Affirm Journal of Computational Statistics

Affirm Journal of Computational Statistics is an international and peer-reviewed journal with an intercontinental advisory board. The journal documents the professional’s interest in any areas that connect to computational statistics. The focus of the journal is on theories and practice in applications of computational statistics, computational bayesian methods, computer science methods, explicit impact of computers on statistical methodology and modeling and simulation. The editorial board of the Affirm Journal of Computational Statistics invites authors to submit original papers, empirical studies, case studies and review papers to the journal. At Affirm Journal of Computational Statistics, we expect the authors to abide Principles of Transparency and Best Practice in Scholarly Publishing suggested by The Committee on Publication Ethics (COPE), the Directory of Open Access Journals (DOAJ), the Open Access Scholarly Publishers Association (OASPA), and Scopus.

Scope and Focus

Applications of Computational Statistics
Artificial Intelligence
Biostatistics and Bioinformatics
Computational Bayesian Methods
Computationally Intensive Statistical Methods
Computer Science Methods
Data Mining
Data Structures
Data Visualization
Development, Evaluation and Validation of Statistical Software and Algorithms
Explicit Impact of Computers on Statistical Methodology
Graphical Statistics
Machine Learning
Modeling and Simulation
Numerical Analysis
Special Applications
Statistical Methodology for Data Analysis

Editor in chief

Dr. Loghman

Abstracting and Indexing

Google Scholar