Journal of the Royal Statistical Society: Series B (Statistical Methodology)
Published on behalf of the Royal Statistical Society
Edited by:
G. Casella and G. O. Roberts
ISI Journal Citation Reports® Ranking: 2008: 3/92 Statistics & Probability
Impact Factor: 2.835
The Journal of the Royal Statistical Society, Series B (Statistical Methodology) has a long tradition of publishing work that is at the leading edge of methodological development, with a strong emphasis on relevance to statistical practice. Included are papers on study design, statistical models, methods of analysis and the theory that underlies them - almost invariably motivated or illustrated by real examples. Series B aims to disseminate work which is innovative, insightful and likely to have a substantial impact on the way that data are collected and analysed; within these parameters the journal's scope is broad, embracing for example relevant work in applied probability, computational methods and the foundations of statistics. Methodological papers read before the Society at its Ordinary Meetings, organized regularly by the Research Section of the Society, are published in Series B with full discussion and authors' response.
TopNews and Announcements
ScholarOne Manuscripts™(formerly known as Manuscript Central)
Authors are able to submit their paper to the Journal of the Royal Statistical Society online using ScholarOne Manuscripts. Benefits of online submission include:
- Fast decisions on your paper. Submission, review and communication are all handled online. No more postal delays or lost messages!
- Easy. Write your paper on any word processor. Simply save text as RTF or Word. Graphics can be uploaded separately in any popular format, including PowerPoint and Excel.
- Convenient. Submit from any computer with an Internet connection. No software needs to be installed. All you need is a Web browser, Acrobat Reader and email.
- Responsive. Decisions sent by email, revisions made online. The moment a decision is taken, an email is dispatched. You can respond to the comments and submit a revised version online.
- Transparent. Track your manuscripts online. Return to the site at any time to see the current status of your submission
To make a submission, please visit http://mc.manuscriptcentral.com/jrss
Online Open
Authors of articles in this journal can now choose to make their articles open access and available free for all readers through the payment of an author fee. Read more.
Articles Published Online Ahead of Print
Articles which have been fully copy-edited and peer-reviewed are published online through our EarlyView feature before the print edition of this journal is published.
Datasets relating to articles published in the four series of the Journal of the Royal Statistical Society are available online.
Free Online Access in the Developing World
Free online access to this journal is available within institutions in the developing world through the AGORA Initiative with the United Nations Food and Agriculture Organization (FAO), and the OARE Initiative (Online Access to Research in the Environment) with the UN Environment Programme (UNEP).
NIH Public Access Mandate
For those interested in the Wiley-Blackwell policy on the NIH Public Access Mandate, please visit our policy statement.
TopHighlights
The group lasso for logistic regression
Lukas Meier, Sarah van de Geer and Peter Bühlmann
L1-regularization path algorithm for generalized linear models
Mee Young Park and Trevor Hastie
Sure independence screening for ultrahigh dimensional feature space
Jianqing Fan and Jinchi Lv
Fast stable direct fitting and smoothness selection for generalized additive models
S. N. Wood
Testing in semiparametric models with interaction, with applications to gene-environment interactions
Arnab Maity, Raymond J. Carroll, Enno Mammen and Nilanjan Chatterjee
Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)
A. Beskos, O. Papaspiliopoulos, G. O. Roberts and P. Fearnhead
Sequential Monte Carlo samplers
P. Del Moral, A. Doucet and A. Jasra
On the bias of the multiple-imputation variance estimator in survey sampling
J. K. Kim, J. M. Brick, W. A. Fuller and G. Kalton
On parametric bootstrap methods for small area prediction
P. Hall and T. Maiti
Discussion papers
Series B also publishes papers which have been presented for discussion at meeting of the society. Forthcoming discussion papers are available from the society's web pages. For recently published discussion papers, please browse the Series B online table of contents. Below is a selection that you can read for free.
Sampling bias and logistic models
P. McCullagh
Highly accessed papers
View the 10 most read articles in Series B (Statistical Methodology)
Highly cited papers
View the 10 most highly cited articles in Series B (Statistical Methodology)
