I am maximizing a likelihood function and trying to reduce the loop. I want to add the vector(parameters to be estimated) to all rows of a matrix (data). The length of vecto
We can use col
to replicate the 'a' elements
b + a[col(b)]
# [,1] [,2] [,3] [,4] [,5]
#[1,] 2 3 1 1 1
#[2,] 2 3 1 1 1
#[3,] 2 3 1 1 1
#[4,] 2 3 1 1 1
#[5,] 2 3 1 1 1
#[6,] 2 3 1 1 1
Or a faster option would be to use rep
b + rep(a, each = nrow(b))
Or use sweep
sweep(b, 2, a, "+")
set.seed(24)
b <- matrix(sample(0:9, 8000*5000, replace=TRUE), ncol=5000)
a <- sample(0:3, 5000, replace=TRUE)
system.time(b + a[col(b)])
# user system elapsed
# 1.08 0.06 1.14
system.time(b + rep(a, each = nrow(b)))
# user system elapsed
# 0.83 0.03 0.86
system.time(t(a+t(b)))
# user system elapsed
# 1.14 0.03 1.17
system.time(sweep(b, 2, a, "+"))
# user system elapsed
# 0.62 0.06 0.69
These solutions using outer()
or collapse::TRA()
are is significantly faster than using rep
or sweep
.