Journal of the Royal Statistical Society. Series B, Statistical Methodology
Overview
The Journal of the Royal Statistical Society, Series B: Statistical Methodology, is a prestigious academic journal that publishes cutting-edge research in statistical methodology. It covers a wide range of topics including theoretical developments, innovative methodologies, and practical applications in statistics. The journal serves as a platform for statisticians and researchers to share their advancements and contribute to the field of statistical methodology.
Details
Details
Abbr.
J R Stat Soc Series B Stat Methodol
Start
1998
End
Continuing
Frequency
Quarterly
p-ISSN
1369-7412
e-ISSN
1467-9868
Country
United Kingdom
Language
English
Metrics
Metrics
h-index / Ranks: 1393
151
SJR / Ranks: 331
4330
CiteScore / Ranks: 3928
5.90
JIF / Ranks: 1190
5.8
Recent Articles
1.
Liu Y, Liu Z, Lin X
J R Stat Soc Series B Stat Methodol
. 2025 Feb;
86(2):461-486.
PMID: 40012608
Testing a global null is a canonical problem in statistics and has a wide range of applications. In view of the fact that no uniformly most powerful test exists, prior...
2.
Tang R, Yuan M, Zhang A
J R Stat Soc Series B Stat Methodol
. 2025 Feb;
87(1):232-255.
PMID: 39943942
This paper introduces a novel framework called Mode-wise Principal Subspace Pursuit (MOP-UP) to extract hidden variations in both the row and column dimensions for matrix data. To enhance the understanding...
3.
Gablenz P, Sabatti C
J R Stat Soc Series B Stat Methodol
. 2025 Feb;
87(1):56-73.
PMID: 39935679
We consider problems where many, somewhat redundant, hypotheses are tested and we are interested in reporting the most precise rejections, with false discovery rate (FDR) control. This is the case,...
4.
Liang F, Kim S, Sun Y
J R Stat Soc Series B Stat Methodol
. 2025 Feb;
87(1):98-131.
PMID: 39935678
While fiducial inference was widely considered a big blunder by R.A. Fisher, the goal he initially set-'inferring the uncertainty of model parameters on the basis of observations'-has been continually pursued...
5.
Tan Z
J R Stat Soc Series B Stat Methodol
. 2024 Nov;
86(5):1339-1363.
PMID: 39544486
Consider sensitivity analysis for estimating average treatment effects under unmeasured confounding, assumed to satisfy a marginal sensitivity model. At the population level, we provide new representations for the sharp population...
6.
Lila E, Zhang W, Levendovszky S
J R Stat Soc Series B Stat Methodol
. 2024 Sep;
86(4):1013-1044.
PMID: 39279915
We introduce a novel framework for the classification of functional data supported on nonlinear, and possibly random, manifold domains. The motivating application is the identification of subjects with Alzheimer's disease...
7.
Yang Y, Kuchibhotla A, Tchetgen Tchetgen E
J R Stat Soc Series B Stat Methodol
. 2024 Sep;
86(4):943-965.
PMID: 39279914
Conformal prediction has received tremendous attention in recent years and has offered new solutions to problems in missing data and causal inference; yet these advances have not leveraged modern semi-parametric...
8.
Cai T, Ke Z, Turner P
J R Stat Soc Series B Stat Methodol
. 2024 Sep;
86(4):922-942.
PMID: 39279913
Motivated by applications in text mining and discrete distribution inference, we test for equality of probability mass functions of groups of high-dimensional multinomial distributions. Special cases of this problem include...
9.
Ye T, Liu Z, Sun B, Tchetgen Tchetgen E
J R Stat Soc Series B Stat Methodol
. 2024 Sep;
86(4):1045-1067.
PMID: 39279912
Mendelian randomization (MR) addresses causal questions using genetic variants as instrumental variables. We propose a new MR method, G-Estimation under No Interaction with Unmeasured Selection (GENIUS)-MAny Weak Invalid IV, which...
10.
Chen Y, Lin S, Zhou Y, Carmichael O, Muller H, Wang J
J R Stat Soc Series B Stat Methodol
. 2024 Jul;
86(3):694-713.
PMID: 39005888
Quantifying the association between components of multivariate random curves is of general interest and is a ubiquitous and basic problem that can be addressed with functional data analysis. An important...