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Visualizing auto performance uncertainty

Confidence intervals are a very important visual indicator of model fit. Here you'll practice changing the appearance of confidence intervals and transforming the scale of partial effects plots.

This exercise is part of the course

Nonlinear Modeling with Generalized Additive Models (GAMs) in R

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Exercise instructions

  • Plot the model (mod) that uses the mpg data, plotting only the partial effect of weight. Make the confidence interval shaded and "hotpink" in color.
  • Make another plot of the weight partial effect, this time shifting the scale by the value of the intercept using the shift argument, and including the uncertainty of the model intercept using the seWithMean argument.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

library(mgcv)
# Fit the model
mod <- gam(hw.mpg ~ s(weight) + s(rpm) + s(price) + comp.ratio, 
           data = mpg, method = "REML")

# Plot the weight effect with colored shading
plot(mod, select = 1, ___)

# Make another plot adding the intercept value and uncertainty
plot(mod, select = 1, ___)
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