Add predictions to a data frame

Usage

add_predictions(data, model, var = "pred", type = NULL)

spread_predictions(data, ..., type = NULL)

gather_predictions(data, ..., .pred = "pred", .model = "model", type = NULL)

Arguments

data: A data frame used to generate the predictions.
model: add_predictions takes a single model;
var: The name of the output column, default value is pred
type: Prediction type, passed on to stats::predict(). Consult predict() documentation for given model to determine valid values.
...: gather_predictions and spread_predictions take multiple models. The name will be taken from either the argument name of the name of the model.
.pred, .model: The variable names used by gather_predictions.

Value

A data frame. add_prediction adds a single new column, with default name pred, to the input data. spread_predictions adds one column for each model. gather_predictions

adds two columns .model and .pred, 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)
grid <- data.frame(x = seq(0, 1, length = 10))
grid %>% add_predictions(m1)
#>            x     pred
#> 1  0.0000000 2.989671
#> 2  0.1111111 3.599630
#> 3  0.2222222 4.209588
#> 4  0.3333333 4.819547
#> 5  0.4444444 5.429505
#> 6  0.5555556 6.039464
#> 7  0.6666667 6.649422
#> 8  0.7777778 7.259381
#> 9  0.8888889 7.869339
#> 10 1.0000000 8.479298

m2 <- lm(y ~ poly(x, 2), data = df)
grid %>% spread_predictions(m1, m2)
#>            x       m1       m2
#> 1  0.0000000 2.989671 2.953507
#> 2  0.1111111 3.599630 3.584332
#> 3  0.2222222 4.209588 4.209973
#> 4  0.3333333 4.819547 4.830430
#> 5  0.4444444 5.429505 5.445702
#> 6  0.5555556 6.039464 6.055791
#> 7  0.6666667 6.649422 6.660696
#> 8  0.7777778 7.259381 7.260416
#> 9  0.8888889 7.869339 7.854953
#> 10 1.0000000 8.479298 8.444306
grid %>% gather_predictions(m1, m2)
#>    model         x     pred
#> 1     m1 0.0000000 2.989671
#> 2     m1 0.1111111 3.599630
#> 3     m1 0.2222222 4.209588
#> 4     m1 0.3333333 4.819547
#> 5     m1 0.4444444 5.429505
#> 6     m1 0.5555556 6.039464
#> 7     m1 0.6666667 6.649422
#> 8     m1 0.7777778 7.259381
#> 9     m1 0.8888889 7.869339
#> 10    m1 1.0000000 8.479298
#> 11    m2 0.0000000 2.953507
#> 12    m2 0.1111111 3.584332
#> 13    m2 0.2222222 4.209973
#> 14    m2 0.3333333 4.830430
#> 15    m2 0.4444444 5.445702
#> 16    m2 0.5555556 6.055791
#> 17    m2 0.6666667 6.660696
#> 18    m2 0.7777778 7.260416
#> 19    m2 0.8888889 7.854953
#> 20    m2 1.0000000 8.444306