Extract a named dataframe from a function in R - r

Question

I have created the following function that I need to extract some information from. However, R is giving me some issues.
HAC.sim <- function(K = 1, N, Hstar, probs, perms = 10000){
specs <- 1:N
### Set up a container to hold the identity of each individual from each permutation
pop <- array(dim = c(c(perms, N), K))
### Create an ID for each haplotype
haps <- as.character(1:Hstar)
### Assign probabilities of occurrence to each haplotype, ensure they sum to 1
### This is where we assume we "know" the distribution of haplotypes
### Here, I have assumed they all occur with equal frequency, but you can change this to assume some dominant ones and some rare ones, whatever you want
probs <- rep(1/Hstar, Hstar)
# probs <- c(220/N, rep(3/N, 2), rep(2/N, 2), rep(1/N, 10))
### Generate permutations, we assume each permutation has N individuals, and we sample those individuals' haplotypes from our probabilities
# If K > 1, haplotypes are partitioned into equally-sized subpopulations/demes
# Can change number of haplotypes in each subpopulation and re-run simulation
# For each additional, K, add new Ki and new pop[j ,, i] in loop
for(j in 1:perms){
for(i in 1:K){
if(i == 1){
pop[j, specs, i] <- sample(haps, size = N, replace = TRUE, prob = probs)
}
else{
pop[j ,, 1] <- sample(haps[K1], size = N, replace = TRUE, prob = probs[K1])
pop[j ,, 2] <- sample(haps[K2], size = N, replace = TRUE, prob = probs[K2])
}
}
}
### Make a matrix to hold the 1:N individuals from each permutation
HAC.mat <- array(dim = c(c(perms, N), K))
for(k in specs){
for(j in 1:perms){
for(i in 1:K){
ind.index <- sample(specs, size = k, replace = FALSE) ## which individuals will we sample
hap.plot <- pop[sample(1:nrow(pop), size = 1, replace = TRUE), ind.index, sample(1:K, size = 1, replace = TRUE)] ## pull those individuals from a permutation
HAC.mat[j, k, i] <- length(unique(hap.plot)) ## how many haplotypes did we get for a given sampling intensity (k) from each ### permutation (j)
}
}
}
### Calculate the mean and CI for number of haplotypes at each sampling intensity (j)
means <- apply(HAC.mat, MARGIN = 2, mean)
lower <- apply(HAC.mat, MARGIN = 2, function(x) quantile(x, 0.025))
upper <- apply(HAC.mat, MARGIN = 2, function(x) quantile(x, 0.975))
### Plot the curve and frequency barplot
par(mfrow = c(1, 2))
for(i in 1:K){
if(i == 1){
plot(specs, means, type = "n", xlab = "Specimens sampled", ylab = "Unique haplotypes", ylim = c(1, Hstar))
polygon(x = c(specs, rev(specs)), y = c(lower, rev(upper)), col = "gray")
lines(specs, means, lwd = 2)
HAC.bar <- barplot(N*probs, xlab = "Unique haplotypes", ylab = "Specimens sampled", names.arg = 1:Hstar)
}
else{
plot(specs, means, type = "n", xlab = "Specimens sampled", ylab = "Unique haplotypes", ylim = c(1, max(HAC.mat)))
polygon(x = c(specs, rev(specs)), y = c(lower, rev(upper)), col = "gray")
lines(specs, means, lwd = 2)
HAC.bar <- barplot(N*probs[get(paste0("K", i))], xlab = "Unique haplotypes", ylab = "Specimens sampled", names.arg = get(paste0("K",i)))
}
}
d <- data.frame(specs, means)
## Measures of Closeness ##
list(c(cat("\n Number of haplotypes sampled: " , max(means))
cat("\n Number of haplotypes not sampled: " , Hstar - max(means))
cat("\n Proportion of haplotypes sampled: " , max(means)/Hstar)
cat("\n Proportion of haplotypes not sampled: " , (Hstar - max(means))/Hstar)), d)
}
HAC.sim(K = 1, N = 100, Hstar = 10)
I would like to be able to easily extract the data frame 'd' from the above function.
I need to pass d to a regression model object.
The output gives me almost what I need except there is a [[1]] appended to the end of the value of (Hstar - max(means))/Hstar), instead of on a new line. Plus, [[1]] is a NULL list object. Why am I getting this NULL list as an output, and how can I fix the problem?
Any help is appreciated.