nested ifelse calculations in R -

i relatively new r , finding nested ifelse functionality not behave expect. begin, info used input function:

loss_cor_df<-data.frame(from_1=c(0,.4,0), to_1=c(0,.5,0),                      from_2=c(0,.55,0), to_2=c(0,.65,0),                       from_3=c(0,.75,0), to_3=c(0,.85,0)                      )  loss_cor_dol<-100*loss_cor_df  loss_cor_rate_df<-data.frame(rate_1=c(0,0.5,0), rate_2=c(0,0.75,0), rate_3=c(0,1,0)) 

my function:

apply_lc<- function(x, lc, rate)  {ifelse(x>=lc$from_3, -rate$rate_1*(min(x,lc$to_1) - lc$from_1) - rate$rate_2*(min(x,lc$to_2)-lc$from_2) - rate$rate_3*(min(x,lc$to_3)-lc$from_3), ifelse(x>=lc$from_2,  -rate$rate_1*(min(x,lc$to_1) - lc$from_1) - rate$rate_2*(min(x,lc$to_2)-lc$from_2),     ifelse(x>=lc$from_1, -rate$rate_1*(min(x,lc$to_1) - lc$from_1),     0))) } 

if apply scalar, expected result.

> apply_lc(85,loss_cor_dol[2,], loss_cor_rate_df[2,]) [1] -22.5 

however, when attempt following, no longer correct answer.

> apply_lc(c(85,80),loss_cor_dol[2,], loss_cor_rate_df[2,]) [1] -17.5 -17.5 

i able use loops , "other" if...else function. however, performance reasons hoping vectorize operation. "apply" family did not seem work inputs function may vary every column in data. suspect have fundamental misunderstanding way in r interprets information , appreciate asssitance.