Statistics and Probability Letters

Aims & Scope

Statistics & Probability Letters adopts a novel and highly innovative approach to the publication of research findings in statistics and probability.

It features concise articles, rapid publication and broad coverage of the statistics and probability literature.

Statistics & Probability Letters is a refereed journal.

Articles will be limited to six journal pages (13 double-space typed pages) including references and figures.

Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in Statistics & Probability Letters.

Every attempt will be made to provide the first review of a submitted manuscript within three months of submission.

The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization.

The aim of Statistics & Probability Letters is to help to alleviate this problem.

Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability.

The mainstream of Letters will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines.

Key results and central ideas must be presented in a clear and concise manner.

These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal.

Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified.

Empirical and computational results that are of significant value will be published.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Decision Sciences and Mathematics, designed to support cutting-edge academic discovery.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Bayesian quantile regression

  Citation: 704

  Authors: Keming, Rana A.

• Unifying the derivations for the Akaike and corrected Akaike information criteria

  Citation: 504

  Authors: Joseph E.

• Estimating the number of change-points via Schwarz' criterion

  Citation: 424

  Authors: Yi-Ching

• Functional linear model

  Citation: 386

  Authors: Hervé, Frédéric, Pascal

• A multivariate Kolmogorov-Smirnov test of goodness of fit

  Citation: 371

  Authors: Ana, Daniel, Rubén

• Descriptive statistics for multivariate distributions

  Citation: 335

  Authors: Hannu

• Sparse spatial autoregressions

  Citation: 287

  Authors: R., Ronald

• A new two-parameter lifetime distribution with bathtub shape or increasing failure rate function

  Citation: 285

  Authors: Zhenmin

• Efficient computation of adjusted <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" display="inline" overflow="scroll"><mml:mi>p</mml:mi></mml:math>-values for resampling-based stepdown multiple testing

  Citation: 268

  Authors: Joseph P., Michael

• On relationships between the Pearson and the distance correlation coefficients

  Citation: 264

  Authors: Dominic, Tamás F., Gábor J.