Country | Netherlands - | 103 H Index |

Subject Area and Category | Computer Science Computational Theory and Mathematics Mathematics Applied Mathematics Computational Mathematics Statistics and Probability | |

Publisher | Elsevier | |

Publication type | Journals | |

ISSN | 01679473 | |

Coverage | 1983-2020 | |

Scope | Computational Statistics and Data Analysis (CSDA), an Official Publication of the network Computational and Methodological Statistics (CMStatistics) and of the International Association for Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of four refereed sections which are divided into the following subject areas: I) Computational Statistics - Manuscripts dealing with: 1) the explicit impact of computers on statistical methodology (e.g., Bayesian computing, bioinformatics,computer graphics, computer intensive inferential methods, data exploration, data mining, expert systems, heuristics, knowledge based systems, machine learning, neural networks, numerical and optimization methods, parallel computing, statistical databases, statistical systems), and 2) the development, evaluation and validation of statistical software and algorithms. Software and algorithms can be submitted with manuscripts and will be stored together with the online article. II) Statistical Methodology for Data Analysis - Manuscripts dealing with novel and original data analytical strategies and methodologies applied in biostatistics (design and analytic methods for clinical trials, epidemiological studies, statistical genetics, or genetic/environmental interactions), chemometrics, classification, data exploration, density estimation, design of experiments, environmetrics, education, image analysis, marketing, model free data exploration, pattern recognition, psychometrics, statistical physics, image processing, robust procedures. [...] III) Special Applications - [...] IV) Annals of Statistical Data Science [...] | |

Join the conversation about this journal |

Quartiles

SJR

Citations per document

Total Cites Self-Cites

External Cites per Doc Cites per Doc

% International Collaboration

Citable documents Non-citable documents

Cited documents Uncited documents

Metrics based on Scopus® data as of April 2020

Loading comments...

Developed by:

Powered by:

Powered by:

Follow us on @ScimagoJR

Scimago Lab, Copyright 2007-2020. Data Source: Scopus®