我的数据集是一个包含29个数据帧的列表，因此一个数据框如下所示：
>MergedData[[1]]
Date EUR.HIGH EUR.LOW EUR.CLOSE
1 2016-08-30 1.1192 1.1153 1.1161
2 2016-08-29 1.1208 1.1158 1.1189
3 2016-08-28 1.1341 1.1181 1.1198
4 2016-08-27 1.1341 1.1181 1.1198
5 2016-08-26 1.1341 1.1181 1.1198
6 2016-08-25 1.1298 1.1259 1.1285
7 2016-08-24 1.1312 1.1245 1.1264
因此，使用此列表，我在R中计算了“信号”，其值为-2,1和0.我希望R进行计算，并将它们保留在输出中，以获得值不为零的变量。这是我的信号在R中的样子：
>price.break
EUR JPY GBP CHF AUD CAD NZD SEK
2016-02-19 NA NA NA NA NA NA NA NA
2016-02-20 0 -2 0 0 -2 0 0 0
2016-02-21 0 0 0 0 0 0 0 0
>ma.sig
EUR JPY GBP CHF AUD CAD NZD SEK
2016-02-19 NA NA NA NA NA NA NA NA
2016-02-20 0 1 0 0 1 0 0 0
2016-02-21 0 0 0 0 0 0 0 0
由于我们已经知道JPY和AUD都返回了非零信号，我希望R计算一个如下所示的输出表：
Currency Deviation from MA RSI
JPY
AUD
这是我试图让R做到这一点的（相当可怕的）尝试：
new.trend <- function(x)
{
ret <- as.list(rep(NA, length(x)))
for (i in 1:length(MergedData)){
x <- MergedData[[i]]
x <- xts(x[,-1], order.by=x[,1])
ma.sig <- ma.crossover(x)
pricebreak <- price.channel(x)
sig.col <- col(x)[which(!ma.sig[,i]&ma.sig[,i-1)]==0)&which(!pricebreak[,i]&pricebreak[,i-1]==0)]
sig.row <- row(x)[which(!ma.sig[,i]&ma.sig[,i-1)]==0)&which(!pricebreak[,i]&pricebreak[,i-1]==0)]
ma20 <- SMA(x[sig.row, sig.col], n=20)
ma50 <- SMA(x[sig.row, sig.col], n=50)
RSI <- RSI(x[sig.row, sig.col], n=14)
dev20 <- x[sig.row, sig.col]-ma20[sig.row, sig.col]/x[sig.row, sig.col]*100
dev50 <- x[sig.row, sig.col]-ma50[sig.row, sig.col]/x[sig.row, sig.col]*100
ret[[i]] <- merge(RSI, 20dev, 50dev)
}
na.omit(do.call(merge,ret))
}
使用sig.col和sig.row，我希望提取确切的行/列号，以便有选择地计算我们得到非负信号的实例。我得到的错误是“错误的数字维度”，而且我有一种强烈的感觉，无论如何我正在做的事情是不正确的。
ma.crossover和pricebreak只是计算以下内容的函数：
ma.crossover<- function(MergedData){
ma <- as.list(rep(NA, length(MergedData)))
for(i in 1:length(MergedData)) {
x <- MergedData[[i]]
x <- xts(x[,-1], order.by=x[,1])
ma20 <- SMA(x[,3], n=20)
ma50 <- SMA(x[,3], n=50)
ma[[i]] <- sign(ma20 - ma50)
}
na.omit(do.call(merge, ma))
}
##price channel
price.channel <- function(MergedData)
{
ret <- as.list(rep(NA, length(MergedData)))
for (i in 1:length(MergedData)) {
x<- MergedData[[i]]
x <- xts(x[,-1], order.by=x[,1])
high <- runMax(x[,2], 20)
low <- runMin(x[,3], 20)
mid <- (high+low)/2
channel <- cbind(high, mid, low)
ret[[i]] <- merge(sign(high-x[,5]), sign(x[,5]-low))
}
na.omit(do.call(merge, ret))
}
我已经坚持了一段时间，因此非常感谢评论或反馈。这是我的输入样本，如果有帮助的话：
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