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我正在按照本教程使用扫描包对时间序列组执行整洁的时间序列预测。Sweep 扩展了 broom 包以整理预测对象。

教程在这里： https ://rdrr.io/cran/sweep/f/vignettes/SW01_Forecasting_Time_Series_Groups.Rmd

问题：我的数据中的时间序列包含不同的长度和开始日期。在本教程中，将固定开始传递给 tk_ts() 因为每个时间序列具有相同的开始和结束日期：

monthly_qty_by_cat2_ts <- monthly_qty_by_cat2_nest %>%
mutate(data.ts = map(.x       = data.tbl, 
                     .f       = tk_ts, 
                     select   = -order.month, 
                     start    = 2011, # <- see the fixed start date here
                     freq     = 12))

问题：如何使用上面的示例（以及教程中的示例）创建时间序列对象的列表列，但包括每个系列的正确开始日期和结束日期（每个系列都不同）

套餐：

library(tidyquant)
library(sweep)
library(timetk)
library(forecast)
library(tidyverse)

可重现的样本数据：

df <- structure(list(id = c("series_1", "series_1", "series_1", "series_1", 
"series_1", "series_1", "series_1", "series_1", "series_1", "series_1", 
"series_1", "series_1", "series_2", "series_2", "series_2", "series_2", 
"series_2", "series_2", "series_2", "series_2", "series_2", "series_2", 
"series_2", "series_2", "series_2", "series_2", "series_2", "series_2", 
"series_2", "series_2", "series_2", "series_2", "series_2", "series_2", 
"series_2", "series_2", "series_3", "series_3", "series_3", "series_3", 
"series_3", "series_3", "series_3", "series_3", "series_3", "series_3", 
"series_3", "series_3", "series_3", "series_3", "series_3", "series_3", 
"series_3", "series_3", "series_3", "series_3", "series_3", "series_3", 
"series_3", "series_3", "series_3", "series_3", "series_3", "series_3", 
"series_3", "series_3", "series_3", "series_3", "series_3", "series_3", 
"series_3", "series_3"), date = structure(c(10957, 10988, 11017, 
11048, 11078, 11109, 11139, 11170, 11201, 11231, 11262, 11292, 
13787, 13818, 13848, 13879, 13910, 13939, 13970, 14000, 14031, 
14061, 14092, 14123, 14153, 14184, 14214, 14245, 14276, 14304, 
14335, 14365, 14396, 14426, 14457, 14488, 15706, 15737, 15765, 
15796, 15826, 15857, 15887, 15918, 15949, 15979, 16010, 16040, 
16071, 16102, 16130, 16161, 16191, 16222, 16252, 16283, 16314, 
16344, 16375, 16405, 16436, 16467, 16495, 16526, 16556, 16587, 
16617, 16648, 16679, 16709, 16740, 16770), class = "Date"), value = c(0.526816892903298, 
0.0640646643005311, 0.569032567087561, 0.733993547270074, 0.742038151714951, 
0.273655793862417, 0.167404572479427, 0.766059899237007, 0.60176682821475, 
0.0769246644340456, 0.162491872673854, 0.323168716160581, 0.179594057612121, 
1.096650313586, 0.894524970557541, 1.55353087605909, 1.50662920810282, 
1.06641945429146, 1.95049989689142, 0.226111006457359, 0.644822218455374, 
0.998987099621445, 0.303691457025707, 0.782052680384368, 1.59218573896214, 
0.171859007328749, 1.9222901831381, 1.4127164632082, 0.919900813139975, 
1.93520273640752, 0.00968976970762014, 0.204170028213412, 1.90123205445707, 
1.05964627675712, 1.40747981145978, 0.476186634972692, 1.56826665904373, 
0.106335987104103, 2.7993093256373, 1.07078968570568, 0.668198951287195, 
0.584522894583642, 0.753677956061438, 2.76492932089604, 2.17496411106549, 
2.56561762047932, 0.586419345578179, 1.7261581714265, 1.38705582660623, 
0.708714888431132, 1.91359720285982, 1.85413848585449, 1.85429209470749, 
2.18856360157952, 1.00432092184201, 0.588805445702747, 2.95583719946444, 
0.382465981179848, 0.711439447710291, 1.24924974096939, 0.961857272777706, 
2.26519317110069, 1.10985011514276, 0.938654307508841, 0.985875837039202, 
1.13028976111673, 2.90536748478189, 0.795255574397743, 1.4741945641581, 
2.02167924796231, 1.2093570465222, 1.47486943169497)), .Names = c("id", 
"date", "value"), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-72L))

嵌套后：

df_nest <- df %>% group_by(id) %>% 
  nest(.key = data.tbl)

从这里我想应用一些函数来改变一个新的列表列，其中包含来自 data.tbl 的相同数据，就像上面的示例（和教程中）一样，强制转换为 ts 对象（以便与预测包一起使用) 但每个系列都有正确的开始和结束日期。

我想应用这样的东西：

df_ts <- df_nest %>%
  mutate(data.ts = map(.x = data.tbl,
                       .f = tk_ts,
                       select = -date,
                       start = c(2000, 1), # <- Problem HERE
                       freq = 12))

但问题是这只给出了 series_1 的正确开始日期。

如何使用每个系列的正确开始和结束日期来改变这个新的 ts 对象列表列？

谢谢

4

1 回答 1

2

用于format()提取年份和月份为start：

df_ts_2 <- df_nest %>%
  mutate(data.ts = map(.x = data.tbl,
                       .f = function(data) tk_ts(
                         data, 
                         select = -date, 
                         start = as.integer(c(format(data$date[1], "%Y"), format(data$date[1], "%m"))),
                         freq = 12
                       )))

print(df_ts_2$data.ts)

# [[1]]
#             Jan        Feb        Mar        Apr        May        Jun        Jul        Aug        Sep        Oct        Nov        Dec
# 2000 0.52681689 0.06406466 0.56903257 0.73399355 0.74203815 0.27365579 0.16740457 0.76605990 0.60176683 0.07692466 0.16249187 0.32316872
# 
# [[2]]
#             Jan        Feb        Mar        Apr        May        Jun        Jul        Aug        Sep        Oct        Nov        Dec
# 2007                                                                                                    0.17959406 1.09665031 0.89452497
# 2008 1.55353088 1.50662921 1.06641945 1.95049990 0.22611101 0.64482222 0.99898710 0.30369146 0.78205268 1.59218574 0.17185901 1.92229018
# 2009 1.41271646 0.91990081 1.93520274 0.00968977 0.20417003 1.90123205 1.05964628 1.40747981 0.47618663                                 
# 
# [[3]]
#            Jan       Feb       Mar       Apr       May       Jun       Jul       Aug       Sep       Oct       Nov       Dec
# 2013 1.5682667 0.1063360 2.7993093 1.0707897 0.6681990 0.5845229 0.7536780 2.7649293 2.1749641 2.5656176 0.5864193 1.7261582
# 2014 1.3870558 0.7087149 1.9135972 1.8541385 1.8542921 2.1885636 1.0043209 0.5888054 2.9558372 0.3824660 0.7114394 1.2492497
# 2015 0.9618573 2.2651932 1.1098501 0.9386543 0.9858758 1.1302898 2.9053675 0.7952556 1.4741946 2.0216792 1.2093570 1.4748694
于 2017-08-11T12:48:43.637 回答