Add residuals to a data frame

add_residuals(data, model, var = "resid")

spread_residuals(data, ...)

gather_residuals(data, ..., .resid = "resid", .model = "model")

Arguments

data: A data frame used to generate the residuals
model, var: add_residuals takes a single model; the output column will be called resid
...: gather_residuals and spread_residuals take multiple models. The name will be taken from either the argument name of the name of the model.
.resid, .model: The variable names used by gather_residuals.

Value

A data frame. add_residuals adds a single new column, .resid, to the input data. spread_residuals adds one column for each model. gather_predictions adds two columns .model and .resid, and repeats the input rows for each model.

Examples

df <- tibble::tibble(
  x = sort(runif(100)),
  y = 5 * x + 0.5 * x ^ 2 + 3 + rnorm(length(x))
)
plot(df)


m1 <- lm(y ~ x, data = df)
df %>% add_residuals(m1)
#> # A tibble: 100 × 3
#>           x     y   resid
#>       <dbl> <dbl>   <dbl>
#>  1 0.000104 2.57  -0.0803
#>  2 0.00402  4.38   1.71  
#>  3 0.0148   3.00   0.264 
#>  4 0.0160   2.81   0.0618
#>  5 0.0287   0.697 -2.12  
#>  6 0.0309   3.22   0.386 
#>  7 0.0349   2.08  -0.782 
#>  8 0.0367   2.55  -0.318 
#>  9 0.0384   1.13  -1.75  
#> 10 0.0469   5.88   2.95  
#> # ℹ 90 more rows

m2 <- lm(y ~ poly(x, 2), data = df)
df %>% spread_residuals(m1, m2)
#> # A tibble: 100 × 4
#>           x     y      m1      m2
#>       <dbl> <dbl>   <dbl>   <dbl>
#>  1 0.000104 2.57  -0.0803 -0.248 
#>  2 0.00402  4.38   1.71    1.54  
#>  3 0.0148   3.00   0.264   0.113 
#>  4 0.0160   2.81   0.0618 -0.0876
#>  5 0.0287   0.697 -2.12   -2.26  
#>  6 0.0309   3.22   0.386   0.252 
#>  7 0.0349   2.08  -0.782  -0.911 
#>  8 0.0367   2.55  -0.318  -0.446 
#>  9 0.0384   1.13  -1.75   -1.88  
#> 10 0.0469   5.88   2.95    2.84  
#> # ℹ 90 more rows
df %>% gather_residuals(m1, m2)
#> # A tibble: 200 × 4
#>    model        x     y   resid
#>    <chr>    <dbl> <dbl>   <dbl>
#>  1 m1    0.000104 2.57  -0.0803
#>  2 m1    0.00402  4.38   1.71  
#>  3 m1    0.0148   3.00   0.264 
#>  4 m1    0.0160   2.81   0.0618
#>  5 m1    0.0287   0.697 -2.12  
#>  6 m1    0.0309   3.22   0.386 
#>  7 m1    0.0349   2.08  -0.782 
#>  8 m1    0.0367   2.55  -0.318 
#>  9 m1    0.0384   1.13  -1.75  
#> 10 m1    0.0469   5.88   2.95  
#> # ℹ 190 more rows