Special Issue on Computational Statistics and Data Analysis

In statistics, a variable distribution is used to calculate helpful quantities, such as mean, variance, and standard deviation. However, when the distribution of a sample set is unknown, a sample mean and variation can be calculated based directly on the values of the number of samples taken. The goal of this special issue is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in the area of computational statistics and data analysis.

In this special issue, we intend to invite front-line researchers and authors to submit original research and review articles on exploring computational statistics and data analysis. In this special issue, potential topics include, but are not limited to:

• Resampling methods
• Markov chain monte carlo methods
• Local regression and kernel density estimation 
• Error and data processing
• Calculation of distribution functions and quantiles 
• Generation and verification of random Numbers
• Stochastic simulation method

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