Event study for multiple firms and multiple dates with for loop

I'm doing an event study with the evReturn function from the erer package. The purpose is to get abnormal returns for each firm and average abnormal returns over all firms. I can't get the average returns because the function does a seperate execution for each firm but doesn't do one for all firms at once although this is possible with a for loop. I can't seem to get the right loop.

I've tried this method:

1.

install.packages("erer")
library(erer)
i <- 1
hh2 <- list()
for(i in 1:3){
  firms <- names(dataset4)[i+1]
  dates <- eventdates2[i]
  print(firms)
  print(dates)
  print(i)
  hh2[[i]] <- 
    evReturn(y=dataset4, firm = firms, event.date=dates, y.date="Timestamp",
             index="NASDAQ", event.win = 3, est.win= 250, digits=4)
}

Example from package erer, daEsa is a dataset included in the package.

# event analysis for one firm and one event window
hhreturn <- evReturn(y = daEsa, firm = "wpp", y.date = "date", 
index = "sp500", est.win = 250, digits = 3, event.date = 19990505, 
event.win = 5) 

# event analysis for many firms and one event window
hh2return2 <- update(hhreturn, firm = c("tin", "wy", "pcl", "pch"))

# event analysis for many firms and many event windows: need a for loop

This last comment is what I need.

Multiple dates:

hh2 <- list()
for(i in c(daEsa$date[3000], daEsa$date[3001])){
  firms <- colnames(daEsa)[12:ncol(daEsa)]
  print(firms)
  print(i)
  hh2[[i]] <- 
    evReturn(y=daEsa, firm = firms, event.date=i, y.date="date",
             index="sp500", event.win = 2, est.win= 250, digits=4)
}

Multiple event windows (not dates):

hh2 <- list()
for(i in c(2, 3)){
  firms <- colnames(daEsa)[12:ncol(daEsa)]
  print(firms)
  print(i)
  hh2[[i]] <- 
    evReturn(y=daEsa, firm = firms, event.date=daEsa$date[3000], y.date="date",
             index="sp500", event.win = i, est.win= 250, digits=4)
}

[1] "pch" "pcl" "pop" "tin" "wpp" "wy" 
[1] 2
[1] "pch" "pcl" "pop" "tin" "wpp" "wy" 
[1] 3