A wrapper for lm() for use in nadir::super_learner().
Arguments
- data
A dataframe to train a learner / learners on.
- formula
A regression formula to use inside this learner.
- weights
Observation weights; see
?lm- ...
Any extra arguments that should be passed to the internal model for model fitting purposes.
Value
A prediction function that accepts newdata,
which returns predictions (a numeric vector of values, one for each row
of newdata).
A prediction function that accepts newdata,
which returns predictions (a numeric vector of values, one for each row
of newdata).
Examples
lnr_lm(mtcars, mpg ~ hp + disp + am + wt)(mtcars)
#> Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
#> 24.458980 23.682060 25.912053 20.730852
#> Hornet Sportabout Valiant Duster 360 Merc 240D
#> 17.743239 20.098866 14.594537 22.417470
#> Merc 230 Merc 280 Merc 280C Merc 450SE
#> 21.226986 19.309094 19.309094 15.417569
#> Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
#> 16.453463 16.301125 11.327738 10.374500
#> Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
#> 9.975558 27.266451 29.591855 28.398918
#> Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
#> 23.183832 18.378027 18.602149 13.747022
#> Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
#> 16.608881 28.074586 26.569732 27.552200
#> Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
#> 17.202961 21.408619 13.067847 23.913739