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ORCIDStatistics 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 - Si-Yu 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 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, T. J. Sullivan, James Buchanan, L. 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
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