Special Issue on Statistical Modeling and Computation

Statistical Modeling and Computation is widely used in modern research throughout the natural and social sciences, medicine, government, and commerce. It emphasizes the use of models to untangle and quantify variation in observed data. By a deft and concise use of computing coupled with an innovative geometrical presentation of the relationship among variables, this fresh approach reveals the logic of statistical inference. As one of most important roles in the statistical research, statistical modeling and computation is of great attractions to researchers.

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

• Probability models
• Generalized linear model
• Multivariate statistics model
• Bayesian model
• Markov chain model
• State-space model
• Gaussian models
• Monte Carlo methods
• Modern statistical computation techniques

Authors should read over the journal’s Authors’ Guidelines 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 - Statistical Modeling and Computation” 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