我正在浏览以下pdf幻灯片（当前为24/42）：

http://www.r-programming.org/files/WFA.pdf

我最初看到的是与并行处理有关的错误（我正在使用Ubuntu），但是当我注释掉并行代码时，遇到了以下错误：

walk.forward（strategy.st = strat.st，paramset.label = “ BBOPT” ，： obj.func（）返回空结果此外：警告 消息：在max（x）中：没有max的所有必输参数；返回-Inf

我已经检查了代码，但似乎找不到错误。我知道代码来自2014年，此后对quantstrat软件包进行了一些更新。我不想使用并行处理来运行代码，我的目的只是让代码运行。

我从幻灯片中复制的代码：

library(quantstrat)
#library(xtsExtra)


stock.st = c("USO")

currency("USD")
stock(stock.st,currency = "USD",multiplier = 1)
Sys.setenc(TZ = "UTC")

initDate = "2006-12-31"
startDate = "2007-01-01"
endDate = "2013-12-31"

initEq = 1000000
tradeSize = initEq / 10

getSymbols(
  stock.st,from = startDate,to = endDate
)

myTheme <- chart_theme()
myTheme$col$dn.col <- "ligthblue"
myTheme$col$dn.border <- "lightgray"
myTheme$col$up.border <- "lightgray"


chart_Series(
  Ad(get(stock.st)),name = stock.st,theme = myTheme
  )

# order sizing function
osFixedDollar <- function(timestamp,orderqty,portfolio,symbol,ruletype){
  pos = getPosQty(portfolio,timestamp)
  if(isTRUE(all.equal(pos,0))){
    ClosePrice = as.numeric(Cl(mktdata[timestamp,]))
    orderqty = sign(orderqty) * round(tradeSize / ClosePrice,-2)
  } else {
    orderqty = 0
  }
  return(orderqty)
}

lineChart(USO["2010"])
addBBands(n = 20,sd = 2)

# define indicators and signals

strat.st <- "bbands"
rm.strat(strat.st)

strategy(strat.st,store = TRUE)

add.indicator(
  strategy = strat.st,name = "BBands",arguments = list(HLC = quote(HLC(mktdata)),maType = "SMA"),label = "BBands"
)

# create a signal when the close > upper BBand (only at the first cross over)
add.signal(
  strategy = strat.st,name = "sigCrossover",arguments = list(columns = c("Close","up"),relationship = "gt"),label = "Cl.gt.UpperBand"
)

# create a signal when the close is < the lower BBand (only at the first cross over)
add.signal(
  strategy = strat.st,"dn"),relationship = "lt"),label = "Cl.lt.LowerBand"
)

add.signal(
  strategy = strat.st,arguments = list(columns = c("High","Low","mavg"),relationship = "op"),# opposite side
  label = "Cross.Mid"
)

# Define the rules

add.rule(
  strategy = strat.st,name = "ruleSignal",arguments = list(
    sigcol = "Cl.gt.UpperBand",# enter a short when we are above the upper BBand
    sigval = TRUE,ORDERTQY = -100,ORDERTYPE = "market",orderside = NULL,threshold = NULL,osFUN = osFixedDollar,orderset = "ocoshort" # short side
    ),type = "enter",label = "SE"
)

add.rule(
  strategy = strat.st,arguments = list(
    sigcol = "Cl.lt.LowerBand",# enter a long when we are below the lower BBand
    sigval = TRUE,orderqty = 100,ordertype = "market",orderset = "ocolong"# long side
  ),label = "LE"
)


add.rule(
  strategy = strat.st,arguments = list(
    sigcol = "Cross.Mid",sigval = TRUE,orderqty = "all",threshold = NULL
  ),type = "exit"
)

# Define distributions

add.distribution(
  strategy = strat.st,paramset.label = "BBOPT",component.type = "indicator",component.label = "BBands",variable = list(n = seq(10,30,by = 5)),label = "n"                                 # n number of periods
)

add.distribution(
  strategy = strat.st,variable = list(sd = seq(1,3,by = 0.5)),label = "sd"                                # sd to test in each n periods
)

# Walk forward analysis
# This is a wrapper for apply.paramset() and applyStrategy()
# args(walk.forward)

# parallel processing
# if(Sys.info()["sysname"] == "Windows"){
#   library(doParallel)
# } else {
#   library(doMC)
#   registerDoMC(cores = detectCores())
# }



rm.strat("opt")

initPortf(
  name = "opt",stock.st,initDate = initDate
)

initacct(
  name = "opt",portfolios = "opt",initDate = initDate,initEq = initEq
)

initOrders(
  portfolio = "opt",initDate = initDate
)

?walk.forward
results <- walk.forward(
  strategy.st = strat.st,portfolio.st = "opt",account.st = "opt",period = "years",# unit of days,months or years etc.
  k.training = 4,# number of training periods
  k.testing = 1,# number of test periods
  nsamples = 0,# number of sample param.combos to draw - 0 means all samples
  obj.func = function(x) {     which(x == max(x)) },#obj.fun = NULL,# user provided function retuning the best para.combo
  #obj.args = NULL,# user provided argument to obj.func
  audit.prefix = "wfa",# prefix to generate filenames for storage of audit data
  anchored = FALSE,# whether to a fixed start or not for the trainijng window
  #include.insamples = NULL,# will run a full backtest for each param.combo in the paramset
  verbose = TRUE
)