Uses a fitted model to augment the response variable with fitted values and residuals. Response residuals (back-transformed) are stored in the .resid column, while innovation residuals (transformed) are stored in the .innov column.

# S3 method for mdl_df
augment(x, ...)

# S3 method for mdl_ts
augment(x, type = NULL, ...)

Arguments

x

A mable.

...

Arguments for model methods.

type

Deprecated.

Examples

library(fable)
library(tsibbledata)

# Forecasting with an ETS(M,Ad,A) model to Australian beer production
aus_production %>%
  model(ets = ETS(log(Beer) ~ error("M") + trend("Ad") + season("A"))) %>% 
  augment()
#> # A tsibble: 218 x 6 [1Q]
#> # Key:       .model [1]
#>    .model Quarter  Beer .fitted .resid    .innov
#>    <chr>    <qtr> <dbl>   <dbl>  <dbl>     <dbl>
#>  1 ets    1956 Q1   284    267.  17.0   0.0111  
#>  2 ets    1956 Q2   213    224. -10.6  -0.00899 
#>  3 ets    1956 Q3   227    236.  -9.02 -0.00713 
#>  4 ets    1956 Q4   308    303.   4.62  0.00264 
#>  5 ets    1957 Q1   262    272.  -9.61 -0.00643 
#>  6 ets    1957 Q2   228    218.   9.96  0.00830 
#>  7 ets    1957 Q3   236    234.   2.34  0.00183 
#>  8 ets    1957 Q4   320    306.  13.6   0.00761 
#>  9 ets    1958 Q1   272    273.  -1.49 -0.000974
#> 10 ets    1958 Q2   233    225.   7.90  0.00637 
#> # … with 208 more rows