Scandinavian Journal of Statistics

Aims & Scope

The Scandinavian Journal of Statistics is internationally recognised as one of the leading statistical journals in the world.

It was founded in 1974 by four Scandinavian statistical societies.

Today more than eighty per cent of the manuscripts are submitted from outside Scandinavia.

It is an international journal devoted to reporting significant and innovative original contributions to statistical methodology, both theory and applications.

The journal specializes in statistical modelling showing particular appreciation of the underlying substantive research problems.

The emergence of specialized methods for analysing longitudinal and spatial data is just one example of an area of important methodological development in which the Scandinavian Journal of Statistics has a particular niche.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1
2024	0.80

SJR (SCImago Journal Rank)

Year	Value
2024	0.871

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	72

Journal Rank

Year	Value
2024	5990

Journal Citation Indicator

Year	Value
2024	249

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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 Decision Sciences and 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.

• The Skew-normal Distribution and Related Multivariate Families*

  Citation: 530

  Authors: ADELCHI

• Log Gaussian Cox Processes

  Citation: 484

  Authors: Jesper, Anne Randi, Rasmus Plenge

• Normal Inverse Gaussian Distributions and Stochastic Volatility Modelling

  Citation: 389

  Authors: Ole E.

• Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps

  Citation: 377

  Authors: CECILIA

• Goodness‐of‐fit Procedures for Copula Models Based on the Probability Integral Transformation

  Citation: 316

  Authors: CHRISTIAN, JEAN‐FRANÇOIS, BRUNO

• Normal Inverse Gaussian Distributions and Stochastic Volatility Modelling

  Citation: 303

  Authors: Ole E.

• On the Unification of Families of Skew‐normal Distributions

  Citation: 281

  Authors: REINALDO B., ADELCHI

• Simple and Globally Convergent Methods for Accelerating the Convergence of Any EM Algorithm

  Citation: 277

  Authors: RAVI, CHRISTOPHE

• Estimation of an Ergodic Diffusion from Discrete Observations

  Citation: 271

  Authors: Mathieu

• Multivariate Dispersion Models Generated From Gaussian Copula

  Citation: 256

  Authors: Peter

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