Bernoulli

Aims & Scope

BERNOULLI is the journal of the Bernoulli Society for Mathematical Statistics and Probability, issued four times per year.

The journal provides a comprehensive account of important developments in the fields of statistics and probability, offering an international forum for both theoretical and applied work.

BERNOULLI will publish: Papers containing original and significant research contributions: with background, mathematical derivation and discussion of the results in suitable detail and, where appropriate, with discussion of interesting applications in relation to the methodology proposed.

Papers of the following two types will also be considered for publication, provided they are judged to enhance the dissemination of research: Review papers which provide an integrated critical survey of some area of probability and statistics and discuss important recent developments.

Scholarly written papers on some historical significant aspect of statistics and probability.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.7

SJR (SCImago Journal Rank)

Year	Value
2024	1.480

Quartile

Year	Value
2024	Q1

Journal Rank

Year	Value
2024	2446

Journal Citation Indicator

Year	Value
2024	665

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Abstracting & Indexing

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

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

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

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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.

• An Adaptive Metropolis Algorithm

  Citation: 1949

  Authors: Heikki, Eero, Johanna

• Exponential Convergence of Langevin Distributions and Their Discrete Approximations

  Citation: 624

  Authors: Gareth O., Richard L.

• Profile likelihood inferences on semiparametric varying-coefficient partially linear models

  Citation: 563

  Authors: Jianqing, Tao

• Hyperbolic Distributions in Finance

  Citation: 553

  Authors: Ernst, Ulrich

• Deterministic and Stochastic Models for Coalescence (Aggregation and Coagulation): A Review of the Mean-Field Theory for Probabilists

  Citation: 467

  Authors: David J.

• Least squares after model selection in high-dimensional sparse models

  Citation: 429

  Authors: Alexandre, Victor

• Efficient estimation of stochastic volatility using noisy observations: a multi-scale approach

  Citation: 416

  Authors: Lan

• Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes

  Citation: 416

  Authors: Christian, Jean-Michel

• Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations

  Citation: 362

  Authors: Peter J., Elizaveta

• The geometric foundations of Hamiltonian Monte Carlo

  Citation: 330

  Authors: Michael, Simon, Sam, Mark

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