Here is a sample data as data2:
lvl x y
0 20.099 21.2
100 21.133 21.4
250 20.866 21.6
500 22.679 21.8
750 22.737 22.1
0 30.396 32.0
100 31.373 32.1
250 31.303 32.2
500 33.984 32.8
750 44.563 38.0
0 22.755 18.5
100 23.194 18.8
250 23.263 20.5
500 23.061 27.9
750 25.678 36.4
I tried to get the rmse and r2 for each level (lvl) by the following lines of codes:
data2 %>% group_by(lvl) %>% summarise_each(funs(rmse(data2$x~data2$y)))
and
summary(lm(data2$x,data2$y))$r.squared
respectively, and I got the following error message when calculating rmse:
Error: argument "obs" is missing, with no default
and
# A tibble: 5 x 3
lvl x y
<int> <dbl> <dbl>
1 0 0.6639888 0.6639888
2 100 0.6639888 0.6639888
3 250 0.6639888 0.6639888
4 500 0.6639888 0.6639888
5 750 0.6639888 0.6639888
when calculating r2.
I wanted to aggregate the rmse and r2 for each level. In this case, I have only 5 levels. So the answer will look like 5 rows X 3 columns with column names `"lvl", "rmse", "r2" Thank you in advance.
You don't need summarise_each summarise will do what you want. If you prefer using dplyr here is a solution
data2 <-
data.frame(
lvl = c( 0, 100, 250, 500, 750, 0, 100, 250, 500, 750, 0, 100, 250, 500, 750)
,x = c(
20.099, 21.133, 20.866, 22.679, 22.737, 30.396, 31.373, 31.303, 33.984, 44.563, 22.755, 23.194, 23.263, 23.061, 25.678
)
,y = c(21.2, 21.4, 21.6, 21.8, 22.1, 32.0, 32.1, 32.2, 32.8, 38.0, 18.5, 18.8, 20.5, 27.9, 36.4)
)
#install.packages("ModelMetrics")
library(ModelMetrics)
data2 %>%
group_by(lvl) %>%
summarise(
RMSE = rmse(x, y)
,R2 = cor(x, y)^2
)
## A tibble: 5 × 3
# lvl RMSE R2
# <dbl> <dbl> <dbl>
#1 0 2.701237 0.8176712
#2 100 2.575982 0.8645350
#3 250 1.729888 0.9091029
#4 500 2.920640 0.7207692
#5 750 7.267279 0.4542507