Abstract
Graduate students in economics are often introduced to some very useful mathematical tools that many outside the discipline may not associate with training in economics. This essay looks at some of these tools and concepts, including constrained optimization, separating hyperplanes, supporting hyperplanes, and ‘duality.’ Applications of these tools are explored including topics from machine learning and bioinformatics.
Disciplines
Agricultural and Resource Economics | Applied Statistics
Recommended Repository Citation
Bogard, Matt, "Mathematical Themes in Economics, Machine Learning, and Bioinformatics" (2010). Economics Faculty Publications. Paper 4.
https://digitalcommons.wku.edu/econ_fac_pub/4
COinS