I have a dataset of approximate counts of birds of 5 species. I wrote a function to calculate the diversity of species using Broullions Index. My data looks like this and my function is written like this:
df <- data.frame(
sp1 = c(2, 3, 4, 5),
sp2 = c(1, 6, 7, 2),
sp3 = c(1, 9, 4, 3),
sp4 = c(2, 2, 2, 4),
sp5 = c(3, 3, 2, 1),
treatment1 = c("A", "B", "C", "A"),
treatment2 = c("D", "E", "D", "E")
)
#write function that estimates Broullion's Index
Brillouin_Index <- function(x){
N <- sum(x)
(log10(factorial(N)) - sum(log10(factorial(x)))) / N
}
df2 <- df %>%
mutate(bindex = Brillon_Index(matrix(df[1:5,])
How do apply my function to calculate the Broullions Index across rows? I thought something like the above would work but no luck yet. The point would be to use the diversity index as the response variable in relation to treatment 1 and 2 which is why I'd like to sum across rows and get a single value across for each row for a new variable called bindex. Any help will be greatly appreciated. Best,
We can use rowwise to group by row
library(dplyr)
df <- df %>%
rowwise %>%
mutate(bindex = Brillouin_Index(as.matrix(c_across(1:5)))) %>%
ungroup
-output
df
# A tibble: 4 x 8
# sp1 sp2 sp3 sp4 sp5 treatment1 treatment2 bindex
# <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <chr> <dbl>
#1 2 1 1 2 3 A D 0.464
#2 3 6 9 2 3 B E 0.528
#3 4 7 4 2 2 C D 0.527
#4 5 2 3 4 1 A E 0.505
Or use apply in base R
df$bindex <- apply(df[1:5], 1, Brillouin_Index)
df$bindex
#[1] 0.4643946 0.5277420 0.5273780 0.5051951
Or with dapply in collapse
library(collapse
df$bindex <- dapply(slt(df, 1:4), Brillouin_Index, MARGIN = 1)