我对R真的很陌生,我仍然试图围绕着()函数进行打包。我对我的数据(MergedData)的示例输入链接here(我对此长度表示歉意;我试图尽可能缩短它)。我工作的一个小项目,我有以下功能:将for()函数中的打印值保存为变量?
new.trend <- function(MergedData)
{
ret <- as.list(rep(NA, length(MergedData)))
ma.sig <- ma.crossover(MergedData)
pricebreak <- price.channel(MergedData)
sig <- intersect(which((ma.sig[1,])==1), which(!pricebreak[1,]==0))
for (i in sig) { #Calculates output variables based on active signals
x <- MergedData[[i]]
x <- xts(x[,-1], order.by=x[,1])
dev20 <- (x[,4]-SMA(x[,4], n=20))/x[,4]*100
dev50 <- (x[,4]-SMA(x[,4], n=50))/x[,4]*100
RSI <- RSI(x[,4], n=14)
ret[[i]]<- na.omit(merge(tail(dev20, n=1L), tail(dev50, n=1L), tail(RSI, n=1L)))
}
na.omit(print(ret))
}
print(new.trend(MergedData))
问题/问题
回报率(RET)将返回此:
> new.trend(MergedData)
[[1]]
EUR.LAST EUR.LAST.1 EMA
2017-02-09 -0.6968559 0.3526983 44.68176
[[2]]
[1] NA
[[3]]
GBP.LAST GBP.LAST.1 EMA
2017-02-09 -0.1920461 1.027927 52.27664
[[4]]
CHF.OPEN CHF.OPEN.1 EMA
2017-02-09 0.5066387 -0.7241689 52.56533
[[5]]
[1] NA
[[6]]
[1] NA
[[7]]
[1] NA
[[8]]
[1] NA
[[9]]
[1] NA
[[10]]
[1] NA
[[11]]
[1] NA
[[12]]
[1] NA
[[13]]
PLN.CLOSE PLN.CLOSE.1 EMA
2017-02-09 0.2824105 -1.569392 48.24069
[[14]]
[1] NA
[[15]]
TRY.CLOSE TRY.CLOSE.1 EMA
2017-02-09 -2.315328 -0.2501765 42.52731
[[16]]
ZAR.CLOSE ZAR.CLOSE.1 EMA
2017-02-09 -0.09598239 -1.492148 46.06286
[[17]]
[1] NA
[[18]]
CLP.CLOSE CLP.CLOSE.1 EMA
2017-02-09 -0.2433194 -2.112368 40.93616
[[19]]
[1] NA
[[20]]
MXN.CLOSE MXN.CLOSE.1 EMA
2017-02-09 -2.460443 -3.490762 34.67792
[[21]]
PEN.CLOSE PEN.CLOSE.1 EMA
2017-02-09 -0.4138617 -1.974541 37.84737
[[22]]
CNY.CLOSE CNY.CLOSE.1 EMA
2017-02-09 -0.08749199 -0.5004658 44.39283
[[23]]
IDR.CLOSE IDR.CLOSE.1 EMA
2017-02-09 -0.4064827 -0.631571 35.91677
[[24]]
INR.CLOSE INR.CLOSE.1 EMA
2017-02-09 -1.291429 -1.594705 21.83156
[[25]]
KRW.CLOSE KRW.CLOSE.1 EMA
2017-02-09 -0.8529425 -2.840274 34.61214
[[26]]
MYR.CLOSE MYR.CLOSE.1 EMA
2017-02-09 0.1407816 -0.4020273 49.80231
[[27]]
SGD.CLOSE SGD.CLOSE.1 EMA
2017-02-09 0.123548 -0.7103133 49.73621
[[28]]
PHP.CLOSE PHP.CLOSE.1 EMA
2017-02-09 0.1355443 0.236601 55.61772
[[29]]
THB.CLOSE THB.CLOSE.1 EMA
2017-02-09 -0.518655 -1.396926 23.51997
但我想检索for()函数中打印的内容,例如:
> for (i in sig) { #Calculates output variables based on active signals
+ x <- MergedData[[i]]
+ x <- xts(x[,-1], order.by=x[,1])
+ dev20 <- (x[,4]-SMA(x[,4], n=20))/x[,4]*100
+ dev50 <- (x[,4]-SMA(x[,4], n=50))/x[,4]*100
+ RSI <- RSI(x[,4], n=14)
+ print(ret[[i]]<- na.omit(merge(tail(dev20, n=1L), tail(dev50, n=1L), tail(RSI, n=1L))))
+ }- (x[,4]-SMA(x[,4], n=50))/x[,4]*100
RSI <- RSI(x[,4], n=14)
print(ret[[i]]<- na.omit(merge(tail(dev20, n=1L), tail(dev50, n=1L), tail(RSI, n=1L))))
}
EUR.LAST EUR.LAST.1 EMA
2017-02-09 -0.6968559 0.3526983 44.68176
GBP.LAST GBP.LAST.1 EMA
2017-02-09 -0.1920461 1.027927 52.27664
CHF.OPEN CHF.OPEN.1 EMA
2017-02-09 0.5066387 -0.7241689 52.56533
PLN.CLOSE PLN.CLOSE.1 EMA
2017-02-09 0.2824105 -1.569392 48.24069
TRY.CLOSE TRY.CLOSE.1 EMA
2017-02-09 -2.315328 -0.2501765 42.52731
ZAR.CLOSE ZAR.CLOSE.1 EMA
2017-02-09 -0.09598239 -1.492148 46.06286
CLP.CLOSE CLP.CLOSE.1 EMA
2017-02-09 -0.2433194 -2.112368 40.93616
MXN.CLOSE MXN.CLOSE.1 EMA
2017-02-09 -2.460443 -3.490762 34.67792
PEN.CLOSE PEN.CLOSE.1 EMA
2017-02-09 -0.4138617 -1.974541 37.84737
CNY.CLOSE CNY.CLOSE.1 EMA
2017-02-09 -0.08749199 -0.5004658 44.39283
IDR.CLOSE IDR.CLOSE.1 EMA
2017-02-09 -0.4064827 -0.631571 35.91677
INR.CLOSE INR.CLOSE.1 EMA
2017-02-09 -1.291429 -1.594705 21.83156
KRW.CLOSE KRW.CLOSE.1 EMA
2017-02-09 -0.8529425 -2.840274 34.61214
MYR.CLOSE MYR.CLOSE.1 EMA
2017-02-09 0.1407816 -0.4020273 49.80231
SGD.CLOSE SGD.CLOSE.1 EMA
2017-02-09 0.123548 -0.7103133 49.73621
PHP.CLOSE PHP.CLOSE.1 EMA
2017-02-09 0.1355443 0.236601 55.61772
THB.CLOSE THB.CLOSE.1 EMA
2017-02-09 -0.518655 -1.396926 23.51997
提示,建议和指针将不胜感激!我知道for()函数可能不是理想的,但它是我知道如何才能够遍历与sig中索引对应的MergedData值的唯一方法。
感谢您的建议,但出于某种原因,我仍然得到同样的结果na.omit(打印(RET) ) – Nikitau
我真的很感谢第二次尝试:),但它给了我“在[.xts'(x,!is.na(x))中出错:'i'或'j'超出范围。我也试过na.omit(do.call(ret,merge)),但它返回了一个空矩阵。 – Nikitau
嗯...我试图用dget加载数据,但R失败。你可以转储dput的数据intead吗? – kwicher