Question

我想用decompose，ets或stl或任何函数分解每小时的时间序列。这是一个示例代码及其输出：

require(xts)
require(forecast)
time_index1 <- seq(from = as.POSIXct("2012-05-15 07:00"),
                   to = as.POSIXct("2012-05-17 18:00"), by="hour")
head(time_index1 <- format(time_index1, format="%Y-%m-%d %H:%M:%S",
                           tz="UTC", usetz=TRUE)
# [1] "2012-05-15 05:00:00 UTC" "2012-05-15 06:00:00 UTC"
# [3] "2012-05-15 07:00:00 UTC" "2012-05-15 08:00:00 UTC"
# [5] "2012-05-15 09:00:00 UTC" "2012-05-15 10:00:00 UTC"
head(time_index <- as.POSIXct(time_index1))
# [1] "2012-05-15 05:00:00 CEST" "2012-05-15 06:00:00 CEST"
# [3] "2012-05-15 07:00:00 CEST" "2012-05-15 08:00:00 CEST"
# [5] "2012-05-15 09:00:00 CEST" "2012-05-15 10:00:00 CEST"

为什么time_index的时区会改回CEST？

set.seed(1)
value <- rnorm(n = length(time_index1))
eventdata1 <- xts(value, order.by = time_index)
tzone(eventdata1)
# [1] ""
head(index(eventdata1))
# [1] "2012-05-15 05:00:00 CEST" "2012-05-15 06:00:00 CEST"
# [3] "2012-05-15 07:00:00 CEST" "2012-05-15 08:00:00 CEST"
# [5] "2012-05-15 09:00:00 CEST" "2012-05-15 10:00:00 CEST"
ets(eventdata1)
# ETS(A,N,N) 
# 
# Call:
#  ets(y = eventdata1) 
# 
#   Smoothing parameters:
#     alpha = 1e-04 
# 
#   Initial states:
#     l = 0.1077 
# 
#   sigma:  0.8481
# 
#      AIC     AICc      BIC 
# 229.8835 230.0940 234.0722
decompose(eventdata1)
# Error in decompose(eventdata1) : 
#   time series has no or less than 2 periods
stl(eventdata1)
# Error in stl(eventdata1) : 
#   series is not periodic or has less than two periods

当我致电tzone或indexTZ时，没有时区，但index清楚地表明时间是用时区定义的。

另外，为什么只有ets有效？它可以用来分解时间序列吗？

Answer 1

为什么time_index的时区会改回CEST？

因为您在调用tz=时没有指定as.POSIXct。如果它是从UTC的偏移量（例如-0800）指定的话，它将仅从字符串中获取时区。请参阅?strptime。

R> head(time_index <- as.POSIXct(time_index1, "UTC"))
[1] "2012-05-15 12:00:00 UTC" "2012-05-15 13:00:00 UTC"
[3] "2012-05-15 14:00:00 UTC" "2012-05-15 15:00:00 UTC"
[5] "2012-05-15 16:00:00 UTC" "2012-05-15 17:00:00 UTC"

当我致电tzone或indexTZ时，没有时区，但index清楚地表明时间是用时区定义的。

所有POSIXct对象都有一个时区。时区""仅表示R无法确定特定时区，因此它使用操作系统指定的时区。请参阅?timezone。

只有ets函数有效，因为您的xts对象没有正确定义的frequency属性。这是xts对象的已知限制，我计划在接下来的几个月内解决它们。您可以在调用xts构造函数后显式指定frequency属性来解决当前问题。

R> set.seed(1)
R> value <- rnorm(n = length(time_index1))
R> eventdata1 <- xts(value, order.by = time_index)
R> attr(eventdata1, 'frequency') <- 24  # set frequency attribute
R> decompose(as.ts(eventdata1))  # decompose expects a 'ts' object

Answer 2

您可以使用tbats来分解每小时数据：

require(forecast)
set.seed(1)
time_index1 <- seq(from = as.POSIXct("2012-05-15 07:00"),
               to = as.POSIXct("2012-05-17 18:00"), by="hour")
value <- rnorm(n = length(time_index1))
eventdata1 <- msts(value, seasonal.periods = c(24) )
seasonaldecomp <- tbats(eventdata1)
plot(seasonaldecomp)

此外，使用msts代替xts可以指定多个季节/周期，例如每小时和每天：c(24, 24*7)

xts每小时时间序列分解

2 个答案: