Computational Statistics & Data Analysis - Impact Factor

Computational Statistics & Data Analysis - Elsevier | 2024 Impact Factor:1.6 | Cite Score:3.3 | Q1

Computational Statistics & Data Analysis Journal

Impact Factor and Journal Rank of Computational Statistics & Data Analysis

About: The ACM Journal on Computing and Cultural Heritage (JOCCH) is a peer-reviewed publication dedicated to research at the intersection of computing and cultural heritage. It focuses on technological advancements and applications that contribute to the preservation, analysis, interpretation, and presentation of cultural heritage.
Objective:
JOCCH aims to provide a platform for researchers, practitioners, and professionals to publish high-quality research papers, case studies, and reviews that advance the state-of-the-art in computing technologies applied to cultural heritage. It promotes interdisciplinary collaboration between computer scientists, archaeologists, historians, conservators, and cultural heritage professionals.
Focus Areas:
The journal covers a wide range of topics including, but not limited to: Digital preservation of cultural artifacts and monuments 3D modeling and visualization of cultural heritage sites Virtual and augmented reality applications in cultural heritage Machine learning and AI for artifact analysis and interpretation Data mining and information retrieval for cultural heritage collections Digital libraries and archives for cultural heritage materials Computer graphics and multimedia technologies in cultural heritage Digital storytelling and interactive experiences in cultural heritage
Impact:
The ACM Journal on Computing and Cultural Heritage contributes significantly to the advancement of cultural heritage research and technology. It facilitates the development of innovative solutions that enhance preservation, access, and understanding of cultural artifacts and sites.
Significance:
The journal is significant for its role in bridging the gap between computing technologies and cultural heritage preservation and dissemination. It supports the development of best practices and standards in digital preservation and encourages the use of advanced computational methods to unlock new insights into cultural heritage.

Journal Home: Journal Homepage

Editor-in-Chief: Ana Maria Colubi

Scope: The journal encompasses various fields within statistics, including but not limited to:
Biometrics and Biostatistics: Statistical methods in biological and medical sciences, including clinical trials, epidemiology, and genetics.
Econometrics: Statistical techniques applied to economic data analysis, forecasting, and modeling.
Data Analysis: Methods for exploring, analyzing, and interpreting data from various domains, including exploratory data analysis, statistical inference, and data visualization.
Computational Methods: Algorithms, computational techniques, and simulations used in statistical analysis and modeling.
Knowledge-Based Systems: Applications of statistical methods in artificial intelligence, machine learning, and expert systems.
Bayesian Computing: Bayesian statistical methods and computational approaches for Bayesian inference and modeling.
Graphics and Visualization: Techniques for graphical representation of data, including statistical graphics, data-driven storytelling, and interactive visual analytics.
Simulation: Monte Carlo simulations, stochastic processes, and simulation-based inference methods.
Algorithms and Software: Development and implementation of statistical algorithms, software tools, and computational environments for statistical analysis.