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r - 分解具有奇数起始月份的 ts

问题描述

目前，我尝试获取数据的季节性成分。为此，我从一组日期和值中创建了一个tsvia 。不幸的是，我的数据集从 2011-07-01 开始并运行到 2018-05-01（缺少我已经从库tk_ts中填充的数据）。padpadr

由于 a必须ts从 1 月 1 日开始，我无法使用 a 对这些数据进行建模。因此，我尝试从我的数据创建 a 并将其转换为 a ，但要么我无法使频率工作，要么数据已关闭。frequency = 12 tsxtsts

这是我的 MWE：

library(tidyquant)
library(timetk)

raw_data <- tibble(Date = c(as.Date("2011-07-01"), as.Date("2011-08-01"),
                   as.Date("2011-09-01"), as.Date("2011-10-01"),
                   as.Date("2011-11-01"), as.Date("2011-12-01"),
                   as.Date("2012-01-01"), as.Date("2012-02-01")),
                  Value = c(1,4,1,4,1,4,1,4))
                  # And so on, till 2018-05-01 and with reasonable values

tk_ts(raw_data, select = Value, start = 2011, frequency = 12)
# Leads to:
# 
#      Jan Feb Mar Apr May Jun Jul Aug
# 2011   1   4   1   4   1   4   1   4
#
# which is bad since my first date is 2011-07-01 not 2011-01-01.

xts_data <- xts(raw_data$Value, order.by = raw_data$Date, frequency = 12)
# xts_data Leads to, which is fine:
# 
# [,1]
# 2011-07-01    1
# 2011-08-01    4
# 2011-09-01    1
# 2011-10-01    4
# 2011-11-01    1
# 2011-12-01    4
# 2012-01-01    1
# 2012-02-01    4

as.ts(xts_data, start = start(xts_data), end = end(xts_data))
# Leads to:
# 
# Time Series:
# Start = 15156 
# End = 15371 
# Frequency = 1 
# [1] 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1
# [52] 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4
# [103] 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1
# [154] 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4
# [205] 1 4 1 4 1 4 1 4 1 4 1 4
#
# Which is totaly bad since there are more than the original 8 values.

as.ts(xts_data, start = start(xts_data))
# Leads to:
# 
# Time Series:
#   Start = 15156 
# End = 15163 
# Frequency = 1 
# [1] 1 4 1 4 1 4 1 4
#
# Which is bad since the Frequency is off
#  and I need it to be ok for the decompose.

as.ts(xts_data, start = start(xts_data), end = end(xts_data), frequency = 12)
# Leads to:
# 
# Error in ts(coredata(x), frequency = frequency(x), ...) : 
#   formal argument "frequency" matched by multiple actual arguments

attr(xts_data, 'frequency') <- 12
as.ts(xts_data, start = start(xts_data))
# Leads to:
# 
# Jan Feb Mar Apr May Jun Jul Aug
# 15156   1   4   1   4   1   4   1   4
#
# Which is as bad as the first example

那么，如何生成不是从 1 月 1 日开始的数据的分解（以获取季节性成分）？

标签： rtime-seriesxts

解决方案

您也可以尝试对start参数进行简单的添加，指定月份编号（在本例中为 07）。

raw_data <- tibble(Date = c(as.Date("2011-07-01"), as.Date("2011-08-01"),
                            as.Date("2011-09-01"), as.Date("2011-10-01"),
                            as.Date("2011-11-01"), as.Date("2011-12-01"),
                            as.Date("2012-01-01"), as.Date("2012-02-01")),
                   Value = c(1,4,1,4,1,4,1,4))
# And so on, till 2018-05-01 and with reasonable values

tk_ts(raw_data, select = Value, start = c(2011,07), frequency = 12)

这将产生以下输出：

tk_ts(raw_data, select = Value, start = c(2011,07), frequency = 12)
     Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2011                           1   4   1   4   1   4
2012   1   4

希望这有助于您在后续步骤中尝试实现的目标。

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