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Statistics and Computing, Volume 31
Volume 31, Number 1, January 2021
- Josef Dick, Takashi Goda, Hiroya Murata:
Toeplitz Monte Carlo. 1 - Jian Cao, Marc G. Genton, David E. Keyes, George M. Turkiyyah:
Exploiting low-rank covariance structures for computing high-dimensional normal and Student-t probabilities. 2 - Javier Juan-Albarracín, Elies Fuster-García, Alfons Juan, Juan M. García-Gómez:
Non-local spatially varying finite mixture models for image segmentation. 3 - Andrew J. Holbrook, Charles E. Loeffler, Seth R. Flaxman, Marc A. Suchard:
Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data. 4 - Shengwei Hu, Yong Wang:
Modal Clustering Using Semiparametric Mixtures and Mode Flattening. 5 - Kitty Yuen Yi Wan, Jim E. Griffin:
An adaptive MCMC method for Bayesian variable selection in logistic and accelerated failure time regression models. 6 - Guillaume Gautier, Rémi Bardenet, Michal Valko:
Fast sampling from β-ensembles. 7 - Yariv Aizenbud, Boris Landa, Yoel Shkolnisky:
Rank-one multi-reference factor analysis. 8 - Zhiyan Ding, Qin Li:
Ensemble Kalman inversion: mean-field limit and convergence analysis. 9 - Wendy K. Tam Cho, Yan Y. Liu:
A parallel evolutionary multiple-try metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions. 10 - William H. Aeberhard, Eva Cantoni, Giampiero Marra, Rosalba Radice:
Robust fitting for generalized additive models for location, scale and shape. 11
Volume 31, Number 2, February 2021
- Ömer Deniz Akyildiz, Joaquín Míguez:
Convergence rates for optimised adaptive importance samplers. 12 - Marco Stefanucci, Antonio Canale:
Multiscale stick-breaking mixture models. 13 - Mark J. Meyer, Elizabeth J. Malloy, Brent A. Coull:
Bayesian wavelet-packet historical functional linear models. 14 - Rico Blaser, Piotr Fryzlewicz:
Regularizing axis-aligned ensembles via data rotations that favor simpler learners. 15 - Topi Paananen, Juho Piironen, Paul-Christian Bürkner, Aki Vehtari:
Implicitly adaptive importance sampling. 16 - Gerhard Tutz, Moritz Berger:
Tree-structured scale effects in binary and ordinal regression. 17 - Rebecca E. Wilson, Idris A. Eckley, Matthew A. Nunes, Timothy Park:
A wavelet-based approach for imputation in nonstationary multivariate time series. 18
Volume 31, Number 3, April 2021
- Shane T. Barratt, Guillermo Angeris, Stephen P. Boyd:
Optimal representative sample weighting. 19 - Estevão B. Prado, Rafael A. Moral, Andrew C. Parnell:
Bayesian additive regression trees with model trees. 20 - Ajay Jasra, Kody J. H. Law, Deng Lu:
Unbiased estimation of the gradient of the log-likelihood in inverse problems. 21 - Cinzia Viroli, Laura Anderlucci:
Deep mixtures of unigrams for uncovering topics in textual data. 22 - Filip Tronarp, Simo Särkkä, Philipp Hennig:
Bayesian ODE solvers: the maximum a posteriori estimate. 23 - Santeri Karppinen, Matti Vihola:
Conditional particle filters with diffuse initial distributions. 24 - Joseph Guinness:
Gaussian process learning via Fisher scoring of Vecchia's approximation. 25 - Tom Stindl, Feng Chen:
Accelerating the estimation of renewal Hawkes self-exciting point processes. 26 - Christian Agrell, Kristina Rognlien Dahl:
Sequential Bayesian optimal experimental design for structural reliability analysis. 27 - Jeremie Coullon, Robert J. Webber:
Ensemble sampler for infinite-dimensional inverse problems. 28 - Valentin De Bortoli, Alain Durmus, Marcelo Pereyra, Ana Fernandez Vidal:
Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. 29 - Gavin Ridley, Benoit Forget:
A simple method for rejection sampling efficiency improvement on SIMT architectures. 30 - Mohammad W. Hattab, David Ruppert:
A mixed model approach to measurement error in semiparametric regression. 31 - Séverine Affeldt, Lazhar Labiod, Mohamed Nadif:
Regularized bi-directional co-clustering. 32 - D. Austin Cole, Ryan B. Christianson, Robert B. Gramacy:
Locally induced Gaussian processes for large-scale simulation experiments. 33 - Yiwei Wang, Jiuhai Chen, Chun Liu, Lulu Kang:
Particle-based energetic variational inference. 34 - Georg Hahn, Sharon Marie Lutz, Nilanjana Laha, Michael H. Cho, Edwin K. Silverman, Christoph Lange:
A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD). 35 - Gernot Müller, Sebastian Uhl:
Estimation of time-varying autoregressive stochastic volatility models with stable innovations. 36 - Joris Bierkens, Sebastiano Grazzi, Frank van der Meulen, Moritz Schauer:
A piecewise deterministic Monte Carlo method for diffusion bridges. 37
Volume 31, Number 4, July 2021
- Samuel M. Fischer, Mark A. Lewis:
A robust and efficient algorithm to find profile likelihood confidence intervals. 38 - Jonas Latz:
Analysis of stochastic gradient descent in continuous time. 39 - Yici Chen, Ken'ichiro Tanaka:
Maximum likelihood estimation of the Fisher-Bingham distribution via efficient calculation of its normalizing constant. 40 - Diederik S. Laman Trip, Wessel N. van Wieringen:
A parallel algorithm for ridge-penalized estimation of the multivariate exponential family from data of mixed types. 41 - Francesco Denti, Andrea Cappozzo, Francesca Greselin:
A two-stage Bayesian semiparametric model for novelty detection with robust prior information. 42 - Xiong Lyu, Mickaël Binois, Michael Ludkovski:
Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation. 43 - Nicolas Jouvin, Charles Bouveyron, Pierre Latouche:
A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering. 44 - Belmiro P. M. Duarte, Anthony C. Atkinson, Nuno M. C. Oliveira:
Optimal experimental design for linear time invariant state-space models. 45 - Feng Zhou, Simon Luo, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen:
Efficient EM-variational inference for nonparametric Hawkes process. 46 - Augusto Fasano, Giovanni Rebaudo, Daniele Durante, Sonia Petrone:
A closed-form filter for binary time series. 47 - Gersende Fort, P. Gach, Eric Moulines:
Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence. 48 - Vojtech Kejzlar, Mookyong Son, Shrijita Bhattacharya, Tapabrata Maiti:
A fast and calibrated computer model emulator: an empirical Bayes approach. 49 - Rémi Leluc, François Portier, Johan Segers:
Control variate selection for Monte Carlo integration. 50 - Duncan Lee, Kitty Meeks, William Pettersson:
Improved inference for areal unit count data using graph-based optimisation. 51
Volume 31, Number 5, September 2021
- Linna Wang, Yichen Qin, Yang Li:
Confidence graphs for graphical model selection. 52 - Thomas Maullin-Sapey, Thomas E. Nichols:
Fisher Scoring for crossed factor linear mixed models. 53 - Satya Prakash Singh, Siuli Mukhopadhyay, Harsh Raj:
Min-max crossover designs for two treatments binary and poisson crossover trials. 54 - Junyang Wang, Jon Cockayne, Oksana A. Chkrebtii, Timothy John Sullivan, Chris J. Oates:
Bayesian numerical methods for nonlinear partial differential equations. 55 - Vladimir Fanaskov:
Uncertainty calibration for probabilistic projection methods. 56 - Yu Luo, David A. Stephens:
Bayesian inference for continuous-time hidden Markov models with an unknown number of states. 57 - Daniel Ahfock, Saumyadipta Pyne, Geoffrey J. McLachlan:
Data fusion using factor analysis and low-rank matrix completion. 58 - Jeremie Houssineau, Jiajie Zeng, Ajay Jasra:
Uncertainty modelling and computational aspects of data association. 59 - Dragos Iustin Palade, Madalina Vlad:
Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport. 60 - Minas Karamanis, Florian Beutler:
Ensemble slice sampling. 61 - Joshua J. Bon, Anthony Lee, Christopher C. Drovandi:
Accelerating sequential Monte Carlo with surrogate likelihoods. 62 - Fadhel Ayed, François Caron:
Nonnegative Bayesian nonparametric factor models with completely random measures. 63 - Renzo Caballero, Ahmed Kebaier, Marco Scavino, Raúl Tempone:
Quantifying uncertainty with a derivative tracking SDE model and application to wind power forecast data. 64 - Selin Damla Ahipasaoglu:
A branch-and-bound algorithm for the exact optimal experimental design problem. 65 - Joachim Schreurs, Iwein Vranckx, Mia Hubert, Johan A. K. Suykens, Peter J. Rousseeuw:
Outlier detection in non-elliptical data by kernel MRCD. 66 - Jonas Latz, Juan P. Madrigal-Cianci, Fabio Nobile, Raúl Tempone:
Generalized parallel tempering on Bayesian inverse problems. 67 - Jacob Vorstrup Goldman, Sumeetpal S. Singh:
Spatiotemporal blocking of the bouncy particle sampler for efficient inference in state-space models. 68
Volume 31, Number 6, November 2021
- Jeong-Eun (Kate) Lee, Geoff K. Nicholls:
Tree based credible set estimation. 69 - Radoslav Harman, Lenka Filová, Samuel Rosa:
Optimal design of multifactor experiments via grid exploration. 70 - John Moriarty, Jure Vogrinc, Alessandro Zocca:
A Metropolis-class sampler for targets with non-convex support. 72 - Kimmo Suotsalo, Yingying Xu, Jukka Corander, Johan Pensar:
High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood. 73 - Alix Marie d'Avigneau, Sumeetpal S. Singh, Lawrence M. Murray:
Anytime parallel tempering. 74 - Zheng Zhao, Muhammad F. Emzir, Simo Särkkä:
Deep state-space Gaussian processes. 75 - Alec Koppel, Hrusikesha Pradhan, Ketan Rajawat:
Consistent online Gaussian process regression without the sample complexity bottleneck. 76 - Xuan Dang, Shuai Huang, Xiaoning Qian:
Penalized Cox's proportional hazards model for high-dimensional survival data with grouped predictors. 77 - Yinan Mao, Xueou Wang, David J. Nott, Michael Evans:
Detecting conflicting summary statistics in likelihood-free inference. 78 - Nadhir Ben Rached, Abdul-Lateef Haji-Ali, Gerardo Rubino, Raúl Tempone:
Efficient importance sampling for large sums of independent and identically distributed random variables. 79 - Chaofan Huang, V. Roshan Joseph, Douglas M. Ray:
Constrained minimum energy designs. 80 - Víctor Elvira, Joaquín Míguez, Petar M. Djuric:
On the performance of particle filters with adaptive number of particles. 81 - Giles Hooker, Lucas Mentch, Siyu Zhou:
Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance. 82
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