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Statistics 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
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
Mean and median bias reduction in generalized linear models. 43-59 - Pierre Barbillon
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
Optimal exact designs of experiments via Mixed Integer Nonlinear Programming. 93-112 - Kris Boudt
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
Spherical regression models with general covariates and anisotropic errors. 153-165 - Peter F. Craigmile
Estimation of long-range dependence in gappy Gaussian time series. 167-185 - Francisco Cuevas
Fast and exact simulation of Gaussian random fields defined on the sphere cross time. 187-194 - Olivier Bock
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
Semiparametric bivariate modelling with flexible extremal dependence. 221-236 - Andrew Glaws, Paul G. Constantine
Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experiments. 237-253 - Luca Greco
Weighted likelihood mixture modeling and model-based clustering. 255-277 - David Rügamer
Inference for L2-Boosting. 279-289 - Sheng Ren, Emily Lei Kang
MCEN: a method of simultaneous variable selection and clustering for high-dimensional multinomial regression. 291-304 - Ömer Deniz Akyildiz
Nudging the particle filter. 305-330 - Gang-Hoo Kim, Sung-Ho Kim
Marginal information for structure learning. 331-349 - Daniel Andrade
Robust Bayesian model selection for variable clustering with the Gaussian graphical model. 351-376 - Tijana Radivojevic
Modified Hamiltonian Monte Carlo for Bayesian inference. 377-404 - Aurya Javeed
Timing observations of diffusions. 405-417 - Arno Solin
Hilbert space methods for reduced-rank Gaussian process regression. 419-446 - Isadora Antoniano-Villalobos, Emanuele Borgonovo
Nonparametric estimation of probabilistic sensitivity measures. 447-467 - Greg McSwiggan, Adrian J. Baddeley
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
Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations. 507-524 - Mohamed Reda El Amri
Data-driven stochastic inversion via functional quantization. 525-541 - Ziwen An
Robust Bayesian synthetic likelihood via a semi-parametric approach. 543-557 - Jukka Sirén
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
Approximation and sampling of multivariate probability distributions in the tensor train decomposition. 603-625 - Evelyn Buckwar
Spectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs. 627-648 - Achmad Choiruddin
Regularized estimation for highly multivariate log Gaussian Cox processes. 649-662 - Richard G. Everitt
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
Mini-batch learning of exponential family finite mixture models. 731-748 - Andrea Ongaro, Sonia Migliorati
A new mixture model on the simplex. 749-770 - Peijun Sang, Jiguo Cao
Functional single-index quantile regression models. 771-781 - Eduardo F. Mendes
A flexible particle Markov chain Monte Carlo method. 783-798 - Jackie S. T. Wong
Properties of the bridge sampler with a focus on splitting the MCMC sample. 799-816 - Denis Dresvyanskiy
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
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
Monte Carlo co-ordinate ascent variational inference. 887-905 - Assyr Abdulle
Random time step probabilistic methods for uncertainty quantification in chaotic and geometric numerical integration. 907-932 - Weichang Yu
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
Variance reduction for Markov chains with application to MCMC. 973-997 - Katya Mauff
Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach. 999-1014 - Hongliang Lü, Julyan Arbel
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
Likelihood-free approximate Gibbs sampling. 1057-1073 - Aijun Zhang
Adaptive iterative Hessian sketch via A-optimal subsampling. 1075-1090 - José L. Torrecilla
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
High-dimensional VAR with low-rank transition. 1139-1153 - Thomas Grundy
High-dimensional changepoint detection via a geometrically inspired mapping. 1155-1166
Volume 30, Number 5, September 2020
- Shanika L. Wickramasuriya
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
Inhomogeneous higher-order summary statistics for point processes on linear networks. 1221-1239 - Francesco Sanna Passino
Classification of periodic arrivals in event time data for filtering computer network traffic. 1241-1254 - Linda S. L. Tan
Conditionally structured variational Gaussian approximation with importance weights. 1255-1272 - Luigi Augugliaro
The conditional censored graphical lasso estimator. 1273-1289 - Francesco Sanna Passino
Bayesian estimation of the latent dimension and communities in stochastic blockmodels. 1291-1307 - Mirai Igarashi
Characterization of topic-based online communities by combining network data and user generated content. 1309-1324 - Joonha Park
Markov chain Monte Carlo algorithms with sequential proposals. 1325-1345 - Fadhel Ayed, Marco Battiston
An information theoretic approach to post randomization methods under differential privacy. 1347-1361 - Luis Angel García-Escudero
Model-based clustering with determinant-and-shape constraint. 1363-1380 - Ajay Jasra
Multilevel particle filters for the non-linear filtering problem in continuous time. 1381-1402 - Hendrik van der Wurp
Generalised joint regression for count data: a penalty extension for competitive settings. 1419-1432 - Christian Soize
Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset. 1433-1457 - Thomas Whitaker
Composite likelihood methods for histogram-valued random variables. 1459-1477 - Joonha Park
Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter. 1497-1522 - Serhat Emre Akhanli
Comparing clusterings and numbers of clusters by aggregation of calibrated clustering validity indexes. 1523-1544
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
Sampling hierarchies of discrete random structures. 1591-1607 - Andrew Zammit-Mangion
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
Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization. 1645-1663 - Chiheb Ben Hammouda
Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks. 1665-1689 - Georg Hahn
BayesProject: Fast computation of a projection direction for multivariate changepoint detection. 1691-1705 - Angshuman Roy
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
Subsampling sequential Monte Carlo for static Bayesian models. 1741-1758 - Aaron P. Lowther
Semi-automated simultaneous predictor selection for regression-SARIMA models. 1759-1778 - Daniel Ahfock
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
Convergence rates of Gaussian ODE filters. 1791-1816
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