Jump to ContentJump to Main Navigation
Navigate here

Dependence Modeling: Contributions in Multivariate Predictive Analytics

    ◄ Back to journal 

EDITED BY

Peng Shi, University of Wisconsin-Madison
Emiliano A. Valdez, University of Connecticut

DESCRIPTION

Dependence Modeling will publish a special issue devoted to “Contributions in Multivariate Predictive Analytics” with the plan to have it published in June 2018. Multivariate predictive analytics involve using statistical techniques to jointly analyze and predict multiple dependent or correlated outcomes. The primary quantity of interest is a multivariate random outcome with components modeled simultaneously. Applications are found in various disciplines such as actuarial science, risk management, economics and finance, and epidemiology.

Both original research contributions and survey papers are welcome. 

Topics related to multivariate predictive analytics include, but not limited to, the following:

  • Copula regression
  • Multivariate count data
  • Longitudinal data
  • Vector time series analysis
  • Spatial statistics
  • Linear and non-linear mixed models
  • Hierarchical or multilevel models
  • Multivariate extremes

HOW TO SUBMIT

All submissions to the special issue must be made electronically at http://www.editorialmanager.com/depmod/ and will undergo the standard peer review process.

When submitting your paper please choose “SI: Contributions in Multivariate Predictive Analytics”.

There are no publication fees for this Special Issue.

Submissions for the special issue are now open. The deadline for the submissions is November 15, 2017 but individual papers will be reviewed and published online on an ongoing basis.

Contributors to the Topical Issue will benefit from:

  • Fair and constructive peer review provided by experts in the field,
  • Open Access to your article for all interested readers,
  • Fast online publication of articles,
  • No publication fees,
  • Free language assistance for authors from non-English speaking regions;

We are looking forward to your submission. If you have any question, please contact us at demo.editorial@degruyter.com