VOL. 34 · NO. 1 | February 2019
 
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Frontmatter
Statist. Sci. 34 (1), (February 2019)
No abstract available
Statist. Sci. 34 (1), (February 2019)
No abstract available
Articles
François-Xavier Briol, Chris J. Oates, Mark Girolami, Michael A. Osborne, Dino Sejdinovic
Statist. Sci. 34 (1), 1-22, (February 2019) DOI: 10.1214/18-STS660
KEYWORDS: computational statistics, nonparametric statistics, probabilistic numerics, uncertainty quantification
Fred J. Hickernell, R. Jagadeeswaran
Statist. Sci. 34 (1), 23-28, (February 2019) DOI: 10.1214/18-STS685
KEYWORDS: Bayesian, fast algorithms, quasi-Monte Carlo
Art B. Owen
Statist. Sci. 34 (1), 29-33, (February 2019) DOI: 10.1214/18-STS676
KEYWORDS: probabilistic numerics, quasi-Monte Carlo
Michael L. Stein, Ying Hung
Statist. Sci. 34 (1), 34-37, (February 2019) DOI: 10.1214/18-STS677
No abstract available
François-Xavier Briol, Chris J. Oates, Mark Girolami, Michael A. Osborne, Dino Sejdinovic
Statist. Sci. 34 (1), 38-42, (February 2019) DOI: 10.1214/18-STS683
KEYWORDS: computational statistics, nonparametric statistics, probabilistic numerics, uncertainty quantification
Vincent Dorie, Jennifer Hill, Uri Shalit, Marc Scott, Dan Cervone
Statist. Sci. 34 (1), 43-68, (February 2019) DOI: 10.1214/18-STS667
KEYWORDS: Causal inference, competition, machine learning, automated algorithms, evaluation
Miguel A. Hernán
Statist. Sci. 34 (1), 69-71, (February 2019) DOI: 10.1214/18-STS684
KEYWORDS: Causal inference, data analysis competitions
Qingyuan Zhao, Luke J. Keele, Dylan S. Small
Statist. Sci. 34 (1), 72-76, (February 2019) DOI: 10.1214/18-STS680
KEYWORDS: observational studies, machine learning, study design
David Jensen
Statist. Sci. 34 (1), 77-81, (February 2019) DOI: 10.1214/18-STS690
KEYWORDS: Causal inference, empirical evaluation, machine learning, algorithmic complexity, constructed observational studies, alignment
Susan Gruber, Mark J. van der Laan
Statist. Sci. 34 (1), 82-85, (February 2019) DOI: 10.1214/18-STS689
KEYWORDS: Targeted learning, Causal inference, TMLE
Ehud Karavani, Tal El-Hay, Yishai Shimoni, Chen Yanover
Statist. Sci. 34 (1), 86-89, (February 2019) DOI: 10.1214/18-STS679
KEYWORDS: Causal inference, competition, data challenge, machine learning, automated algorithms, evaluation
Nicole Bohme Carnegie
Statist. Sci. 34 (1), 90-93, (February 2019) DOI: 10.1214/18-STS682
KEYWORDS: Bayesian additive regression trees, TMLE, propensity score
Vincent Dorie, Jennifer Hill, Uri Shalit, Marc Scott, Dan Cervone
Statist. Sci. 34 (1), 94-99, (February 2019) DOI: 10.1214/18-STS688
KEYWORDS: Causal inference, competition, machine learning, automated algorithms, evaluation
Georg Lindgren
Statist. Sci. 34 (1), 100-128, (February 2019) DOI: 10.1214/18-STS662
KEYWORDS: computational statistics, distribution of maximum, Durbin’s formula, excursion length distribution, first passage, independent interval assumption, level crossings, multivariate normal probabilities, period/amplitude distribution, Rice’s formula, RIND program, statistical computation, stochastic process, successive crossing distance distribution, truncated normal moments, Wafo toolbox
Víctor Elvira, Luca Martino, David Luengo, Mónica F. Bugallo
Statist. Sci. 34 (1), 129-155, (February 2019) DOI: 10.1214/18-STS668
KEYWORDS: Monte Carlo methods, multiple importance sampling, Bayesian inference
Geurt Jongbloed
Statist. Sci. 34 (1), 156-168, (February 2019) DOI: 10.1214/18-STS663
KEYWORDS: University of Amsterdam, Mathematical Center (CWI), Delft University of Technology, violin playing
Vladimir Koltchinskii, Richard Nickl, Philippe Rigollet
Statist. Sci. 34 (1), 169-175, (February 2019) DOI: 10.1214/18-STS678
KEYWORDS: Biography, Probability, statistics
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