
High-dimensional sparse single-index regression via Hilbert-Schmidt independence criterion. 86 - Emanuele Borgonovo, Elmar Plischke, Clémentine Prieur:
Total effects with constrained features. 87 - Thomas Lux:
Estimation of regime-switching diffusions via Fourier transforms. 88 - Ruiting Hao, Xiaorong Yang:
Multiple-output quantile regression neural network. 89 - Hanâ Lbath, Alexander Petersen, Sophie Achard:
Large-scale correlation screening under dependence for brain functional connectivity network inference. 90 - Alessandro Celani, Paolo Pagnottoni, Galin L. Jones:
Bayesian variable selection for matrix autoregressive models. 91 - Xinyu Zhang, Hongwei Shi, Niwen Zhou, Falong Tan, Xu Guo:
Quantile generalized measures of correlation. 92 - Janice L. Scealy, Kassel L. Hingee, John T. Kent, Andrew T. A. Wood:
Robust score matching for compositional data. 93 - Alessio Farcomeni, Marco Geraci:
Quantile ratio regression. 94
Volume 34, Number 3, June 2024
- Fengchuan Zhang, Sanguo Zhang, Shi-Ming Li, Mingyang Ren:
Matrix regression heterogeneity analysis. 95 - Junwen Xiao, Zishu Zhan, Jingxiao Zhang:
Doubly robust estimation of optimal treatment regimes for survival data using an instrumental variable. 96 - Ian Meneghel Danilevicz, Valderio Anselmo Reisen, Pascal Bondon:
Expectile and M-quantile regression for panel data. 97 - Faïcel Chamroukhi, Nhat Thien Pham, Van Hà Hoang, Geoffrey J. McLachlan:
Functional mixtures-of-experts. 98 - Kes Ward, Gaetano Romano, Idris A. Eckley, Paul Fearnhead:
A constant-per-iteration likelihood ratio test for online changepoint detection for exponential family models. 99 - David Rodríguez-Vítores, Carlos Matrán:
Improving model choice in classification: an approach based on clustering of covariance matrices. 100 - Jasmin Rühl, Sarah Friedrich:
Resampling-based confidence intervals and bands for the average treatment effect in observational studies with competing risks. 101 - Jungmin Shin, Seunghyun Gwak, Seung Jun Shin, Sungwan Bang:
Simultaneous estimation and variable selection for a non-crossing multiple quantile regression using deep neural networks. 102 - Abdelaati Daouia, Gilles Stupfler, Antoine Usseglio-Carleve:
An expectile computation cookbook. 103 - Sarah Leyder, Jakob Raymaekers, Tim Verdonck:
Generalized spherical principal component analysis. 104 - Youwu Lin, Xin Zeng, Pei Wang, Shuai Huang, Kok Lay Teo:
Variable selection using axis-aligned random projections for partial least-squares regression. 105 - Seungwoo Kang, Hee-Seok Oh:
Novel sampling method for the von Mises-Fisher distribution. 106 - Chen Ouyang, Chenkaixiang Lu, Xiong Zhao, Ruping Huang, Gonglin Yuan, Yiyan Jiang:
Stochastic three-term conjugate gradient method with variance technique for non-convex learning. 107 - Carlo Cavicchia, Maurizio Vichi, Giorgia Zaccaria:
Parsimonious ultrametric Gaussian mixture models. 108 - Jonathan James:
Automated generation of initial points for adaptive rejection sampling of log-concave distributions. 109 - Bao Anh Vu, David Gunawan, Andrew Zammit-Mangion:
R-VGAL: a sequential variational Bayes algorithm for generalised linear mixed models. 110 - Frank Rotiroti, Stephen G. Walker:
Reversed particle filtering for hidden markov models. 111 - Xuejun Jiang, Yakun Liang, Haofeng Wang:
Screen then select: a strategy for correlated predictors in high-dimensional quantile regression. 112 - Marion Naveau, Guillaume Kon Kam King, Renaud Rincent, Laure Sansonnet, Maud Delattre:
Correction to: Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm. 113 - Ilaria Bombelli, Maurizio Vichi:
Parsimonious consensus hierarchies, partitions and fuzzy partitioning of a set of hierarchies. 114 - Ziyang Yang, Idris A. Eckley, Paul Fearnhead:
A communication-efficient, online changepoint detection method for monitoring distributed sensor networks. 115 - Joaquín Martínez-Minaya, Haavard Rue:
A flexible Bayesian tool for CoDa mixed models: logistic-normal distribution with Dirichlet covariance. 116 - Dongrak Choi, Woojung Bae, Jun Yan, Sangwook Kang:
A general model-checking procedure for semiparametric accelerated failure time models. 117 - Yu-Chien Bo Ning, Ning Ning:
Spike and slab Bayesian sparse principal component analysis. 118
Volume 34, Number 4, August 2024
- Alex Cooper, Aki Vehtari, Catherine Forbes, Daniel Simpson, Lauren Kennedy:
Bayesian cross-validation by parallel Markov chain Monte Carlo. 119 - Vladimir Pastukhov:
Fused lasso nearly-isotonic signal approximation in general dimensions. 120