Statistical Methods and Applications

Aims & Scope

Statistical Methods and Applications (SMA), the official Journal of the Italian Statistical Society, is an international journal aiming at promoting the development of statistical methodology and its applications in the biological, demographic, economic, health, physical, social and other scientific domains.

SMA includes two sections: The first is devoted to statistical methodology and publishes original contributions in all fields of Statistics and, occasionally, critical reviews and discussions on recent developments in statistical theory and methods.

The second section of the journal publishes papers devoted to original and/or innovative applications of recent statistical methodology and complex approaches of statistical data analysis.

The journal is published four times a year.

SMA provides a forum for the presentation of Italian and international research on methods that are of central interest to modern statistics.

Discussions on methodological foundations and methods that have broad applications will be welcome and preferred.

View Aims & Scope

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Metrics & Ranking

SJR (SCImago Journal Rank)

Year	Value
2024	0.411

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	36

Impact Factor

Year	Value
2024	1.10

Journal Rank

Year	Value
2024	13544

Journal Citation Indicator

Year	Value
2024	244

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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.

• Influence functions of the Spearman and Kendall correlation measures

  Citation: 484

  Authors: Christophe, Catherine

• Multivariate functional outlier detection

  Citation: 133

  Authors: Mia, Peter J., Pieter

• Small area estimation: the EBLUP estimator based on spatially correlated random area effects

  Citation: 110

  Authors: Monica, Nicola

• Bayesian inference for categorical data analysis

  Citation: 109

  Authors: Alan, David B.

• Fuzzy measures of the incidence of relative poverty and deprivation: a multi-dimensional perspective

  Citation: 91

  Authors: Gianni, Vijay

• Cross-validation methods in principal component analysis: A comparison

  Citation: 88

  Authors: Giancarlo, Chiara

• Model-based clustering and classification with non-normal mixture distributions

  Citation: 79

  Authors: Sharon X., Geoffrey J.

• Robust analysis of bibliometric data

  Citation: 78

  Authors: Francesca, Silvia

• Multivariate Markov switching dynamic conditional correlation GARCH representations for contagion analysis

  Citation: 78

  Authors: Monica, Massimiliano

• Modelling time series of counts with overdispersion

  Citation: 74

  Authors: Christian H.

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