add.distribution problem with KST()

hello, i am totally new to quantstrat and R so if my code might not be as "sexy" as it could. But feel free to mention parts where my code is redundant or if you have tips I am greatful for anything
I basically tried to do a strategy with KST() and that works fine but the optimization doesnt.
For the KST() i need 4 different ROC
`nROC = c(10, 15, 20, 30)`
then 4 different SMA that smooth the corresponding ROC
`n = c(10,10,10,15)`
4 weights for each SMA
`wts = 1:4`
this produces the KST line
and lastly one SMA that makes the signal line
`nSig = 9`
so what i want is totest for different combinations of values but I cant figure out how
I tried the optimization only for values of n to see if it works but instead of getting 4 different SMA for my 4 different ROC it only works with the same SMA for all ROC
also I get

> Warning message:
> In xtfrm.data.frame(x) : cannot xtfrm data frames
greatful for any help
```
my code
library(quantstrat)
library(dplyr)
library(data.table)
library(DT)
library(ggplot2)
library(htmltools)
library(htmlwidgets)
library(knitr)
library(lattice)
library(pander)
#kernvariablen
init_date<-"2017-12-31"
start_date<-"2018-01-01"
end_date<-Sys.Date()
initEq<-10000
currency("USD")
adjustment<-TRUE
currency("USD")
Sys.setenv(TZ = "UTC")

basic_symbols<-function(){
symbols<-c(
#"FUTY",
"XLY"#,
# "VAW",
#"PTH"
)
}

portfolio.st<-"Port.KST"
account.st<-"Acct.KST"
strategy.st<-"Strat.KST"

#symbols<-c("XLY")

symbols<-basic_symbols()
getSymbols(Symbols = symbols,
from= start_date,
to= end_date,
index.class="POSIXct")
stock(symbols,
currency = "USD",
multiplier = 1)

rm.strat(portfolio.st)
rm.strat(account.st)
rm.strat(strategy.st)

initPortf(name = portfolio.st,
symbols = symbols,
initDate = init_date)
initAcct(name = account.st,
portfolios = portfolio.st,
initDate = init_date,
initEq = initEq)
initOrders(portfolio = portfolio.st,
symbols = symbols,
initDate = init_date)
strategy(strategy.st,
store = TRUE)

add.indicator(strategy = strategy.st,
name = "KST",
arguments = list(price = quote(Cl(mktdata)),
n = c(10,10,10,15),
nROC = c(10, 15, 20, 30),
nSig = 9,
maType = "SMA",
wts = 1:4),
label = "kst")
add.signal(strategy =strategy.st,
name = "sigCrossover",
arguments = list(
columns =c("signal","kst"),
relationship="gte"),
label = "long")
add.signal(strategy.st,
name = "sigCrossover",
arguments = list(columns =c("signal","kst"),
relationship="lt"),
label = "short")
add.rule(strategy = strategy.st,
name = "ruleSignal",
arguments = list(sigcol="long",
sigval=TRUE,
orderqty=100,
ordertype="stoplimit",
orderside="long",
threshold=0.0005,
prefer="High",
TxmFees=-10,
replace=FALSE),
type = "enter",
label = "EnterLONG")
add.rule(strategy = strategy.st,
name = "ruleSignal",
arguments = list(sigcol="short",
sigval=TRUE,
orderqty=-100,
ordertype="stoplimit",
orderside="short",
threshold=-0.005,
prefer="Low",
TxmFees=-10,
replace=FALSE),
type = "enter",
label = "EnterLONG")
add.rule(strategy = strategy.st,
name = "ruleSignal",
arguments = list(sigcol="short",
sigval=TRUE,
orderside="short",
ordertype="market",
orderqty="all",
TynFees=-10,
replace=TRUE),
type = "exit",
label = "Exit2SHORT")
add.rule(strategy = strategy.st,
name = "ruleSignal",
arguments = list(sigcol="long",
sigval=TRUE,
orderside="short",
ordertype="market",
orderqty="all",
TynFees=-10,
replace=TRUE),
type = "exit",
label = "Exit2LONG")

checkBlotterUpdate <- function(port.st = portfolio.st,
account.st = account.st,
verbose = TRUE) {

ok <- TRUE
p <- getPortfolio(port.st)
a <- getAccount(account.st)
syms <- names(p$symbols)
port.tot <- sum(
sapply(
syms,
FUN = function(x) eval(
parse(
text = paste("sum(p$symbols",
x,
"posPL.USD$Net.Trading.PL)",
sep = "$")))))

port.sum.tot <- sum(p$summary$Net.Trading.PL)

if(!isTRUE(all.equal(port.tot, port.sum.tot))) {
ok <- FALSE
if(verbose) print("portfolio P&L doesn't match sum of symbols P&L")
}

initEq <- as.numeric(first(a$summary$End.Eq))
endEq <- as.numeric(last(a$summary$End.Eq))

if(!isTRUE(all.equal(port.tot, endEq - initEq)) ) {
ok <- FALSE
if(verbose) print("portfolio P&L doesn't match account P&L")
}

if(sum(duplicated(index(p$summary)))) {
ok <- FALSE
if(verbose)print("duplicate timestamps in portfolio summary")

}

if(sum(duplicated(index(a$summary)))) {
ok <- FALSE
if(verbose) print("duplicate timestamps in account summary")
}
return(ok)
}

cwd <- getwd()

results_file <- paste("results", strategy.st, "RData", sep = ".")
if( file.exists(results_file) ) {
load(results_file)
} else {
results <- applyStrategy(strategy.st, portfolios = portfolio.st)
updatePortf(portfolio.st)
updateAcct(account.st)
updateEndEq(account.st)
if(checkBlotterUpdate(portfolio.st, account.st, verbose = TRUE)) {
save(list = "results", file = results_file)
save.strategy(strategy.st)
}
}
setwd(cwd)

tstats <- tradeStats(portfolio.st)
kable(t(tstats))
###########################

.kstDistr <- matrix(c(10:12,10:12,10:12,15:17),4,3)

library(parallel)

if( Sys.info()['sysname'] == "Windows") {
library(doParallel)
registerDoParallel(cores=detectCores())
} else {
library(doMC)
registerDoMC(cores=detectCores())
}
#Add Distribution
add.distribution(strategy.st,
paramset.label = "KST",
component.type = "indicator",
component.label = "kst",
variable = list(n = .kstDistr),
label = "kst")

set.seed(20201312)
.nsamples <-5
rm(results)
results <- apply.paramset(strategy.st,
paramset.label = "KST",
portfolio.st = portfolio.st,
account.st = account.st,
nsamples = .nsamples,
verbose = TRUE)
```

Start with the reproduced add.distribution call using variable = list(n = .kstDistr), then follow the apply.paramset invocation in the issue code. Check how the KST indicator arguments are passed during optimization and trace the xtfrm.data.frame warning; done means the four smoothing values can be varied independently without the warning.

Written by the indexing model from the issue text.