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Statistics and Computing, Volume 33
Volume 33, Number 1, February 2023
- Zheyuan Li, Jiguo Cao:
Automatic search intervals for the smoothing parameter in penalized splines. 1 - Rico Krueger, Michel Bierlaire, Thomas Gasos, Prateek Bansal:
Robust discrete choice models with t-distributed kernel errors. 2 - Francisco Vargas, Andrius Ovsianas, David Fernandes, Mark Girolami, Neil D. Lawrence, Nikolas Nüsken:
Bayesian learning via neural Schrödinger-Föllmer flows. 3 - Michael Grabchak, Piergiacomo Sabino:
Efficient simulation of p-tempered α-stable OU processes. 4 - Marco Capó, Aritz Pérez, José Antonio Lozano:
LASSO for streaming data with adaptative filtering. 5 - Angelos Alexopoulos, Petros Dellaportas, Michalis K. Titsias:
Variance reduction for Metropolis-Hastings samplers. 6 - Alan R. Vazquez, Weng Kee Wong, Peter Goos:
Constructing two-level QB-optimal screening designs using mixed-integer programming and heuristic algorithms. 7 - Joris Bierkens, Sebastiano Grazzi, Frank van der Meulen, Moritz Schauer:
Sticky PDMP samplers for sparse and local inference problems. 8 - Siyu Yi, Yong-Dao Zhou:
Model-free global likelihood subsampling for massive data. 9 - Nha Vo-Thanh, Hans-Peter Piepho:
Bayesian A-optimal two-phase designs with a single blocking factor in each phase. 10 - Anna L. Smith, Tian Zheng, Andrew Gelman:
Prediction scoring of data-driven discoveries for reproducible research. 11 - Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander:
Stochastic cluster embedding. 12 - Shufei Ge, Shijia Wang, Lloyd T. Elliott:
Shape modeling with spline partitions. 13 - Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang:
Sparse logistic functional principal component analysis for binary data. 15 - Lukas Cironis, Jan Palczewski, Georgios Aivaliotis:
Automatic model training under restrictive time constraints. 16 - Gabriel Riutort-Mayol, Paul-Christian Bürkner, Michael Riis Andersen, Arno Solin, Aki Vehtari:
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming. 17 - Vojtech Kejzlar, Tapabrata Maiti:
Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration. 18 - Mohamed Maama, Ajay Jasra, Hernando C. Ombao:
Bayesian parameter inference for partially observed stochastic differential equations driven by fractional Brownian motion. 19 - Nikolai Spuck, Matthias Schmid, Nils Heim, Ute Klarmann-Schulz, Achim Hörauf, Moritz Berger:
Flexible tree-structured regression models for discrete event times. 20 - Victor Freguglia, Nancy Lopes Garcia:
Detecting renewal states in chains of variable length via intrinsic Bayes factors. 21 - Andrew M. Raim:
Direct sampling with a step function. 22 - Kamran Pentland, Massimiliano Tamborrino, Timothy John Sullivan, James Buchanan, Lynton C. Appel:
GParareal: a time-parallel ODE solver using Gaussian process emulation. 23 - Lucas Kock, Nadja Klein, David J. Nott:
Correction to : Variational inference and sparsity in high-dimensional deep Gaussian mixture models. 24 - Lisa Gaedke-Merzhäuser, Janet van Niekerk, Olaf Schenk, Håvard Rue:
Parallelized integrated nested Laplace approximations for fast Bayesian inference. 25 - Pekka Korhonen, Francis K. C. Hui, Jenni Niku, Sara Taskinen:
Fast and universal estimation of latent variable models using extended variational approximations. 26 - Yeonjoo Lee, Natalia Rojas-Perilla, Marina Runge, Timo Schmid:
Variable selection using conditional AIC for linear mixed models with data-driven transformations. 27 - Thomas Rusch, Patrick Mair, Kurt Hornik:
Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling. 28 - Arnaud Poinas, Rémi Bardenet:
On proportional volume sampling for experimental design in general spaces. 29 - Junyi Zhang, Angelos Dassios:
Truncated Poisson-Dirichlet approximation for Dirichlet process hierarchical models. 30 - Hiroshi Yamashita, Hideyuki Suzuki, Kazuyuki Aihara:
Entropic herding. 31 - Katherine A. L. Valeriano, Christian E. Galarza, Larissa A. Matos:
Moments and random number generation for the truncated elliptical family of distributions. 32 - Atlanta Chakraborty, David J. Nott, Christopher C. Drovandi, David T. Frazier, Scott A. Sisson:
Modularized Bayesian analyses and cutting feedback in likelihood-free inference. 33 - Daniel Ahfock, William J. Astle, Sylvia Richardson:
On randomized sketching algorithms and the Tracy-Widom law. 34 - Bradley Wakefield, Yan-Xia Lin, Rathindra Sarathy, Krishnamurty Muralidhar:
Moment-based density estimation of confidential micro-data: a computational statistics approach. 35
Volume 33, Number 2, April 2023
- Belén Pulido, Alba M. Franco Pereira, Rosa E. Lillo:
A fast epigraph and hypograph-based approach for clustering functional data. 36 - David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn:
Probabilistic time series forecasts with autoregressive transformation models. 37 - Li-Pang Chen:
De-noising boosting methods for variable selection and estimation subject to error-prone variables. 38 - Shouto Yonekura, Shonosuke Sugasawa:
Adaptation of the tuning parameter in general Bayesian inference with robust divergence. 39 - Eya Ben Amar, Nadhir Ben Rached, Abdul-Lateef Haji-Ali, Raúl Tempone:
State-dependent importance sampling for estimating expectations of functionals of sums of independent random variables. 40 - Clément Duhamel, Céline Helbert, Miguel Munoz Zuniga, Clémentine Prieur, Delphine Sinoquet:
A SUR version of the Bichon criterion for excursion set estimation. 41 - Marko Järvenpää, Jukka Corander:
On predictive inference for intractable models via approximate Bayesian computation. 42 - Huibin Weng, Olivier Parent:
Beyond homophilic dyadic interactions: the impact of network formation on individual outcomes. 43 - Ionut Paun, Dirk Husmeier, Colin J. Torney:
Stochastic variational inference for scalable non-stationary Gaussian process regression. 44 - Zhuang Yang, Li Ma:
Adaptive step size rules for stochastic optimization in large-scale learning. 45 - Gery Geenens, Alicia Nieto-Reyes, Giacomo Francisci:
Statistical depth in abstract metric spaces. 46 - Ensiyeh Nezakati, Eugen Pircalabelu:
Unbalanced distributed estimation and inference for the precision matrix in Gaussian graphical models. 47 - Christopher Geoga, Oana Marin, Michel Schanen, Michael L. Stein:
Fitting Matérn smoothness parameters using automatic differentiation. 48 - Mateusz B. Majka, Marc Sabate Vidales, Lukasz Szpruch:
Multi-index antithetic stochastic gradient algorithm. 49 - Iván Gutiérrez, Luis Gutiérrez, Danilo Alvares:
A new flexible Bayesian hypothesis test for multivariate data. 50 - João Victor B. de Freitas, Caio L. N. Azevedo, Juvêncio S. Nobre:
A stochastic approximation ECME algorithm to semi-parametric scale mixtures of centred skew normal regression models. 51 - Al-Fahad M. Al-Qadhi, Carey E. Priebe, Hayden S. Helm, Vince Lyzinski:
Subgraph nomination: query by example subgraph retrieval in networks. 52 - Philipp Sterzinger, Ioannis Kosmidis:
Maximum softly-penalized likelihood for mixed effects logistic regression. 53 - Zaida C. Quiroz, Marcos Oliveira Prates, Dipak K. Dey, Håvard Rue:
Fast Bayesian inference of block Nearest Neighbor Gaussian models for large data. 54 - Edoardo Redivo, Cinzia Viroli, Alessio Farcomeni:
Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers. 55
Volume 33, Number 3, June 2023
- Myeongjong Kang, Matthias Katzfuss:
Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference. 56 - Xiaoxiao Zhou, Xinyuan Song:
Functional concurrent hidden Markov model. 57 - Chiheb Ben Hammouda, Nadhir Ben Rached, Raúl Tempone, Sophia Wiechert:
Learning-based importance sampling via stochastic optimal control for stochastic reaction networks. 58 - Chien-Yu Peng, Yi-Shian Dong, Tsai-Hung Fan:
The first-passage-time moments for the Hougaard process and its Birnbaum-Saunders approximation. 59 - Filippo Antonazzo, Christophe Biernacki, Christine Keribin:
Frugal Gaussian clustering of huge imbalanced datasets through a bin-marginal approach. 60 - Diala Hawat, Guillaume Gautier, Rémi Bardenet, Raphaël Lachièze-Rey:
On estimating the structure factor of a point process, with applications to hyperuniformity. 61 - Xin Liang:
On the optimality of the Oja's algorithm for online PCA. 62 - Håkon Gryvill, Håkon Tjelmeland:
A sparse matrix formulation of model-based ensemble Kalman filter. 63 - Marno Basson, Tobias M. Louw, Theresa R. Smith:
Variational Tobit Gaussian Process Regression. 64 - Gersende Fort, Eric Moulines:
Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization. 65 - Jeremie Coullon, Leah F. South, Christopher Nemeth:
Efficient and generalizable tuning strategies for stochastic gradient MCMC. 66 - Min Xu, Zhongfeng Qin:
A Bayesian parametrized method for interval-valued regression models. 67 - Maolin Pan, Minggao Gu, Xianyi Wu, Xiaodan Fan:
Globally and symmetrically identified Bayesian multinomial probit model. 68 - Enes Makalic, Daniel F. Schmidt:
Maximum likelihood estimation of the Weibull distribution with reduced bias. 69 - Marc Lambert, Silvère Bonnabel, Francis R. Bach:
The limited-memory recursive variational Gaussian approximation (L-RVGA). 70 - Meadhbh O'Neill, Kevin Burke:
Variable selection using a smooth information criterion for distributional regression models. 71 - Yujia Ding, Qidi Peng, Zhengming Song, Hansen Chen:
Variable selection and regularization via arbitrary rectangle-range generalized elastic net. 72 - Kangning Wang, Shaomin Li:
Distributed statistical optimization for non-randomly stored big data with application to penalized learning. 73 - Yiming Liu, Shaochen Wang, Wang Zhou:
General Jackknife empirical likelihood and its applications. 74
Volume 33, Number 4, August 2023
- Il-Suk Kang, Hosik Choi, Young Joo Yoon, Junyoung Park, Soon-Sun Kwon, Cheolwoo Park:
Fréchet distance-based cluster analysis for multi-dimensional functional data. 75 - Vaidehi Dixit, Ryan Martin:
A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions. 76 - Alessandro Mastrototaro, Jimmy Olsson:
Adaptive online variance estimation in particle filters: the ALVar estimator. 77 - Chen Huang, Jieli Ding, Yanqin Feng:
A quadratic upper bound algorithm for regression analysis of credit risk under the proportional hazards model with case-cohort data. 78 - Xiaodong Yang, Jun S. Liu:
Convergence rate of multiple-try Metropolis independent sampler. 79 - Ben Bettisworth, Alexander I. Jordan, Alexandros Stamatakis:
Phylourny: efficiently calculating elimination tournament win probabilities via phylogenetic methods. 80 - Pete Philipson, Alan Huang:
A fast look-up method for Bayesian mean-parameterised Conway-Maxwell-Poisson regression models. 81 - Imke Botha, Robert Kohn, Leah F. South, Christopher C. Drovandi:
Automatically adapting the number of state particles in SMC2. 82 - Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson:
A similarity-based Bayesian mixture-of-experts model. 83 - Paul G. Beckman, Christopher Geoga, Michael L. Stein, Mihai Anitescu:
Scalable computations for nonstationary Gaussian processes. 84 - Armin Eftekhari, Luis Vargas, Konstantinos C. Zygalakis:
The forward-backward envelope for sampling with the overdamped Langevin algorithm. 85 - Haixiang Zhang, Xin Li:
A framework for mediation analysis with massive data. 86 - Efstratios Palias, Ata Kabán:
The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification. 87 - Zishu Zhan, Xiangjie Li, Jingxiao Zhang:
Partial replacement imputation estimation for partially linear models with complex missing pattern covariates. 88 - Shiwei Lan, Shuyi Li, Mirjeta Pasha:
Bayesian spatiotemporal modeling for inverse problems. 89 - Sijing Li, Cheng Zhang, Zhiwen Zhang, Hongkai Zhao:
A data-driven and model-based accelerated Hamiltonian Monte Carlo method for Bayesian elliptic inverse problems. 90 - Anna Bonnet, Miguel Martinez Herrera, Maxime Sangnier:
Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity. 91
Volume 33, Number 5, October 2023
- Walter R. Gilks, Lukas Cironis, Stuart Barber:
Wavelet Monte Carlo: a principle for sampling from complex distributions. 92 - Robin Richter, Shankar Bhamidi, Sach Mukherjee:
Improved baselines for causal structure learning on interventional data. 93 - Andreas Anastasiou, Angelos Papanastasiou:
Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences. 94 - Rémi Boutin, Charles Bouveyron, Pierre Latouche:
Embedded topics in the stochastic block model. 95 - Ruiqi Liu, Ganggang Xu, Zuofeng Shang:
Distributed adaptive nearest neighbor classifier: algorithm and theory. 96 - Xinzhu Liang, Shangda Yang, Simon L. Cotter, Kody J. H. Law:
A randomized multi-index sequential Monte Carlo method. 97 - Marta Crispino, Cristina Mollica, Valerio Astuti, Luca Tardella:
Efficient and accurate inference for mixtures of Mallows models with Spearman distance. 98 - Maicon J. Karling, Marc G. Genton, Simos G. Meintanis:
Goodness-of-fit tests for multivariate skewed distributions based on the characteristic function. 99 - Jessica E. Forsyth, Ali H. Al-Anbaki, Berenika Plusa, Simon L. Cotter:
Unlabelled landmark matching via Bayesian data selection, and application to cell matching across imaging modalities. 100 - Xinmin Li, Haozhe Liang, Wolfgang K. Härdle, Hua Liang:
Use generalized linear models or generalized partially linear models? 101 - Yanxin Li, Antonio Linero, Stephen G. Walker:
Latent uniform samplers on multivariate binary spaces. 102 - Julien Demange-Chryst, François Bachoc, Jérôme Morio:
Efficient estimation of multiple expectations with the same sample by adaptive importance sampling and control variates. 103 - Gonzalo Vicente, Aritz Adin, Tomás Goicoa, María Dolores Ugarte:
High-dimensional order-free multivariate spatial disease mapping. 104 - Jason Hou-Liu, Ryan P. Browne:
Generalized linear models for massive data via doubly-sketching. 105 - Michail Tsagris, Abdulaziz Alenazi, Connie Stewart:
Flexible non-parametric regression models for compositional response data with zeros. 106 - Eduardo García-Portugués, Arturo Prieto-Tirado:
Toroidal PCA via density ridges. 107 - Henry A. Palasciano, Guy P. Nason:
A test for the absence of aliasing or white noise in two-dimensional locally stationary wavelet processes. 108 - Tomás Mrkvicka, Mari Myllymäki:
False discovery rate envelopes. 109 - Dean A. Bodenham, Yoshinobu Kawahara:
euMMD: efficiently computing the MMD two-sample test statistic for univariate data. 110 - Mary Llewellyn, Ruth King, Víctor Elvira, Gordon Ross:
A point mass proposal method for Bayesian state-space model fitting. 111 - Samuel I. Watson, Yi Pan:
Evaluation of combinatorial optimisation algorithms for c-optimal experimental designs with correlated observations. 112 - Yan Li, Na Han, Yuxiang Qin, Jing Zhang, Jinxia Su:
Trans-cGAN: transformer-Unet-based generative adversarial networks for cross-modality magnetic resonance image synthesis. 113 - Yao Shi, Wanchunzi Yu, John Stufken:
Optimal designs for generalized linear mixed models based on the penalized quasi-likelihood method. 114 - Danilo Alvares, Valeria Leiva-Yamaguchi:
A two-stage approach for Bayesian joint models: reducing complexity while maintaining accuracy. 115 - Ibrahim Merad, Stéphane Gaïffas:
Robust supervised learning with coordinate gradient descent. 116 - Jiahui Zou, Chaoxia Yuan, Xinyu Zhang, Guohua Zou, Alan T. K. Wan:
Model averaging for support vector classifier by cross-validation. 117 - Sidi Wu, Cédric Beaulac, Jiguo Cao:
Neural networks for scalar input and functional output. 118 - Theodore Papamarkou:
Approximate blocked Gibbs sampling for Bayesian neural networks. 119 - Frédéric Lavancier, Ege Rubak:
On simulation of continuous determinantal point processes. 120