Climate, agriculture, and hunger: statistical prediction of undernourishment using nonlinear regression and data-mining techniques

DOI10.1080/02664763.2015.1032216OpenAlexW1996030127MaRDI QIDQ5130351

Julie E. Shortridge, Seth D. Guikema, Benjamin F. Zaitchik, Stefanie M. Falconi

Publication date: 4 November 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2015.1032216

zbMATH Keywords

data miningregressionclimatehungerfood securityundernourishment

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Bagging predictors
• BART: Bayesian additive regression trees
• Random forests
• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)

Related Items (1)

Climate change and U.S. agriculture: Accounting for multidimensional slope heterogeneity in panel data

Uses Software

• ElemStatLearn
• BartPy

This page was built for publication: Climate, agriculture, and hunger: statistical prediction of undernourishment using nonlinear regression and data-mining techniques

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q5130351)