Generates residuals and fitted values of a fitted gamFit object.
Usage
# S3 method for class 'gamFit'
augment(x, ...)Examples
library(dplyr)
library(tibble)
library(tidyr)
library(tsibble)
# Simulate data
n = 1005
set.seed(123)
sim_data <- tibble(x_lag_000 = runif(n)) |>
mutate(
# Add x_lags
x_lag = lag_matrix(x_lag_000, 5)) |>
unpack(x_lag, names_sep = "_") |>
mutate(
# Response variable
y = (0.9*x_lag_000 + 0.6*x_lag_001 + 0.45*x_lag_003)^3 + rnorm(n, sd = 0.1),
# Add an index to the data set
inddd = seq(1, n)) |>
drop_na() |>
select(inddd, y, starts_with("x_lag")) |>
# Make the data set a `tsibble`
as_tsibble(index = inddd)
# Predictors taken as non-linear variables
s.vars <- colnames(sim_data)[3:6]
# Predictors taken as linear variables
linear.vars <- colnames(sim_data)[7:8]
# Model fitting
gamModel <- model_gam(data = sim_data,
yvar = "y",
s.vars = s.vars,
linear.vars = linear.vars)
# Obtain residuals and fitted values
augment(gamModel)
#> # A tibble: 1,000 × 3
#> Index .resid .fitted
#> <int> <dbl> <dbl>
#> 1 6 -0.392 0.959
#> 2 7 -0.219 0.985
#> 3 8 0.515 3.10
#> 4 9 -0.166 1.41
#> 5 10 -0.0998 1.01
#> 6 11 0.356 3.23
#> 7 12 -0.0723 1.92
#> 8 13 -0.0837 1.38
#> 9 14 0.238 2.25
#> 10 15 -0.134 0.283
#> # ℹ 990 more rows