我是R(和编程)的新手,我必须为216种不同的产品做出简单的指数平滑预测。
示例:
items <- dataset
Date A B C
01-10 3 1 7
02-10 4 2 0
03-10 9 2 1
04-10 8 1 3
我得到了:
for(i in 1:ncol(items)) {
col <- ts(items[,i])
fcast <- ses(col, h=12)
write.table(fcast, file ="test.csv",sep=";", dec=",")
}
Error: not compatible with REALSXP
我做错了什么,还是我走在正确的轨道上?...请帮帮我
答案 0 :(得分:0)
这应该有效:
# library("forecast")
for(i in 1:ncol(items)) {
col <- ts(items[,i])
fcast <- ses(col, h=12)
write.table(fcast, file =paste("test", i, ".csv", sep="") ,sep=";", dec=",")
}
Althogh我的代码没有任何错误。
我的示例item
是data.frame
看dput
输出:
structure(list(Date = structure(1:4, .Label = c("01-10", "02-10",
"03-10", "04-10"), class = "factor"), A = c(3L, 4L, 9L, 8L),
B = c(1L, 2L, 2L, 1L), C = c(7L, 0L, 1L, 3L)), .Names = c("Date",
"A", "B", "C"), class = "data.frame", row.names = c(NA, -4L))
其中第一列为factor
,其他列为integer