Welcome to the repository for sparse learning website
Next Available Date: August 15, 2025
Time: 8am-11am
Venue: Ecological Society of America (ESA) annual meeting in Baltimore, Maryland
Cost: $35 fee imposed by ESA, not Modelscapes or the presenters
Unlock the power of ecological insights in the era of big data! Massive ecological datasets are being generated more frequently and inexpensively than ever before. However, datasets with far more predictors (P) than observations (N) pose serious challenges for traditional statistical methods, often resulting in overfitting, poor predictive performance, and inaccurate variable selection. Sparse modeling approaches that constrain the number of potential predictors in a model offer a potential way forward for the analysis of datasets with P»N, and can lead to better out-of-sample prediction using distilled models that might better reflect the true processes affecting the response. Join our interactive workshop tailored for ecologists across all levels, where you’ll delve into cutting-edge techniques using intuitive R packages to harness, analyze, and interpret big ecological datasets. This workshop will provide an introductory course on sparse modeling techniques followed by a live-coding lesson in R, where participants will create their own scripts for the SuSiE (susieR) and lasso (glmnet) approaches. Participants will walk away from this course with a firm understanding of several sparse modeling approaches and their usefulness, as well as methods for implementing, visualizing, and interpreting these modeling approaches in R.
How to sign up: When you register for the SFS annual meeting, look under “Add Ons/ Pre-Conference Workshops”, and add “Introduction to Sparse Modeling in R” to your cart. If you have already registered for the meeting and want to add this workshop, log into your meeting registration, select the “Registration” tab and scroll down to “Add Ons/ Pre-Conference Workshops”. There, find “Introduction to Sparse Modeling in R” and click “add”; then proceed to check out.
Workshop code repository: https://github.com/apatt76/IntroductionToSparseModelingInR
Post-workshop survey: https://umt.co1.qualtrics.com/jfe/form/SV_acaQ7zuqT1BvalM
Note: This workshop is supported by the Modelscapes Consortium, a joint collaboration between the University of Wyoming, the University of Montana, and the University of Nevada Reno.