Next, let's consider how to profile the memory utilization of R code.
One approach is to use Rprof() by setting the memory.profiling argument and the corresponding memory argument to summaryRprof():
Rprof("Rprof-mem.out", memory.profiling=TRUE)
y <- sampvar(x)
Rprof(NULL)
summaryRprof("Rprof-mem.out", memory="both")
## $by.self
## self.time self.pct total.time total.pct mem.total
## "sq.var" 4.16 54.88 5.40 71.24 1129.4
## "my.sum" 1.82 24.01 2.18 28.76 526.9
## "^" 0.56 7.39 0.56 7.39 171.0
## "+" 0.44 5.80 0.44 5.80 129.2
## "-" 0.40 5.28 0.40 5.28 140.2
## "(" 0.20 2.64 0.20 2.64 49.7
##
## $by.total
## total.time total.pct mem.total self.time self.pct
## "sampvar" 7.58 100.00 1656.2 0.00 0.00
## "sq.var" 5.40 71.24 1129.4 4.16 54.88
##...