2020

Gorgi P. - Beta-negative binomial auto-regressions for modelling integer-valued time series with extreme observations, pp. 1325-1347.
Mozgunov P., Jaki T. - An information theoretic approach for selecting arms in clinical trials, pp. 1223-1247.
Mukhopadhyay M., Li D., Dunson D.B. - Estimating densities with non-linear support by using Fisher-Gaussian kernels, pp. 1249-1271.
Pollock M., Fearnhead P., Johansen A.M., Roberts G.O. - Quasi-stationary Monte Carlo and the ScaLE algorithm, pp. 1167-1221.
Richardson R., Kottas A., Sansó B. - Spatiotemporal modelling using integro-difference equations with bivariate stable kernels, pp. 1371-1392.
Tang Y., Reid N. - Modified likelihood root in high dimensions, pp. 1349-1369.
Wang G., Sarkar A., Carbonetto P., Stephens M. - A simple new approach to variable selection in regression, with application to genetic fine mapping, pp. 1273-1300.
Ye T., Shao J. - Robust tests for treatment effect in survival analysis under covariate-adaptive randomization, pp. 1301-1323.

Apley D. W., Zhu J. - Visualizing the effects of predictor variables in black box supervised learning models, pp. 1059‑1086.
Engelke S., Hitz A. S. - Graphical models for extremes, pp. 871‑932.
Fortini S., Petrone S. - Quasi-Bayes properties of a procedure for sequential learning in mixture models, pp. 1087‑1114.
Lane A. - Adaptive designs for optimal observed Fisher information, pp. 1029‑1058.
Liu B., Zhou C., Zhang X., Liu Y. - A unified data-adaptive framework for high dimensional change point detection, pp. 933‑963.
Poß D., Liebl D., Kneip A., Eisenbarth H., Wager T. D., Barrett L. F. - Superconsistent estimation of points of impact in non-parametric regression with functional predictors, pp. 1115‑1140.
Rad K. R., Maleki A. - A scalable estimate of the out-of-sample prediction error via approximate leave-one-out cross-validation, pp. 965‑996.
Silva I. R., Kulldorff M., Yih W. K. - Optimal alpha spending for sequential analysis with binomial data, pp. 1141‑1164.
Taeb A., Shah P., Chandrasekaran V. - False discovery and its control in low rank estimation, pp. 997‑1027.

Javanmard A., Lee J. D. - A flexible framework for hypothesis testing in high dimensions, pp. 685–718.
Westling T., Gilbert P., Carone M. - Causal isotonic regression, pp. 719–47.
Díaz I., Hejazi N. S. - Causal mediation analysis for stochastic interventions, pp. 661–83.
Janková J., Shah R. D., Bühlmann P., Samworth R. J. - Goodness-of-fit testing in high dimensional generalized linear models, pp. 773–95.
Chauvet G., Vallée A.-A. - Inference for two-stage sampling designs, pp. 797–815.
Jiang Z., Ling N., Lu Z., Tj⊘stheim D., Zhang Q. - On bandwidth choice for spatial data density estimation, pp. 817–40.
Rosenblum M., Fang E. X., Liu H. - Optimal, two-stage, adaptive enrichment designs for randomized trials, using sparse linear programming, pp. 749–72.
Singh, S. - Reply to the correction by Grover and Kaur: a new randomized response model, pp. 865–8.
Prasad A., Suggala A. S., Balakrishnan S., Ravikumar P. - Robust estimation via robust gradient estimation, pp. 601–27.
Hemerik J., Goeman J. J., Finos L. - Robust testing in generalized linear models by sign flipping score contributions, pp. 841–64.
Dette H., Kokot K., Volgushev S. - Testing relevant hypotheses in functional time series via self-normalization, pp. 629–60.
Jacob P. E., O’Leary J., Atchadé Y. F. - Unbiased Markov chain Monte Carlo methods with couplings, pp. 543–600.

Cai T. T., Guo Z. - Semisupervised inference for explained variance in high dimensional linear regression and its applications, pp. 391‑419.
Dubey P., Müller H.-G. - Functional models for time-varying random objects, pp. 275‑327.
Frazier D. T., Robert C. P., Rousseau J. - Model misspecification in approximate Bayesian computation: consequences and diagnostics, pp. 421‑444.
Gataric M., Wang T., Samworth R. J. - Sparse principal component analysis via axis-aligned random projections, pp. 329‑359.
Jiang J., Torabi M. - Sumca: simple, unified, Monte-Carlo-assisted approach to second-order unbiased mean-squared prediction error estimation, pp. 467‑485.
Shah R. D., Frot B., Thanei G.-A., Meinshausen N. - Right singular vector projection graphs: fast high dimensional covariance matrix estimation under latent confounding, pp. 361‑389.
Shi X., Miao W., Nelson J. C., Tchetgen E. J. T. - Multiply robust causal inference with double-negative control adjustment for categorical unmeasured confounding, pp. 521‑540.
Todeschini A., Miscouridou X., Caron F. - Exchangeable random measures for sparse and modular graphs with overlapping communities, pp. 487‑520.
Yang S., Kim J. K., Song R. - Doubly robust inference when combining probability and non-probability samples with high dimensional data, pp. 445‑465.

DUNSON David, WOOD Simon - Report of the Editors—2019, p. 3-4
KHISMATULLINA Marina, VOGT Michael - Multiscale inference and long‐run variance estimation in non‐parametric regression with time series errors, Pages: 5-37
CINELLI Carlos, HAZLETT Chad - Making sense of sensitivity: extending omitted variable bias, pp. 39-67
LUO Lan, SONG Peter X.‐K. - Renewable estimation and incremental inference in generalized linear models with streaming data sets, pp. 69-97
CHEN Fan, ZHANG Yini, ROHE Karl - Targeted sampling from massive block model graphs with personalized PageRank, pp. 99-126
CHRISTENSEN Jonathan, MA Li - A Bayesian hierarchical model for related densities by using Pólya trees. pp. 127-153
ZHAO Puying, GHOSH Malay, RAO J. N. K., WU Changbao - Bayesian empirical likelihood inference with complex survey data, pp. 155-174
BERRETT Thomas B., WANG Yi, FOYGEL BARBER Rina, SAMWORTH RICHARD J. - The conditional permutation test for independence while controlling for confounders, pp. 175-197
FULCHER Isabel R., SHPITSER Ilya, MAREALLE Stella, TCHETGEN Eric J. - Robust inference on population indirect causal effects: the generalized front door criterion, pp. 199-214
BOLIN David, WALLIN Jonas - Multivariate type G Matérn stochastic partial differential equation random fields, pp. 215-239
LI Xinran, DING Peng - Rerandomization and regression adjustment, pp. 241-268
KUMAR GROVEr Lovleen, KAUR Amanpreet - Correction: ‘A new randomized response model’, pp. 269-271

Dernière modification le 22.03.2022