Special Issue on Statistical Modeling and Computation Research  

 

Statistical modeling and computation is an emerging discipline which blends statistics with computer science each other. It is widely used in modern research including in statistics, mathematics, actuarial Science, engineering, physics, and economics. It emphasizes the use of models to untangle and quantify variation in observed data. The goal of this Special Issue is to provide a platform for scientists worldwide to promote, share, and discuss various new issues and developments in the area of statistical modeling and computation.

 

In this special issue, we intend to invite front-line researchers and authors to submit original research and review articles on exploring statistical modeling and computation research. Potential topics include, but are not limited to:

• Probability models
• Random variables and probability distributions
• Regression models
• Generalized linear model
• Multivariate statistics model
• Bayesian model
• Markov chain model
• State-space model
• Gaussian model
• Statistical inference
• Advanced models and inference
• Applications

 

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 specify the “Special Issue” under your manuscript title. The research field “Special Issue - Statistical Modeling and Computation Research” should be selected during your submission.

 

Special Issue timetable:

Guest Editor:

Prof. Qihua Wang

Chinese Academy of Sciences, China

 

For further questions or inquiries

Please contact Editorial Assistant at

ojs@scirp.org