我有一个月度时间序列 - monthlyTs：
monthlyTs <- ts(all.xts , frequency = 12, start=decimal_date(ymd("2012-01-29")))
head(index(monthlyTs))
1“2012-01-29 00:00:00 UTC”“2012-02-26 01:22:47 UTC”“2012-03-25 02:45:35 UTC“”2012-04-29 04:29:04 UTC“ [5]“2012-05-27 05:51:52 UTC”“2012-06-24 07:14:39 UTC”
我想应用从2013年开始的时间窗口：
head(window(monthly, start = 2013))
2012-01-29 00:00:00 2
2012-02-26 01:22:47 8 2012-03-25 02:45:35 6 2012-04-29 04:29:04 5 2012-05-27 05:51:52 4 2012-06-24 07:14:39 4
所以看起来像窗口函数没有按预期过滤。有什么问题？
根据要求提供完全可重复的示例：
christmas.csv - tiny CSV file (google trends for 'Christmas' request)
#Reading data from the csv. Format - [week start date], [views per week]
data = read.csv('christmas.csv', sep=",", header = FALSE, skip = 3,col.names = c("Week","Views"))[[2]]
# creating time series
myTs <- ts(data[[2]], freq=365.25/7, start=decimal_date(ymd("2012-01-29")))
#converting from weekly to month time series
all.xts <- xts(myTs, date_decimal(index(myTs)))
monthlyTs <- ts(all.xts , frequency = 12, start=decimal_date(ymd("2012-01-29")))
head(window(monthlyTs, start = 2013))
2012-01-29 00:00:00 2
2012-02-26 01:22:47 8 2012-03-25 02:45:35 6 2012-04-29 04:29:04 5 2012-05-27 05:51:52 4 2012-06-24 07:14:39 4
答案 0 :(得分：1)
有两个问题：
all.xts是每周而非每月时间对于第二点，尝试使用
更改函数start调用中为参数ts传递的值
c(lubridate::year("2012-01-29"), lubridate::month("2012-01-29"))
并将频率更改为值12.即使用以下行：
ts(all.xts , frequency = 12, start = c(lubridate::year("2012-01-29"), lubridate::month("2012-01-29")) )
使用dput的输出，您的代码重写如下：
data <- c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 4L, 5L, 5L, 6L, 8L, 11L, 16L, 22L, 33L, 42L,
45L, 55L, 64L, 8L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 5L, 6L, 8L,
12L, 16L, 21L, 27L, 43L, 47L, 56L, 79L, 10L, 5L, 2L, 2L, 2L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L,
3L, 3L, 4L, 5L, 5L, 6L, 8L, 12L, 17L, 21L, 27L, 43L, 47L, 53L,
87L, 12L, 5L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 5L, 6L, 6L, 8L, 13L,
17L, 20L, 27L, 44L, 50L, 54L, 100L, 15L, 6L, 3L, 2L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L,
3L, 4L, 5L, 5L, 6L, 8L, 11L, 16L, 21L, 29L, 43L, 48L, 53L, 80L,
46L, 8L, 3L, 2L)
myTs <- ts(data, freq=365.25/7, start=decimal_date(ymd("2012-01-29")))
all.xts <- xts::xts(myTs, date_decimal(index(myTs)))
monthlyTs <- ts(all.xts , frequency = 12, start = c(lubridate::year("2012-01-29"), lubridate::month("2012-01-29")) )
window(monthlyTs, start= c(2013))
最后一行将打印出来：
> window(monthlyTs, start= c(2013))
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2013 1 1 1 1 1 1 1 1 1 1 1 1
2014 1 1 1 1 2 2 2 2 3 3 3 4
2015 5 5 6 8 11 16 22 33 42 45 55 64
2016 8 4 2 2 2 2 2 2 1 1 1 1
2017 1 1 1 1 1 1 1 1 1 1 1 1
2018 1 1 1 1 1 1 1 2 2 2 2 2
2019 3 3 3 4 4 5 6 8 12 16 21 27
2020 43 47 56 79 10 5 2 2 2 1 1 1
2021 1 1 1 1 1 1 1 1 1 1 1 1
2022 1 1 1 1 1 1 1 1 1 1 2 2
2023 2 2 2 2 3 3 3 4 5 5 6 8
2024 12 17 21 27 43 47 53 87 12 5 2 2
2025 2 1 1 1 1 1 1 1 1 1 1 1
2026 1 1 1 1 1 1 1 1 1 1 1 1
2027 1 2 2 2 2 2 2 2 3 3 3 4
2028 5 6 6 8 13 17 20 27 44 50 54 100
2029 15 6 3 2 2 1 1 1 1 1 1 1
2030 1 1 1 1 1 1 1 1 1 1 1 1
2031 1 1 1 1 1 1 2 2 2 2 2 2
2032 3 3 3 4 5 5 6 8 11 16 21 29
2033 43 48 53 80 46 8 3 2