Special Issue on Computational Statistics and Data Analysis

Computational Statistics is a cross subject of mathematical statistics, computational mathematics and computer science. It is the area of computational science specific to the mathematical science of statistics. Data Analysis refers to the process of collecting and analyzing the large amount of data by appropriate statistical analysis, extracting useful information and forming a conclusion.

In this special issue, we intend to invite front-line researchers and authors to submit original researches and review articles on exploring Computational Statistics and Data Analysis. Potential topics include, but are not limited to:

• Functional data analysis
• Mixed effects models, generalized linear models and random effects models
• Scientific visualization
• Decision trees
• Variance reduction techniques
• Extreme value theory
• Genetic algorithm, EM algorithm and MCMC algorithm

Authors should read over the journal’s For Authors carefully before submission. Prospective authors should submit an electronic copy of their complete manuscript through the journal’s Paper Submission System.

Please kindly notice that the “Special Issue” under your manuscript title is supposed to be specified and the research field “Special Issue – Computational Statistics and Data Analysis” should be chosen during your submission.

According to the following timetable:

Guest Editor:

For further questions or inquiries

Please contact Editorial Assistant at

ojs@scirp.org