Nested for loops using row lags and multipliers defined in loop - r

Question

End goal is to take a dataframe and create a new column based on multiplication and addition of prior rows, i.e. if my multipliers are 0.1, 0.2, and 0.3, my addition is z + [lag(z) * 0.1] ,then I want to take column Z and transform it 3 times as such (skipping the first row):
z <- 1:4*10
df <- data.frame(z)
Z
Z_0.1
Z_0.2
Z_0.3
10
10
10
10
20
21
22
23
30
32.1
34.4
36.9
40
43.21
46.88
51.07
I have been able to get the correct values by manually feeding in the rate and overwriting the existing column:
for (i in 1:nrow(df)) {
if (i ==1)
df[i,1] <- df[i,1]
else
df[i,1] <- df[i,1] + (df[i-1,1] * 0.1)
}
Separately, I can also create column placeholders for the new values:
for (i in seq(0.1, 0.3, by = 0.1)) {
cola <- paste('col', i, sep = "_")
df[[cola]] <- 0
}
However, I cannot seem to combine these loops and get the outcome in the above sample table. I have tried this:
for (i in 1:nrow(df2)) {
for (j in seq(0.1, 0.3, by = 0.1)) {
cola <- paste('col', j, sep = "_")
df[[cola]] <- 0
if (i ==1)
df[[cola]] <- df[i,1]
else
df[[cola]] <- df[i,1] + (df[i-1,1] * j)
}
}
But it fills all the new columns with the same values for the whole column
Z
Z_0.1
Z_0.2
Z_0.3
10
77.02
81.85
86.68
20
77.02
81.85
86.68
30
77.02
81.85
86.68
40
77.02
81.85
86.68
Appreciate any suggestions. I'm not married to for loops if anyone has an alternative suggestion.

Answer 1

Like this maybe?
Z <- 1:4*10
y <- seq(0.1, 0.3, by = 0.1)
df <- data.frame(Z)
for (i in 1:(length(Z)-1)+1){
for (j in seq_along(y)){
df[1,paste0('Z_', y[j])] = Z[1]
df[i, paste0('Z_', y[j])] = Z[i]+(df[i-1, paste0('Z_', y[j])]*y[j])
}
}
df
#> Z Z_0.1 Z_0.2 Z_0.3
#> 1 10 10.00 10.00 10.00
#> 2 20 21.00 22.00 23.00
#> 3 30 32.10 34.40 36.90
#> 4 40 43.21 46.88 51.07
Created on 2022-09-09 by the reprex package (v2.0.1)