Canadian Journal of Statistics

Aims & Scope

The Canadian Journal of Statistics is the official journal of the Statistical Society of Canada.

It has a reputation internationally as an excellent journal.

The editorial board is comprised of statistical scientists with applied, computational, methodological, theoretical and probabilistic interests.

Their role is to ensure that the journal continues to provide an international forum for the discipline of Statistics.

The journal seeks papers making broad points of interest to many readers, whereas papers making important points of more specific interest are better placed in more specialized journals.

The levels of innovation and impact are key in the evaluation of submitted manuscripts.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1
2024	0.80

Journal Rank

Year	Value
2024	9870

Journal Citation Indicator

Year	Value
2024	206

SJR (SCImago Journal Rank)

Year	Value
2024	0.588

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	57

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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.

• Negative binomial and mixed Poisson regression

  Citation: 771

  Authors: Jerald F.

• Beyond kappa: A review of interrater agreement measures

  Citation: 682

  Authors: Mousumi, Michelle, Laura, Debajyoti

• Nonparametric standard errors and confidence intervals

  Citation: 485

  Authors: Bradley

• A new class of multivariate skew distributions with applications to bayesian regression models

  Citation: 460

  Authors: Sujit K., Dipak K., Márcia D.

• Copules archimédiennes et families de lois bidimensionnelles dont les marges sont données

  Citation: 324

  Authors: Christian, R. Jock

• Bayesian analysis of elapsed times in continuous‐time Markov chains

  Citation: 277

  Authors: Marco A. R., Marc A.

• Bayesian variable selection with related predictors

  Citation: 242

  Authors: Hugh

• Confidence curves and improved exact confidence intervals for discrete distributions

  Citation: 227

  Authors: Helge

• Truncated regular vines in high dimensions with application to financial data

  Citation: 217

  Authors: E. C., C., K.

• Semiparametric estimation in copula models

  Citation: 204

  Authors: Hideatsu

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