【发布时间】:2017-12-14 23:38:53
【问题描述】:
我有一个类似于“df1”的数据框。将值列转换为每日时间序列后,我使用 Holt Winters 方法拟合并预测未来 120 天。我希望能够使用 dygraphs 可视化实际和预测。
library(dygraphs)
> head(df1)
timestamp value
1 2017-03-29 534.4571
2 2017-03-30 536.4350
3 2017-03-31 534.6661
4 2017-04-01 535.9185
5 2017-04-02 532.6998
6 2017-04-03 534.8282
convert_to_daily_ts <- function(x){
x <- x[order(x$timestamp),]
x$value_ts <- ts(x$value, frequency = 7)
return(x)
}
df1 <- convert_to_daily_ts(df1)
hw <- tryCatch(HoltWinters(df1$value_ts), error=NA)
p <- predict(hw, n.ahead = 120, prediction.interval = TRUE, level=0.95)
act <- df1$value_ts
all <- cbind(act, p)
> class(all)
[1] "mts" "ts" "matrix"
> head(all)
Time Series:
Start = c(1, 1)
End = c(1, 6)
Frequency = 7
actual p.fit p.upr p.lwr
1.000000 534.4571 NA NA NA
1.142857 536.4350 NA NA NA
1.285714 534.6661 NA NA NA
1.428571 535.9185 NA NA NA
1.571429 532.6998 NA NA NA
1.714286 534.8282 NA NA NA
> tail(all)
Time Series:
Start = c(115, 2)
End = c(115, 7)
Frequency = 7
actual p.fit p.upr p.lwr
115.1429 NA 386.2924 581.7568 190.8279
115.2857 NA 384.4614 580.0625 188.8603
115.4286 NA 383.4728 579.2104 187.7352
115.5714 NA 381.3159 577.1900 185.4418
115.7143 NA 383.3130 579.3234 187.3025
115.8571 NA 384.2098 580.3565 188.0631
> str(all)
mts [1:805, 1:4] 534 536 535 536 533 ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr [1:4] "actual" "p.fit" "p.upr" "p.lwr"
- attr(*, "tsp")= num [1:3] 1 116 7
- attr(*, "class")= chr [1:3] "mts" "ts" "matrix"
dygraph(all, main = "Daily Predictions") %>%
dySeries("act", label = "Actual") %>%
dySeries(c("p.lwr", "p.fit", "p.upr"), label = "Predicted") %>%
dyOptions(drawGrid = F) %>%
dyRangeSelector()
我得到Error:Unsupported type passed to argument 'data'. 但是'all' 类与dygraph 的预期一样。任何可视化上述数据(实际和预测)的帮助都会有所帮助。另外,我需要 x 轴值来显示月-年(例如:2017 年 6 月、2017 年 7 月)而不是 1、2、3 等等。有可能吗?
【问题讨论】:
-
str(all)长什么样子? -
@RyanMorton 添加了 str(all)
标签: arrays r time-series dygraphs timeserieschart