Doing more with GAMs

Nonlinear Modeling with Generalized Additive Models (GAMs) in R

Noam Ross

Senior Research Scientist, EcoHealth Alliance

Chapter 1

  • GAM theory
  • Fitting GAMs
  • Mixing linear and nonlinear terms

Chapter 2

  • Interpreting GAMs
  • Visualizing GAMs
  • Model-checking and concurvity

Chapter 3

  • 2-D Interactions and spatial data
  • Interactions with different scales
  • Continuous-categorical interaction

Chapter 4

  • Logistic GAMs
  • Plotting logistic outputs
  • Making predictions
Nonlinear Modeling with Generalized Additive Models (GAMs) in R

GAMs and the Tidyverse

library(broom)

augment(gam_model)
tidy(gam_model)
glance(gam_model)

library(caret)

train(x, y, method = "gam", ...)
Nonlinear Modeling with Generalized Additive Models (GAMs) in R

Other types of smooths

?smooth.terms
Nonlinear Modeling with Generalized Additive Models (GAMs) in R

Other types of outcomes/distributions

?family.mgcv

See Generalized Linear Models

Nonlinear Modeling with Generalized Additive Models (GAMs) in R

Variable selection

?gam.selection
Nonlinear Modeling with Generalized Additive Models (GAMs) in R

Complex model structures

?gam.models

See Hierarchical and Mixed Effects Models

Nonlinear Modeling with Generalized Additive Models (GAMs) in R

Thank You!

Nonlinear Modeling with Generalized Additive Models (GAMs) in R

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