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ORCIDStatistics and Computing, Volume 30
Volume 30, Number 1, February 2020
- Kei Kobayashi
, Henry P. Wynn:
Empirical geodesic graphs and CAT(k) metrics for data analysis. 1-18 - Zheyuan Li, Simon N. Wood:
Faster model matrix crossproducts for large generalized linear models with discretized covariates. 19-25 - Nicholas G. Tawn, Gareth O. Roberts, Jeffrey S. Rosenthal:
Weight-preserving simulated tempering. 27-41 - Ioannis Kosmidis, Euloge Clovis Kenne Pagui, Nicola Sartori:
Mean and median bias reduction in generalized linear models. 43-59 - Pierre Barbillon, Loïc Schwaller, Stéphane Robin, Andrew Flachs, Glenn Stone:
Epidemiologic network inference. 61-75 - Francesco Battaglia, Domenico Cucina, Manuel Rizzo:
Parsimonious periodic autoregressive models for time series with evolving trend and seasonality. 77-91 - Belmiro P. M. Duarte, José F. O. Granjo, Weng Kee Wong:
Optimal exact designs of experiments via Mixed Integer Nonlinear Programming. 93-112 - Kris Boudt, Peter J. Rousseeuw, Steven Vanduffel, Tim Verdonck:
The minimum regularized covariance determinant estimator. 113-128 - Yafeng Cheng, Jian Qing Shi, Janet A. Eyre:
Nonlinear mixed-effects scalar-on-function models and variable selection. 129-140 - Torsten Hothorn:
Transformation boosting machines. 141-152 - P. J. Paine, S. P. Preston, Michail Tsagris, Andrew T. A. Wood:
Spherical regression models with general covariates and anisotropic errors. 153-165 - Peter F. Craigmile, Debashis Mondal:
Estimation of long-range dependence in gappy Gaussian time series. 167-185 - Francisco Cuevas, Denis Allard, Emilio Porcu:
Fast and exact simulation of Gaussian random fields defined on the sphere cross time. 187-194 - Olivier Bock, Xavier Collilieux, François Guillamon, Emilie Lebarbier, Claire Pascal:
A breakpoint detection in the mean model with heterogeneous variance on fixed time intervals. 195-207
Volume 30, Number 2, March 2020
- Matthew Price-Williams, Nicholas A. Heard:
Nonparametric self-exciting models for computer network traffic. 209-220 - Manuele Leonelli, Dani Gamerman:
Semiparametric bivariate modelling with flexible extremal dependence. 221-236 - Andrew Glaws, Paul G. Constantine, R. Dennis Cook:
Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experiments. 237-253 - Luca Greco, Claudio Agostinelli:
Weighted likelihood mixture modeling and model-based clustering. 255-277 - David Rügamer, Sonja Greven:
Inference for L2-Boosting. 279-289 - Sheng Ren, Emily Lei Kang, Jason L. Lu:
MCEN: a method of simultaneous variable selection and clustering for high-dimensional multinomial regression. 291-304 - Ömer Deniz Akyildiz, Joaquín Míguez:
Nudging the particle filter. 305-330 - Gang-Hoo Kim, Sung-Ho Kim:
Marginal information for structure learning. 331-349 - Daniel Andrade, Akiko Takeda, Kenji Fukumizu:
Robust Bayesian model selection for variable clustering with the Gaussian graphical model. 351-376 - Tijana Radivojevic, Elena V. Akhmatskaya:
Modified Hamiltonian Monte Carlo for Bayesian inference. 377-404 - Aurya Javeed, Giles Hooker:
Timing observations of diffusions. 405-417 - Arno Solin, Simo Särkkä:
Hilbert space methods for reduced-rank Gaussian process regression. 419-446 - Isadora Antoniano-Villalobos, Emanuele Borgonovo, Xuefei Lu:
Nonparametric estimation of probabilistic sensitivity measures. 447-467 - Greg McSwiggan, Adrian J. Baddeley, Gopalan M. Nair:
Estimation of relative risk for events on a linear network. 469-484
Volume 30, Number 3, May 2020
- Panagiotis Papastamoulis:
Clustering multivariate data using factor analytic Bayesian mixtures with an unknown number of components. 485-506 - Michael B. Giles, Mateusz B. Majka, Lukasz Szpruch, Sebastian J. Vollmer, Konstantinos C. Zygalakis:
Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations. 507-524 - Mohamed Reda El Amri, Céline Helbert, Olivier Lepreux, Miguel Munoz Zuniga, Clémentine Prieur, Delphine Sinoquet:
Data-driven stochastic inversion via functional quantization. 525-541 - Ziwen An, David J. Nott, Christopher C. Drovandi:
Robust Bayesian synthetic likelihood via a semi-parametric approach. 543-557 - Jukka Sirén, Samuel Kaski:
Local dimension reduction of summary statistics for likelihood-free inference. 559-570 - Georg Hahn:
Optimal allocation of Monte Carlo simulations to multiple hypothesis tests. 571-586 - Alvin J. K. Chua:
Sampling from manifold-restricted distributions using tangent bundle projections. 587-602 - Sergey Dolgov, Karim Anaya-Izquierdo, Colin Fox, Robert Scheichl:
Approximation and sampling of multivariate probability distributions in the tensor train decomposition. 603-625 - Evelyn Buckwar, Massimiliano Tamborrino, Irene Tubikanec:
Spectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs. 627-648 - Achmad Choiruddin, Francisco Cuevas-Pacheco, Jean-François Coeurjolly, Rasmus Waagepetersen:
Regularized estimation for highly multivariate log Gaussian Cox processes. 649-662 - Richard G. Everitt, Richard Culliford, Felipe J. Medina-Aguayo, Daniel J. Wilson:
Sequential Monte Carlo with transformations. 663-676 - Eliana Christou:
Central quantile subspace. 677-695 - Fan Wang, Sach Mukherjee, Sylvia Richardson, Steven M. Hill:
High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking. 697-719 - Changye Wu, Christian P. Robert:
Coordinate sampler: a non-reversible Gibbs-like MCMC sampler. 721-730
Volume 30, Number 4, July 2020
- Hien Duy Nguyen, Florence Forbes, Geoffrey J. McLachlan:
Mini-batch learning of exponential family finite mixture models. 731-748 - Andrea Ongaro, Sonia Migliorati, Roberto Ascari:
A new mixture model on the simplex. 749-770 - Peijun Sang, Jiguo Cao:
Functional single-index quantile regression models. 771-781 - Eduardo F. Mendes, Christopher K. Carter, David Gunawan, Robert Kohn:
A flexible particle Markov chain Monte Carlo method. 783-798 - Jackie S. T. Wong, Jonathan J. Forster, Peter W. F. Smith:
Properties of the bridge sampler with a focus on splitting the MCMC sample. 799-816 - Denis Dresvyanskiy, Tatiana Karaseva, Vitalii Makogin, Sergei Mitrofanov, Claudia Redenbach, Evgeny Spodarev:
Detecting anomalies in fibre systems using 3-dimensional image data. 817-837 - Pallavi Ray, Debdeep Pati, Anirban Bhattacharya:
Efficient Bayesian shape-restricted function estimation with constrained Gaussian process priors. 839-853 - Bruno Santos, Thomas Kneib:
Noncrossing structured additive multiple-output Bayesian quantile regression models. 855-869 - Keiji Takai:
Incomplete-data Fisher scoring method with steplength adjustment. 871-886 - Lifeng Ye, Alexandros Beskos, Maria De Iorio, Jie Hao:
Monte Carlo co-ordinate ascent variational inference. 887-905 - Assyr Abdulle, Giacomo Garegnani:
Random time step probabilistic methods for uncertainty quantification in chaotic and geometric numerical integration. 907-932 - Weichang Yu, John T. Ormerod, Michael Stewart:
Variational discriminant analysis with variable selection. 933-951 - Raoul Müller, Dominic Schuhmacher, Jorge Mateu:
Metrics and barycenters for point pattern data. 953-972 - Denis Belomestny, Leonid Iosipoi, Eric Moulines, Alexey Naumov, Sergey Samsonov:
Variance reduction for Markov chains with application to MCMC. 973-997 - Katya Mauff, Ewout W. Steyerberg, Isabella Kardys, Eric Boersma, Dimitris Rizopoulos:
Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach. 999-1014 - Hongliang Lü, Julyan Arbel, Florence Forbes:
Bayesian nonparametric priors for hidden Markov random fields. 1015-1035 - Qiang Liu, Xin T. Tong:
Accelerating Metropolis-within-Gibbs sampler with localized computations of differential equations. 1037-1056 - G. S. Rodrigues, David J. Nott, Scott A. Sisson:
Likelihood-free approximate Gibbs sampling. 1057-1073 - Aijun Zhang, Hengtao Zhang, Guosheng Yin:
Adaptive iterative Hessian sketch via A-optimal subsampling. 1075-1090 - José L. Torrecilla, Carlos Ramos-Carreño, Manuel A. Sánchez-Montañés, Alberto Suárez:
Optimal classification of Gaussian processes in homo- and heteroscedastic settings. 1091-1111 - Rahul Mazumder, Diego Saldana, Haolei Weng:
Matrix completion with nonconvex regularization: spectral operators and scalable algorithms. 1113-1138 - Pierre Alquier, Karine Bertin, Paul Doukhan, Rémy Garnier:
High-dimensional VAR with low-rank transition. 1139-1153 - Thomas Grundy, Rebecca Killick, Gueorgui Mihaylov:
High-dimensional changepoint detection via a geometrically inspired mapping. 1155-1166
Volume 30, Number 5, September 2020
- Shanika L. Wickramasuriya, Berwin A. Turlach, Rob J. Hyndman:
Optimal non-negative forecast reconciliation. 1167-1182 - S. G. J. Senarathne, Christopher C. Drovandi, James M. McGree:
A Laplace-based algorithm for Bayesian adaptive design. 1183-1208 - Haixu Wang, Jiguo Cao:
Estimating time-varying directed neural networks. 1209-1220 - Ottmar Cronie, M. Mehdi Moradi, Jorge Mateu:
Inhomogeneous higher-order summary statistics for point processes on linear networks. 1221-1239 - Francesco Sanna Passino, Nicholas A. Heard:
Classification of periodic arrivals in event time data for filtering computer network traffic. 1241-1254 - Linda S. L. Tan, Aishwarya Bhaskaran, David J. Nott:
Conditionally structured variational Gaussian approximation with importance weights. 1255-1272 - Luigi Augugliaro, Gianluca Sottile, Veronica Vinciotti:
The conditional censored graphical lasso estimator. 1273-1289 - Francesco Sanna Passino, Nicholas A. Heard:
Bayesian estimation of the latent dimension and communities in stochastic blockmodels. 1291-1307 - Mirai Igarashi, Nobuhiko Terui:
Characterization of topic-based online communities by combining network data and user generated content. 1309-1324 - Joonha Park, Yves F. Atchadé:
Markov chain Monte Carlo algorithms with sequential proposals. 1325-1345 - Fadhel Ayed, Marco Battiston, Federico Camerlenghi:
An information theoretic approach to post randomization methods under differential privacy. 1347-1361 - Luis Angel García-Escudero, Agustín Mayo-Íscar, Marco Riani:
Model-based clustering with determinant-and-shape constraint. 1363-1380 - Ajay Jasra, Fangyuan Yu, Jeremy Heng:
Multilevel particle filters for the non-linear filtering problem in continuous time. 1381-1402 - Hendrik van der Wurp, Andreas Groll, Thomas Kneib, Giampiero Marra, Rosalba Radice:
Generalised joint regression for count data: a penalty extension for competitive settings. 1419-1432 - Christian Soize, Roger G. Ghanem, Christophe Desceliers:
Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset. 1433-1457 - Thomas Whitaker, Boris Beranger, Scott A. Sisson:
Composite likelihood methods for histogram-valued random variables. 1459-1477 - Joonha Park, Edward L. Ionides:
Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter. 1497-1522 - Serhat Emre Akhanli, Christian Hennig:
Comparing clusterings and numbers of clusters by aggregation of calibrated clustering validity indexes. 1523-1544 - Alfredo Alegría, Xavier Emery, Christian Lantuéjoul:
The turning arcs: a computationally efficient algorithm to simulate isotropic vector-valued Gaussian random fields on the d-sphere. 1403-1418 - Denis Allard, Xavier Emery, Céline Lacaux, Christian Lantuéjoul:
Simulating space-time random fields with nonseparable Gneiting-type covariance functions. 1479-1495 - Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy:
Anomaly and Novelty detection for robust semi-supervised learning. 1545-1571
Volume 30, Number 6, November 2020
- Claes Andersson, Tomás Mrkvicka:
Inference for cluster point processes with over- or under-dispersed cluster sizes. 1573-1590 - Antonio Lijoi, Igor Prünster, Tommaso Rigon:
Sampling hierarchies of discrete random structures. 1591-1607 - Andrew Zammit-Mangion, Jonathan Rougier:
Multi-scale process modelling and distributed computation for spatial data. 1609-1627 - Aude Sportisse, Claire Boyer, Julie Josse:
Imputation and low-rank estimation with Missing Not At Random data. 1629-1643 - Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez:
Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization. 1645-1663 - Chiheb Ben Hammouda, Nadhir Ben Rached, Raúl Tempone:
Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks. 1665-1689 - Georg Hahn, Paul Fearnhead, Idris A. Eckley:
BayesProject: Fast computation of a projection direction for multivariate changepoint detection. 1691-1705 - Angshuman Roy, Soham Sarkar, Anil Kumar Ghosh, Alok Goswami:
On some consistent tests of mutual independence among several random vectors of arbitrary dimensions. 1707-1723 - Estelle Kuhn, Catherine Matias, Tabea Rebafka:
Properties of the stochastic approximation EM algorithm with mini-batch sampling. 1725-1739 - David Gunawan, Khue-Dung Dang, Matias Quiroz, Robert Kohn, Minh-Ngoc Tran:
Subsampling sequential Monte Carlo for static Bayesian models. 1741-1758 - Aaron P. Lowther, Paul Fearnhead, Matthew A. Nunes, Kjeld Jensen:
Semi-automated simultaneous predictor selection for regression-SARIMA models. 1759-1778 - Daniel Ahfock, Geoffrey J. McLachlan:
An apparent paradox: a classifier based on a partially classified sample may have smaller expected error rate than that if the sample were completely classified. 1779-1790 - Hans Kersting, Timothy John Sullivan, Philipp Hennig:
Convergence rates of Gaussian ODE filters. 1791-1816
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