How to apply custom function to vector accumulation in R? In an efficient and idiomatic way?

Alessandro Jacopson

I know a function in cumsumR that computes the cumulative sum of its vector arguments.

I need the "cumulative apply" not a summation function, but a "generic" function, which in my specific case is the quantilefunction.

My current solution is based on a loop:

set.seed(42)
df<-data.frame(measurement=rnorm(1000),upper=0,lower=0)
for ( r in seq(1,nrow(df))){
  df$upper[r]<-quantile(df[seq(1,r),"measurement"],c(.99))
  df$lower[r]<-quantile(df[seq(1,r),"measurement"],c(.01))
}

x=seq(1,nrow(df))
plot(df$measurement,type="l",col="grey")
lines(x,df$upper,col="red")
lines(x,df$lower,col="blue")

enter image description here

It works, but it's not very efficient and I think there should be a more idiomatic approach in R.

Sven Hornstein

You can use this method:

set.seed(42)
df <- data.frame(measurement = rnorm(1000))

res <- sapply(seq(nrow(df)), function(x) 
  quantile(df[seq(x), "measurement"], c(.01, .99)))

It creates a matrix with nrow(df)two and two rows , the first row is the first percentile, and the first row is the ninety-ninth percentile.

You can add this information to the dataframe df(as two columns):

df <- setNames(cbind(df, t(res)), c(names(df), "lower", "upper"))

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