Plots the glide path for the coefficients for a PrestoGP model.

This method generates a plot showing the coefficients of the model for different values of the tuning parameter. It is a wrapper for plot.glmnet.

Usage

# S4 method for class 'PrestoGPModel'
plot_beta(model, ...)

Arguments

model

The PrestoGP model object

...

Additional parameters to plot.glmnet

References

• Messier, K.P. and Katzfuss, M. "Scalable penalized spatiotemporal land-use regression for ground-level nitrogen dioxide", The Annals of Applied Statistics (2021) 15(2):688-710.

See also

PrestoGPModel-class, prestogp_fit, plot.glmnet

Examples

data(soil)
soil <- soil[!is.na(soil[,5]),] # remove rows with NA's
y <- soil[,4]                   # predict moisture content
X <- as.matrix(soil[,5:9])
locs <- as.matrix(soil[,1:2])

soil.vm <- new("VecchiaModel", n_neighbors = 10)
soil.vm <- prestogp_fit(soil.vm, y, X, locs)
#> 
#> Estimating initial beta... 
#> Estimation of initial beta complete 
#> 
#> Beginning iteration 1 
#> Estimating theta... 
#> Estimation of theta complete 
#> Estimating beta... 
#> Estimation of beta complete 
#> Iteration 1 complete 
#> Current penalized negative log likelihood: 487.2212 
#> Current MSE: 9.104869 
#> Beginning iteration 2 
#> Estimating theta... 
#> Estimation of theta complete 
#> Estimating beta... 
#> Estimation of beta complete 
#> Iteration 2 complete 
#> Current penalized negative log likelihood: 487.1424 
#> Current MSE: 9.107437 
#> Beginning iteration 3 
#> Estimating theta... 
#> Estimation of theta complete 
#> Estimating beta... 
#> Estimation of beta complete 
#> Iteration 3 complete 
#> Current penalized negative log likelihood: 487.1424 
#> Current MSE: 9.107472 
plot_beta(soil.vm)