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 singlemodel
;- var
The name of the output column, default value is
pred
- type
Prediction type, passed on to
stats::predict()
. Consultpredict()
documentation for givenmodel
to determine valid values.- ...
gather_predictions
andspread_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 2.814380
#> 2 0.1111111 3.441413
#> 3 0.2222222 4.068446
#> 4 0.3333333 4.695478
#> 5 0.4444444 5.322511
#> 6 0.5555556 5.949544
#> 7 0.6666667 6.576577
#> 8 0.7777778 7.203610
#> 9 0.8888889 7.830642
#> 10 1.0000000 8.457675
m2 <- lm(y ~ poly(x, 2), data = df)
grid %>% spread_predictions(m1, m2)
#> x m1 m2
#> 1 0.0000000 2.814380 2.358486
#> 2 0.1111111 3.441413 3.263516
#> 3 0.2222222 4.068446 4.098546
#> 4 0.3333333 4.695478 4.863576
#> 5 0.4444444 5.322511 5.558606
#> 6 0.5555556 5.949544 6.183635
#> 7 0.6666667 6.576577 6.738664
#> 8 0.7777778 7.203610 7.223693
#> 9 0.8888889 7.830642 7.638722
#> 10 1.0000000 8.457675 7.983750
grid %>% gather_predictions(m1, m2)
#> model x pred
#> 1 m1 0.0000000 2.814380
#> 2 m1 0.1111111 3.441413
#> 3 m1 0.2222222 4.068446
#> 4 m1 0.3333333 4.695478
#> 5 m1 0.4444444 5.322511
#> 6 m1 0.5555556 5.949544
#> 7 m1 0.6666667 6.576577
#> 8 m1 0.7777778 7.203610
#> 9 m1 0.8888889 7.830642
#> 10 m1 1.0000000 8.457675
#> 11 m2 0.0000000 2.358486
#> 12 m2 0.1111111 3.263516
#> 13 m2 0.2222222 4.098546
#> 14 m2 0.3333333 4.863576
#> 15 m2 0.4444444 5.558606
#> 16 m2 0.5555556 6.183635
#> 17 m2 0.6666667 6.738664
#> 18 m2 0.7777778 7.223693
#> 19 m2 0.8888889 7.638722
#> 20 m2 1.0000000 7.983750