r - 比较R中多个时间序列的间隔

Question

我有两个并发时间序列A和B，都包含由开始和结束时间定义的事件 - 这是一个示例：

A.df <- structure(list(A.eventid = 1:53,
                       A.start = structure(c(1563219814.52, 1563219852.37, 1563220313.16, 1563220472.66, 1563220704.35, 1563220879.51, 1563221108.24, 1563221158.33, 1563221387.43, 1563221400.7, 1563221602.34, 1563221828.33, 1563222165.52, 1563222314.2, 1563222557.28, 1563222669.44, 1563222905.52, 1563223091.62, 1563223237.19, 1563223273.64, 1563223580.14, 1563223908.66, 1563224093.27, 1563224497.41, 1563224554.64, 1563224705.57, 1563225011.55, 1563225192.59, 1563225305.14, 1563225414.38, 1563225432.21, 1563225898.61, 1563226034.51, 1563226110.18, 1563226206.49, 1563226528.13, 1563226570.18, 1563226788.53, 1563227026.21, 1563227502.2, 1563227709.3, 1563227832.51, 1563228127.44, 1563228188.4, 1563228293.59, 1563228558.39, 1563228680.32, 1563228819.44, 1563229208.51, 1563229282.14, 1563229528.52, 1563229959.21, 1563230268.65), class = c("POSIXct", "POSIXt")), 
                       A.end = structure(c(1563219846.43, 1563220304.39, 1563220470.68, 1563220702.37, 1563220877.5, 1563221102.18, 1563221151.47, 1563221379.63, 1563221389.22, 1563221600.32, 1563221819.27, 1563222157.29, 1563222312.23, 1563222555.25, 1563222667.42, 1563222894.56, 1563223079.44, 1563223230.39, 1563223273.24, 1563223578.14, 1563223900.48, 1563224089.24, 1563224493.45, 1563224550.37, 1563224699.47, 1563225005.13, 1563225188.17, 1563225293.21, 1563225412.17, 1563225417.46, 1563225894.44, 1563226025.2, 1563226108.13, 1563226204.37, 1563226517.59, 1563226562.41, 1563226780.59, 1563227022.28, 1563227493.57, 1563227705.52, 1563227830.38, 1563228125.49, 1563228184.21, 1563228286.39, 1563228546.47, 1563228677.67, 1563228816.5, 1563229198.68, 1563229273.54, 1563229526.53, 1563229952.57, 1563230257.16, 1563230742.25), class = c("POSIXct", "POSIXt"))),
                       row.names = 1:53, class = "data.frame")

B.df <- structure(list(B.eventid = 1:52,
                       B.start = structure(c(1563221811.888, 1563222153.835, 1563222156.013, 1563222220.14, 1563222289.692, 1563222305.607, 1563222611.565, 1563222631.139, 1563222636.867, 1563222763.565, 1563222774.301, 1563222848.507, 1563222849.957, 1563222853.513, 1563223225.656, 1563223302.539, 1563223326.153, 1563223328.934, 1563223590.144, 1563223592.904, 1563224035.038, 1563224692.704, 1563226451.642, 1563226454.731, 1563226819.701, 1563226824.685, 1563227278.677, 1563227770.247, 1563227773.907, 1563227800.529, 1563227804.663, 1563227809.749, 1563227813.237, 1563227819.043, 1563227829.781, 1563227973.727, 1563229396.472, 1563229454.515, 1563229473.079, 1563229488.669, 1563229521.413, 1563229542.954, 1563229553.595, 1563229565.988, 1563229569.095, 1563229618.857, 1563229791.585, 1563229936.355, 1563230339.141, 1563230734.677, 1563231667.173, 1563231978.567), class = c("POSIXct", "POSIXt")),
                       B.end = structure(c(1563221815.058, 1563222154.295, 1563222158.633, 1563222222.07, 1563222289.872, 1563222308.617, 1563222614.265, 1563222633.509, 1563222640.367, 1563222769.045, 1563222774.801, 1563222848.677, 1563222850.237, 1563222856.103, 1563223226.166, 1563223305.339, 1563223328.763, 1563223333.234, 1563223591.454, 1563223593.084, 1563224043.618, 1563224695.234, 1563226454.622, 1563226456.771, 1563226822.551, 1563226827.225, 1563227282.067, 1563227771.787, 1563227774.477, 1563227802.199, 1563227806.653, 1563227811.569, 1563227817.897, 1563227823.643, 1563227830.351, 1563227978.177, 1563229401.282, 1563229457.905, 1563229478.359, 1563229492.439, 1563229527.723, 1563229545.694, 1563229558.975, 1563229568.658, 1563229571.255, 1563229621.117, 1563229792.055, 1563229952.055, 1563230344.351, 1563230739.647, 1563231672.983, 1563231979.987), class = c("POSIXct", "POSIXt"))),
                       row.names = 1:52, class = "data.frame")

系列A中的事件较长，而系列中的事件B较短。

我画了一个示意图来帮助解释：

对于A发生≥4个B事件的每个事件，我想比较（也在示意图中显示）：

X = the mean interval between B events occurring during the A event

和

Y = the interval between the last B event occuring during the A event, and the first B event occurring after the A event

我的问题是 和 的X计算Y。

为了计算X，我尝试使用事件发生的事件对事件foverlaps进行分组。但是，这不包括在 A 事件之间的间隙内发生的事件。BAB

此外，我尝试使用和失败来计算分组B事件之间的平均间隔，因为我不能限制只在组内工作（即它也计算组之间的间隔）。mutatelaglag

最后，我不确定如何有效地识别Y间隔的开始/结束来计算其持续时间。

我在想我的 R/编码正在改进，但这让我有点挣扎 - 任何帮助都会非常感激！

标签： rdplyrtime-seriesposixct

Answer 1

我试图提出一个可能的解决方案，减去平均计算的部分，这应该是显而易见的。首先，我重命名了列名，这样可以更轻松地加入数据集：

A.df = A.df %>% 
  rename_all(funs(str_replace(., "A.", ""))) %>% 
  mutate(type="A")
B.df = B.df %>%
  rename_all(funs(str_replace(., "B.", ""))) %>% 
  mutate(type="B")

那么整体数据，按时间排序，为：

data = bind_rows(A.df, B.df) %>% 
  arrange(start)

A现在我添加一列，显示事件最后开始的时间戳。向前填充此值将为每个事件显示最后一个事件的时间A。

data = data %>%
  mutate(last.A.start=ifelse(type=='A', start, NA)) %>%
  tidyr::fill(last.A.start) 

最后，A可以删除事件。只要 last.A.start相同，则B事件属于同一A事件。根据这些信息x并y可以进行计算。

data = data %>%
  filter(type == "B") %>%
  mutate(
    duration=end-start,  # Not needed.
    delta=start - lag(end),
    sameA=(last.A.start == lag(last.A.start)),
    x=ifelse(sameA, delta, NA),
    y=ifelse(sameA, NA, delta)
  )

这有帮助吗？最好的，米