Our World Statistics Day conversations have been a great reminder of how much statistics can inform our lives. Do you have an example of how statistics has made a difference in your life? Share your story with the Community!
Choose Language Hide Translation Bar

Understand Wild Lemurs’ Soil Consumption Using Regularized Linear Models in JMP® ( US 2018 142 )

Jiangeng Huang, PhD Candidate in Statistics, Virginia Tech
Brandon Semel, PhD Candidate in Fish & Wildlife Conservation, Virginia Tech

Mitch Irwin, Department of Anthropology, Northern Illinois University

Jessica Rothman, Department of Anthropology, Hunter College of the City University of New York

 

Level: Intermediate


In this study, we sought to explain the function of soil consumption in critically endangered wild lemur populations based on nutritional data collected from four groups of diademed sifakas (Propithecus diadema).  These groups of lemurs inhabited continuous and fragmented forests in central-eastern Madagascar across five seasons. Biological data in nutritional studies proposes many challenges including multiple variables, multicollinearity between variables and a relatively small number of observations. Advances in regularized linear models, such as elastic net, enabled us to select important features and estimate these effects in one step, addressing the challenge of multicollinearity by combining lasso and ridge regressions at the same time. Here, we use the regularized regression function in JMP to reveal several important variables that help explain the soil consumption behavior of wild lemurs.

 

Discovery Lemur_Page_02.jpgDiscovery Lemur_Page_03.jpgDiscovery Lemur_Page_04.jpgDiscovery Lemur_Page_05.jpgDiscovery Lemur_Page_06.jpgDiscovery Lemur_Page_07.jpgDiscovery Lemur_Page_08.jpgDiscovery Lemur_Page_09.jpgDiscovery Lemur_Page_10.jpgDiscovery Lemur_Page_11.jpgDiscovery Lemur_Page_12.jpg