make R program faster

Hi

there are some good tips in "The R Inferno"
http://www.burns-stat.com/documents/books/the-r-inferno/
or connect C++ to R with Rcpp
http://dirk.eddelbuettel.com/code/rcpp.html
or byte code compiler (library(compiler))
or library(data.table)

but do you have an idea to fasten standard R source code, with the 
following Rprof output

                 self.time self.pct total.time total.pct
[<-.data.frame       1.34    29.13       1.78     38.70
[.data.frame         0.26     5.65       1.02     22.17
[[                   0.12     2.61       0.44      9.57
NextMethod           0.12     2.61       0.12      2.61
match                0.10     2.17       0.16      3.48
<Anonymous>          0.10     2.17       0.10      2.17
c                    0.10     2.17       0.10      2.17
[[.data.frame        0.08     1.74       0.32      6.96
[.Date               0.06     1.30       0.10      2.17
FUN                  0.06     1.30       0.10      2.17
[<-                  0.04     0.87       1.82     39.57
[                    0.04     0.87       1.04     22.61
[<-.Date             0.04     0.87       0.18      3.91
vapply               0.04     0.87       0.14      3.04
%in%                 0.02     0.43       0.18      3.91
+                    0.02     0.43       0.10      2.17


It comes from a simulation algorithmus that calculates day wise values 
(values are depenend from the output of the day before). First I create 
a data.frame with NAs. Finally each row contains the daily values.

output <- as.data.frame(matrix(nrow = 365, ncol = 50))
for (day in (1:365)) {
   ...
   r <- list(Date=d,daylength=daylength,TempSum=tempsum, ...)
   output[day,] <- r
}

Is there an better (faster) way to do such things in R?

Greetings
Christof