lm - How to predict something in R given two specifications? -


i have large data set. here example of of it.

                          car sport suv wagon minivan pickup awd rwd  msrp invoice enginesize cylinders  hp city.mpg hwy.mpg weight           chevrolet aveo 4dr     0   0     0       0      0   0   0 11690   10965        1.6         4 103       28      34   2370  chevrolet aveo ls 4dr hatch     0   0     0       0      0   0   0 12585   11802        1.6         4 103       28      34   2348       chevrolet cavalier 2dr     0   0     0       0      0   0   0 14610   13697        2.2         4 140       26      37   2617       chevrolet cavalier 4dr     0   0     0       0      0   0   0 14810   13884        2.2         4 140       26      37   2676    chevrolet cavalier ls 2dr     0   0     0       0      0   0   0 16385   15357        2.2         4 140       26      37   2617            dodge neon se 4dr     0   0     0       0      0   0   0 13670   12849        2.0         4 132       29      36   2581

what want predict horsepower of sports car 3.5-liter engine. not sure start. have made these models finding horsepower of sports car.

sportfilter <- cars$sport==1 hpmodelsport <- lm(cars$hp[sportfilter] ~ cars$enginesize[sportfilter])

and engine size.

hpmodel <- lm(hp ~ enginesize, data = cars)

but how use both of these. , engine size model general, how specify 3.5-liter?

assuming trying predict hp based on enginesize , sport can following:

cars <- read.table("d:/downloads/04cars.csv", header =t, sep =",", stringsasfactors = false) fit <- lm(hp ~ enginesize + sport , data=cars) vals <-  data.frame(enginesize = 3.5, sport = 1) predict(fit, newdata=vals)

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