Development of parsimonious nonlinear models

Background

Many complex problems have complex solutions. However, the difficulty lays in development of solutions that are nor similar in complexity with the problem itself, but significantly simpler. In this project, simplicity is represented by parsimony, booth at model stage and data input stage.

Objective

Solving complex problems with simple models

Publications

• Seminal paper: Strimbu, B. M., A. Amarioarei, and M. Paun. 2017. A parsimonious approach for modeling uncertainty within complex nonlinear relationships. Ecosphere 8(9):e01945. 10.1002/ecs2.1945
• Strimbu BM, Amarioarei A, McTague JP, Paun M 2018. A posteriori bias correction of three models used for environmental reporting. Forestry 91(1): 49-62
• Strimbu, B.M. (2012) Correction for bias of models with lognormal distributed variables in absence of original data. Annals of Forest Research 55(2): 265-279