不同窗口大小的滚动统计-6ren

不同窗口大小的滚动统计

转载作者：行者123 更新时间：2023-12-02 02:07:43

我正在管理股票每日数据集。这是示例代码:

A <- cumsum(rnorm(200))
Date <- Sys.Date() + cumsum(sample(1:5, 200, replace = TRUE)) # unequaly spaced time series
data<-data.frame(Date,A)
data<-data%>%
  mutate(Year_Month=as.yearmon(Date))

我的目标是计算一个名为 B 的新每月变量。它是根据以 12 个月结束的 12 个月期间的每日数据 A 的平均值计算得出的。 例如，2021-07-03属于2021年7月，我需要设置之前12个月(从2020年7月到2021年6月)的窗口，并使用该窗口内的所有每日数据A计算平均值。 因此，对于[2021-07-03,2021-07-31]，结果B是相同的。

我尝试过使用rollapply和runner函数，但困难是窗口不是恒定的，因为每个月的天数不是恒定的。我想在 dplyr 环境下实现这个目标。

预期的示例输出如下所示:

   Date     Year_Month  A   B
2021-07-03  July 2021  3.3  2.3
2021-07-08  July 2021  1.5  2.3
2021-07-11  July 2021  4.3  2.3
...
2021-08-04   Aug 2021  2.2  3.2
2021-08-07   Aug 2021  5.7  3.2
2021-08-09   Aug 2021  4.2  3.2

我的新数据集是一个纯时间序列，包含 348 个每月观察值:

   Date       A
2021-07-01   3.1
2021-08-01   4.5
2021-09-01   5.5
...
2021-10-01   4.4
2021-11-01   2.4
2021-12-01   5.5

我通过对以月结束的 60 个月的滚动窗口进行 AR(2) 模型来计算冲击。第 n+1 个月的冲击是该系列的实际值与其预测值(残差)之间的差异，使用过去 60 个月估计的斜率系数。

我正在编写一个函数并在 slider 内调用它。

AR_2<-function(x){
  arima(x,order=c(1,0,0))$residuals
  
}

MILIQ_unexpected<-MILIQ%>%
  mutate(Shock= slide_index_dbl(A, Date, AR_2, .before = months(60), .after = months(-1), .complete = T))

我收到以下错误:

Problem with `mutate()` input `B`.
x In iteration 61, the result of `.f` had size 59, not 1.
i Input `B` is `slide_index_dbl(...)`.
Backtrace:
  1. `%>%`(...)
 11. slider:::stop_not_all_size_one(61L, 59L)
 12. slider:::glubort("In iteration {iteration}, the result of `.f` had size {size}, not 1.")

最佳答案

针对已编辑问题的解释。

你又以错误的方式做事了。对于滚动计算，即根据之前的 n 个变量(大小为 n 的向量)为每个日期分配一个值，您需要一个返回标量(大小为 1 的向量)的函数，例如均值、总和等，因此还有 rollmean、rollsum 等。但是 arima(rnorm(50), order = c(1,0,0))$residuals返回长度为 50 的向量。那么，除非进一步总结，否则如何将大小为 n>1 的向量分配给单个值。
如果您进一步应用一些聚合函数，例如 mean ，你的问题就可以解决了。
例如

data %>%
  mutate(dummy = floor_date(Date, 'month'),
         B = slide_index_dbl(A, dummy, \(x) mean(arima(x, order = c(1,0,0))$residuals), .before = months(12), .after = months(-1), .complete = T))

这在我的 R 中有效

答案

一个slider方法。但是，由于 slider 索引直接作用于日期字段，因此不要使用 Year_month我创建了一个虚拟列 floor_date .

slider 的语法说明::slider_index_dbl

它返回 double类型向量，因此后缀 dbl
它还使用 index您的日期列，因此 _index_
第一个参数是要执行值/滚动计算的向量
第二个参数是索引，由于您使用的是月份而不是日期，所以我创建了 dummy栏目
第三个参数是函数，即 mean待计算
。 before用于获取当前索引之前的 12 个索引值
.after用于排除当前索引，因此 -1
library(lubridate) 也可以加载，因为此处使用了多个函数。

library(tidyverse)
library(zoo)

set.seed(123)

A <- cumsum(rnorm(200))
Date <- Sys.Date() + cumsum(sample(1:5, 200, replace = TRUE)) # unequaly spaced time series
data<-data.frame(Date,A)
data<-data%>%
  mutate(Year_Month=as.yearmon(Date))

library(slider)
library(lubridate)

data %>%
  mutate(dummy = floor_date(Date, 'month'),
         B = slide_index_dbl(A, dummy, mean, .before = months(12), .after = months(-1)))

#>           Date           A Year_Month      dummy         B
#> 1   2021-07-02 -0.56047565   Jul 2021 2021-07-01       NaN
#> 2   2021-07-03 -0.79065314   Jul 2021 2021-07-01       NaN
#> 3   2021-07-08  0.76805518   Jul 2021 2021-07-01       NaN
#> 4   2021-07-09  0.83856357   Jul 2021 2021-07-01       NaN
#> 5   2021-07-13  0.96785130   Jul 2021 2021-07-01       NaN
#> 6   2021-07-15  2.68291629   Jul 2021 2021-07-01       NaN
#> 7   2021-07-17  3.14383250   Jul 2021 2021-07-01       NaN
#> 8   2021-07-21  1.87877126   Jul 2021 2021-07-01       NaN
#> 9   2021-07-22  1.19191841   Jul 2021 2021-07-01       NaN
#> 10  2021-07-26  0.74625644   Jul 2021 2021-07-01       NaN
#> 11  2021-07-31  1.97033824   Jul 2021 2021-07-01       NaN
#> 12  2021-08-05  2.33015207   Aug 2021 2021-08-01 1.1670340
#> 13  2021-08-08  2.73092352   Aug 2021 2021-08-01 1.1670340
#> 14  2021-08-13  2.84160623   Aug 2021 2021-08-01 1.1670340
#> 15  2021-08-18  2.28576510   Aug 2021 2021-08-01 1.1670340
#> 16  2021-08-21  4.07267823   Aug 2021 2021-08-01 1.1670340
#> 17  2021-08-22  4.57052871   Aug 2021 2021-08-01 1.1670340
#> 18  2021-08-25  2.60391156   Aug 2021 2021-08-01 1.1670340
#> 19  2021-08-29  3.30526746   Aug 2021 2021-08-01 1.1670340
#> 20  2021-08-31  2.83247605   Aug 2021 2021-08-01 1.1670340
#> 21  2021-09-05  1.76465234   Sep 2021 2021-09-01 2.0205342
#> 22  2021-09-06  1.54667743   Sep 2021 2021-09-01 2.0205342
#> 23  2021-09-10  0.52067298   Sep 2021 2021-09-01 2.0205342
#> 24  2021-09-13 -0.20821825   Sep 2021 2021-09-01 2.0205342
#> 25  2021-09-14 -0.83325752   Sep 2021 2021-09-01 2.0205342
#> 26  2021-09-16 -2.51995083   Sep 2021 2021-09-01 2.0205342
#> 27  2021-09-19 -1.68216378   Sep 2021 2021-09-01 2.0205342
#> 28  2021-09-22 -1.52879067   Sep 2021 2021-09-01 2.0205342
#> 29  2021-09-23 -2.66692760   Sep 2021 2021-09-01 2.0205342
#> 30  2021-09-25 -1.41311268   Sep 2021 2021-09-01 2.0205342
#> 31  2021-09-26 -0.98664846   Sep 2021 2021-09-01 2.0205342
#> 32  2021-09-28 -1.28171994   Sep 2021 2021-09-01 2.0205342
#> 33  2021-09-30 -0.38659428   Sep 2021 2021-09-01 2.0205342
#> 34  2021-10-02  0.49153921   Oct 2021 2021-10-01 0.9313728
#> 35  2021-10-07  1.31312029   Oct 2021 2021-10-01 0.9313728
#> 36  2021-10-11  2.00176054   Oct 2021 2021-10-01 0.9313728
#> 37  2021-10-15  2.55567820   Oct 2021 2021-10-01 0.9313728
#> 38  2021-10-20  2.49376648   Oct 2021 2021-10-01 0.9313728
#> 39  2021-10-24  2.18780382   Oct 2021 2021-10-01 0.9313728
#> 40  2021-10-25  1.80733282   Oct 2021 2021-10-01 0.9313728
#> 41  2021-10-27  1.11262584   Oct 2021 2021-10-01 0.9313728
#> 42  2021-10-28  0.90470856   Oct 2021 2021-10-01 0.9313728
#> 43  2021-10-30 -0.36068779   Oct 2021 2021-10-01 0.9313728
#> 44  2021-11-02  1.80826818   Nov 2021 2021-11-01 1.0521616
#> 45  2021-11-04  3.01623018   Nov 2021 2021-11-01 1.0521616
#> 46  2021-11-07  1.89312159   Nov 2021 2021-11-01 1.0521616
#> 47  2021-11-08  1.49023676   Nov 2021 2021-11-01 1.0521616
#> 48  2021-11-12  1.02358140   Nov 2021 2021-11-01 1.0521616
#> 49  2021-11-14  1.80354652   Nov 2021 2021-11-01 1.0521616
#> 50  2021-11-17  1.72017745   Nov 2021 2021-11-01 1.0521616
#> 51  2021-11-22  1.97349597   Nov 2021 2021-11-01 1.0521616
#> 52  2021-11-27  1.94494921   Nov 2021 2021-11-01 1.0521616
#> 53  2021-11-30  1.90207876   Nov 2021 2021-11-01 1.0521616
#> 54  2021-12-02  3.27068104   Dec 2021 2021-12-01 1.2041252
#> 55  2021-12-07  3.04491005   Dec 2021 2021-12-01 1.2041252
#> 56  2021-12-11  4.56138066   Dec 2021 2021-12-01 1.2041252
#> 57  2021-12-13  3.01262785   Dec 2021 2021-12-01 1.2041252
#> 58  2021-12-14  3.59724160   Dec 2021 2021-12-01 1.2041252
#> 59  2021-12-18  3.72109585   Dec 2021 2021-12-01 1.2041252
#> 60  2021-12-19  3.93703742   Dec 2021 2021-12-01 1.2041252
#> 61  2021-12-23  4.31667690   Dec 2021 2021-12-01 1.2041252
#> 62  2021-12-28  3.81435345   Dec 2021 2021-12-01 1.2041252
#> 63  2022-01-01  3.48114606   Jan 2022 2022-01-01 1.5660426
#> 64  2022-01-03  2.46257068   Jan 2022 2022-01-01 1.5660426
#> 65  2022-01-05  1.39077945   Jan 2022 2022-01-01 1.5660426
#> 66  2022-01-09  1.69430809   Jan 2022 2022-01-01 1.5660426
#> 67  2022-01-12  2.14251787   Jan 2022 2022-01-01 1.5660426
#> 68  2022-01-17  2.19552210   Jan 2022 2022-01-01 1.5660426
#> 69  2022-01-19  3.11778957   Jan 2022 2022-01-01 1.5660426
#> 70  2022-01-22  5.16787425   Jan 2022 2022-01-01 1.5660426
#> 71  2022-01-25  4.67684309   Jan 2022 2022-01-01 1.5660426
#> 72  2022-01-28  2.36767421   Jan 2022 2022-01-01 1.5660426
#> 73  2022-01-29  3.37341274   Jan 2022 2022-01-01 1.5660426
#> 74  2022-01-30  2.66421197   Jan 2022 2022-01-01 1.5660426
#> 75  2022-02-02  1.97620336   Feb 2022 2022-02-01 1.7814769
#> 76  2022-02-06  3.00177473   Feb 2022 2022-02-01 1.7814769
#> 77  2022-02-10  2.71700172   Feb 2022 2022-02-01 1.7814769
#> 78  2022-02-15  1.49628401   Feb 2022 2022-02-01 1.7814769
#> 79  2022-02-17  1.67758749   Feb 2022 2022-02-01 1.7814769
#> 80  2022-02-19  1.53869613   Feb 2022 2022-02-01 1.7814769
#> 81  2022-02-23  1.54446031   Feb 2022 2022-02-01 1.7814769
#> 82  2022-02-25  1.92974071   Feb 2022 2022-02-01 1.7814769
#> 83  2022-02-26  1.55908068   Feb 2022 2022-02-01 1.7814769
#> 84  2022-03-02  2.20345723   Mar 2022 2022-03-01 1.7984352
#> 85  2022-03-05  1.98297067   Mar 2022 2022-03-01 1.7984352
#> 86  2022-03-06  2.31475263   Mar 2022 2022-03-01 1.7984352
#> 87  2022-03-11  3.41159164   Mar 2022 2022-03-01 1.7984352
#> 88  2022-03-14  3.84677313   Mar 2022 2022-03-01 1.7984352
#> 89  2022-03-18  3.52084155   Mar 2022 2022-03-01 1.7984352
#> 90  2022-03-20  4.66964917   Mar 2022 2022-03-01 1.7984352
#> 91  2022-03-25  5.66315302   Mar 2022 2022-03-01 1.7984352
#> 92  2022-03-30  6.21154998   Mar 2022 2022-03-01 1.7984352
#> 93  2022-04-01  6.45028172   Apr 2022 2022-04-01 1.9901615
#> 94  2022-04-03  5.82237564   Apr 2022 2022-04-01 1.9901615
#> 95  2022-04-05  7.18302809   Apr 2022 2022-04-01 1.9901615
#> 96  2022-04-06  6.58276850   Apr 2022 2022-04-01 1.9901615
#> 97  2022-04-09  8.77010150   Apr 2022 2022-04-01 1.9901615
#> 98  2022-04-13 10.30271212   Apr 2022 2022-04-01 1.9901615
#> 99  2022-04-16 10.06701176   Apr 2022 2022-04-01 1.9901615
#> 100 2022-04-19  9.04059086   Apr 2022 2022-04-01 1.9901615
#> 101 2022-04-22  8.33018430   Apr 2022 2022-04-01 1.9901615
#> 102 2022-04-26  8.58706801   Apr 2022 2022-04-01 1.9901615
#> 103 2022-04-30  8.34037613   Apr 2022 2022-04-01 1.9901615
#> 104 2022-05-03  7.99283353   May 2022 2022-05-01 2.6463239
#> 105 2022-05-07  7.04121496   May 2022 2022-05-01 2.6463239
#> 106 2022-05-09  6.99618724   May 2022 2022-05-01 2.6463239
#> 107 2022-05-12  6.21128277   May 2022 2022-05-01 2.6463239
#> 108 2022-05-16  4.54334083   May 2022 2022-05-01 2.6463239
#> 109 2022-05-18  4.16311431   May 2022 2022-05-01 2.6463239
#> 110 2022-05-19  5.08211092   May 2022 2022-05-01 2.6463239
#> 111 2022-05-22  4.50676396   May 2022 2022-05-01 2.6463239
#> 112 2022-05-26  5.11472828   May 2022 2022-05-01 2.6463239
#> 113 2022-05-27  3.49684557   May 2022 2022-05-01 2.6463239
#> 114 2022-05-28  3.44128361   May 2022 2022-05-01 2.6463239
#> 115 2022-06-01  3.96069081   Jun 2022 2022-06-01 2.9049216
#> 116 2022-06-05  4.26184417   Jun 2022 2022-06-01 2.9049216
#> 117 2022-06-10  4.36752037   Jun 2022 2022-06-01 2.9049216
#> 118 2022-06-11  3.72681436   Jun 2022 2022-06-01 2.9049216
#> 119 2022-06-15  2.87711001   Jun 2022 2022-06-01 2.9049216
#> 120 2022-06-20  1.85298122   Jun 2022 2022-06-01 2.9049216
#> 121 2022-06-23  1.97062782   Jun 2022 2022-06-01 2.9049216
#> 122 2022-06-25  1.02315321   Jun 2022 2022-06-01 2.9049216
#> 123 2022-06-30  0.53259576   Jun 2022 2022-06-01 2.9049216
#> 124 2022-07-04  0.27650357   Jul 2022 2022-07-01 2.8921496
#> 125 2022-07-08  2.12036558   Jul 2022 2022-07-01 2.8921496
#> 126 2022-07-09  1.46841567   Jul 2022 2022-07-01 2.8921496
#> 127 2022-07-12  1.70380225   Jul 2022 2022-07-01 2.8921496
#> 128 2022-07-15  1.78176310   Jul 2022 2022-07-01 2.8921496
#> 129 2022-07-18  0.81990646   Jul 2022 2022-07-01 2.8921496
#> 130 2022-07-23  0.74859838   Jul 2022 2022-07-01 2.8921496
#> 131 2022-07-25  2.19314923   Jul 2022 2022-07-01 2.8921496
#> 132 2022-07-30  2.64465329   Jul 2022 2022-07-01 2.8921496
#> 133 2022-08-01  2.68588621   Aug 2022 2022-08-01 2.9475552
#> 134 2022-08-02  2.26338938   Aug 2022 2022-08-01 2.9475552
#> 135 2022-08-06  0.21014215   Aug 2022 2022-08-01 2.9475552
#> 136 2022-08-08  1.34147937   Aug 2022 2022-08-01 2.9475552
#> 137 2022-08-10 -0.11916070   Aug 2022 2022-08-01 2.9475552
#> 138 2022-08-13  0.62078681   Aug 2022 2022-08-01 2.9475552
#> 139 2022-08-18  2.52989038   Aug 2022 2022-08-01 2.9475552
#> 140 2022-08-19  1.08599722   Aug 2022 2022-08-01 2.9475552
#> 141 2022-08-22  1.78778155   Aug 2022 2022-08-01 2.9475552
#> 142 2022-08-25  1.52558406   Aug 2022 2022-08-01 2.9475552
#> 143 2022-08-27 -0.04656010   Aug 2022 2022-08-01 2.9475552
#> 144 2022-09-01 -1.56122775   Sep 2022 2022-09-01 2.7883422
#> 145 2022-09-02 -3.16276392   Sep 2022 2022-09-01 2.7883422
#> 146 2022-09-06 -3.69367045   Sep 2022 2022-09-01 2.7883422
#> 147 2022-09-10 -5.15542603   Sep 2022 2022-09-01 2.7883422
#> 148 2022-09-11 -4.46750926   Sep 2022 2022-09-01 2.7883422
#> 149 2022-09-14 -2.36740032   Sep 2022 2022-09-01 2.7883422
#> 150 2022-09-18 -3.65443079   Sep 2022 2022-09-01 2.7883422
#> 151 2022-09-22 -2.86669195   Sep 2022 2022-09-01 2.7883422
#> 152 2022-09-23 -2.09764971   Sep 2022 2022-09-01 2.7883422
#> 153 2022-09-28 -1.76544713   Sep 2022 2022-09-01 2.7883422
#> 154 2022-10-01 -2.77382373   Oct 2022 2022-10-01 2.6820771
#> 155 2022-10-05 -2.89327634   Oct 2022 2022-10-01 2.6820771
#> 156 2022-10-07 -3.17367168   Oct 2022 2022-10-01 2.6820771
#> 157 2022-10-10 -2.61068214   Oct 2022 2022-10-01 2.6820771
#> 158 2022-10-12 -2.98312090   Oct 2022 2022-10-01 2.6820771
#> 159 2022-10-15 -2.00614751   Oct 2022 2022-10-01 2.6820771
#> 160 2022-10-18 -2.38072837   Oct 2022 2022-10-01 2.6820771
#> 161 2022-10-19 -1.32801690   Oct 2022 2022-10-01 2.6820771
#> 162 2022-10-24 -2.37719391   Oct 2022 2022-10-01 2.6820771
#> 163 2022-10-28 -3.63734916   Oct 2022 2022-10-01 2.6820771
#> 164 2022-11-01 -0.39630922   Nov 2022 2022-11-01 2.3431466
#> 165 2022-11-06 -0.81316681   Nov 2022 2022-11-01 2.3431466
#> 166 2022-11-09 -0.51493922   Nov 2022 2022-11-01 2.3431466
#> 167 2022-11-11  0.12163046   Nov 2022 2022-11-01 2.3431466
#> 168 2022-11-15 -0.36215017   Nov 2022 2022-11-01 2.3431466
#> 169 2022-11-20  0.15471187   Nov 2022 2022-11-01 2.3431466
#> 170 2022-11-22  0.52367640   Nov 2022 2022-11-01 2.3431466
#> 171 2022-11-25  0.30829589   Nov 2022 2022-11-01 2.3431466
#> 172 2022-11-28  0.37358893   Nov 2022 2022-11-01 2.3431466
#> 173 2022-11-29  0.33952167   Nov 2022 2022-11-01 2.3431466
#> 174 2022-12-02  2.46797357   Dec 2022 2022-12-01 2.1861398
#> 175 2022-12-04  1.72663748   Dec 2022 2022-12-01 2.1861398
#> 176 2022-12-07  0.63064121   Dec 2022 2022-12-01 2.1861398
#> 177 2022-12-10  0.66842961   Dec 2022 2022-12-01 2.1861398
#> 178 2022-12-11  0.97891036   Dec 2022 2022-12-01 2.1861398
#> 179 2022-12-13  1.41543384   Dec 2022 2022-12-01 2.1861398
#> 180 2022-12-15  0.95706850   Dec 2022 2022-12-01 2.1861398
#> 181 2022-12-17 -0.10625763   Dec 2022 2022-12-01 2.1861398
#> 182 2022-12-21  1.15692755   Dec 2022 2022-12-01 2.1861398
#> 183 2022-12-22  0.80727716   Dec 2022 2022-12-01 2.1861398
#> 184 2022-12-27 -0.05823570   Dec 2022 2022-12-01 2.1861398
#> 185 2023-01-01 -0.29451527   Jan 2023 2023-01-01 1.9647998
#> 186 2023-01-04 -0.49169117   Jan 2023 2023-01-01 1.9647998
#> 187 2023-01-07  0.61822912   Jan 2023 2023-01-01 1.9647998
#> 188 2023-01-12  0.70296641   Jan 2023 2023-01-01 1.9647998
#> 189 2023-01-13  1.45702020   Jan 2023 2023-01-01 1.9647998
#> 190 2023-01-17  0.95772818   Jan 2023 2023-01-01 1.9647998
#> 191 2023-01-19  1.17217349   Jan 2023 2023-01-01 1.9647998
#> 192 2023-01-24  0.84748758   Jan 2023 2023-01-01 1.9647998
#> 193 2023-01-28  0.94207111   Jan 2023 2023-01-01 1.9647998
#> 194 2023-02-02  0.04670775   Feb 2023 2023-02-01 1.7721209
#> 195 2023-02-03 -1.26409378   Feb 2023 2023-02-01 1.7721209
#> 196 2023-02-05  0.73311960   Feb 2023 2023-02-01 1.7721209
#> 197 2023-02-08  1.33382843   Feb 2023 2023-02-01 1.7721209
#> 198 2023-02-09  0.08255706   Feb 2023 2023-02-01 1.7721209
#> 199 2023-02-10 -0.52860885   Feb 2023 2023-02-01 1.7721209
#> 200 2023-02-13 -1.71408894   Feb 2023 2023-02-01 1.7721209

^{由 reprex package 于 2021 年 6 月 29 日创建(v2.0.0)}

作为滚动平均值的检查，我计算了 Excel 中前 123 行的平均值，即 2.8921496并正确显示在July 2022中行。

根据评论中的要求，如果只需要完整的案例 -

使用参数.complete = TRUE

data %>%
  mutate(dummy = floor_date(Date, 'month'),
         B = slide_index_dbl(A, dummy, mean, .before = months(12), .after = months(-1), .complete = T))

          Date           A Year_Month      dummy        B
1   2021-07-03 -0.56047565   Jul 2021 2021-07-01       NA
2   2021-07-04 -0.79065314   Jul 2021 2021-07-01       NA
3   2021-07-09  0.76805518   Jul 2021 2021-07-01       NA
4   2021-07-10  0.83856357   Jul 2021 2021-07-01       NA
5   2021-07-14  0.96785130   Jul 2021 2021-07-01       NA
6   2021-07-16  2.68291629   Jul 2021 2021-07-01       NA
7   2021-07-18  3.14383250   Jul 2021 2021-07-01       NA
8   2021-07-22  1.87877126   Jul 2021 2021-07-01       NA
9   2021-07-23  1.19191841   Jul 2021 2021-07-01       NA
10  2021-07-27  0.74625644   Jul 2021 2021-07-01       NA
11  2021-08-01  1.97033824   Aug 2021 2021-08-01       NA
12  2021-08-06  2.33015207   Aug 2021 2021-08-01       NA
13  2021-08-09  2.73092352   Aug 2021 2021-08-01       NA
14  2021-08-14  2.84160623   Aug 2021 2021-08-01       NA
15  2021-08-19  2.28576510   Aug 2021 2021-08-01       NA
16  2021-08-22  4.07267823   Aug 2021 2021-08-01       NA
17  2021-08-23  4.57052871   Aug 2021 2021-08-01       NA
18  2021-08-26  2.60391156   Aug 2021 2021-08-01       NA
19  2021-08-30  3.30526746   Aug 2021 2021-08-01       NA
20  2021-09-01  2.83247605   Sep 2021 2021-09-01       NA
21  2021-09-06  1.76465234   Sep 2021 2021-09-01       NA
22  2021-09-07  1.54667743   Sep 2021 2021-09-01       NA
23  2021-09-11  0.52067298   Sep 2021 2021-09-01       NA
24  2021-09-14 -0.20821825   Sep 2021 2021-09-01       NA
25  2021-09-15 -0.83325752   Sep 2021 2021-09-01       NA
26  2021-09-17 -2.51995083   Sep 2021 2021-09-01       NA
27  2021-09-20 -1.68216378   Sep 2021 2021-09-01       NA
28  2021-09-23 -1.52879067   Sep 2021 2021-09-01       NA
29  2021-09-24 -2.66692760   Sep 2021 2021-09-01       NA
30  2021-09-26 -1.41311268   Sep 2021 2021-09-01       NA
31  2021-09-27 -0.98664846   Sep 2021 2021-09-01       NA
32  2021-09-29 -1.28171994   Sep 2021 2021-09-01       NA
33  2021-10-01 -0.38659428   Oct 2021 2021-10-01       NA
34  2021-10-03  0.49153921   Oct 2021 2021-10-01       NA
35  2021-10-08  1.31312029   Oct 2021 2021-10-01       NA
36  2021-10-12  2.00176054   Oct 2021 2021-10-01       NA
37  2021-10-16  2.55567820   Oct 2021 2021-10-01       NA
38  2021-10-21  2.49376648   Oct 2021 2021-10-01       NA
39  2021-10-25  2.18780382   Oct 2021 2021-10-01       NA
40  2021-10-26  1.80733282   Oct 2021 2021-10-01       NA
41  2021-10-28  1.11262584   Oct 2021 2021-10-01       NA
42  2021-10-29  0.90470856   Oct 2021 2021-10-01       NA
43  2021-10-31 -0.36068779   Oct 2021 2021-10-01       NA
44  2021-11-03  1.80826818   Nov 2021 2021-11-01       NA
45  2021-11-05  3.01623018   Nov 2021 2021-11-01       NA
46  2021-11-08  1.89312159   Nov 2021 2021-11-01       NA
47  2021-11-09  1.49023676   Nov 2021 2021-11-01       NA
48  2021-11-13  1.02358140   Nov 2021 2021-11-01       NA
49  2021-11-15  1.80354652   Nov 2021 2021-11-01       NA
50  2021-11-18  1.72017745   Nov 2021 2021-11-01       NA
51  2021-11-23  1.97349597   Nov 2021 2021-11-01       NA
52  2021-11-28  1.94494921   Nov 2021 2021-11-01       NA
53  2021-12-01  1.90207876   Dec 2021 2021-12-01       NA
54  2021-12-03  3.27068104   Dec 2021 2021-12-01       NA
55  2021-12-08  3.04491005   Dec 2021 2021-12-01       NA
56  2021-12-12  4.56138066   Dec 2021 2021-12-01       NA
57  2021-12-14  3.01262785   Dec 2021 2021-12-01       NA
58  2021-12-15  3.59724160   Dec 2021 2021-12-01       NA
59  2021-12-19  3.72109585   Dec 2021 2021-12-01       NA
60  2021-12-20  3.93703742   Dec 2021 2021-12-01       NA
61  2021-12-24  4.31667690   Dec 2021 2021-12-01       NA
62  2021-12-29  3.81435345   Dec 2021 2021-12-01       NA
63  2022-01-02  3.48114606   Jan 2022 2022-01-01       NA
64  2022-01-04  2.46257068   Jan 2022 2022-01-01       NA
65  2022-01-06  1.39077945   Jan 2022 2022-01-01       NA
66  2022-01-10  1.69430809   Jan 2022 2022-01-01       NA
67  2022-01-13  2.14251787   Jan 2022 2022-01-01       NA
68  2022-01-18  2.19552210   Jan 2022 2022-01-01       NA
69  2022-01-20  3.11778957   Jan 2022 2022-01-01       NA
70  2022-01-23  5.16787425   Jan 2022 2022-01-01       NA
71  2022-01-26  4.67684309   Jan 2022 2022-01-01       NA
72  2022-01-29  2.36767421   Jan 2022 2022-01-01       NA
73  2022-01-30  3.37341274   Jan 2022 2022-01-01       NA
74  2022-01-31  2.66421197   Jan 2022 2022-01-01       NA
75  2022-02-03  1.97620336   Feb 2022 2022-02-01       NA
76  2022-02-07  3.00177473   Feb 2022 2022-02-01       NA
77  2022-02-11  2.71700172   Feb 2022 2022-02-01       NA
78  2022-02-16  1.49628401   Feb 2022 2022-02-01       NA
79  2022-02-18  1.67758749   Feb 2022 2022-02-01       NA
80  2022-02-20  1.53869613   Feb 2022 2022-02-01       NA
81  2022-02-24  1.54446031   Feb 2022 2022-02-01       NA
82  2022-02-26  1.92974071   Feb 2022 2022-02-01       NA
83  2022-02-27  1.55908068   Feb 2022 2022-02-01       NA
84  2022-03-03  2.20345723   Mar 2022 2022-03-01       NA
85  2022-03-06  1.98297067   Mar 2022 2022-03-01       NA
86  2022-03-07  2.31475263   Mar 2022 2022-03-01       NA
87  2022-03-12  3.41159164   Mar 2022 2022-03-01       NA
88  2022-03-15  3.84677313   Mar 2022 2022-03-01       NA
89  2022-03-19  3.52084155   Mar 2022 2022-03-01       NA
90  2022-03-21  4.66964917   Mar 2022 2022-03-01       NA
91  2022-03-26  5.66315302   Mar 2022 2022-03-01       NA
92  2022-03-31  6.21154998   Mar 2022 2022-03-01       NA
93  2022-04-02  6.45028172   Apr 2022 2022-04-01       NA
94  2022-04-04  5.82237564   Apr 2022 2022-04-01       NA
95  2022-04-06  7.18302809   Apr 2022 2022-04-01       NA
96  2022-04-07  6.58276850   Apr 2022 2022-04-01       NA
97  2022-04-10  8.77010150   Apr 2022 2022-04-01       NA
98  2022-04-14 10.30271212   Apr 2022 2022-04-01       NA
99  2022-04-17 10.06701176   Apr 2022 2022-04-01       NA
100 2022-04-20  9.04059086   Apr 2022 2022-04-01       NA
101 2022-04-23  8.33018430   Apr 2022 2022-04-01       NA
102 2022-04-27  8.58706801   Apr 2022 2022-04-01       NA
103 2022-05-01  8.34037613   May 2022 2022-05-01       NA
104 2022-05-04  7.99283353   May 2022 2022-05-01       NA
105 2022-05-08  7.04121496   May 2022 2022-05-01       NA
106 2022-05-10  6.99618724   May 2022 2022-05-01       NA
107 2022-05-13  6.21128277   May 2022 2022-05-01       NA
108 2022-05-17  4.54334083   May 2022 2022-05-01       NA
109 2022-05-19  4.16311431   May 2022 2022-05-01       NA
110 2022-05-20  5.08211092   May 2022 2022-05-01       NA
111 2022-05-23  4.50676396   May 2022 2022-05-01       NA
112 2022-05-27  5.11472828   May 2022 2022-05-01       NA
113 2022-05-28  3.49684557   May 2022 2022-05-01       NA
114 2022-05-29  3.44128361   May 2022 2022-05-01       NA
115 2022-06-02  3.96069081   Jun 2022 2022-06-01       NA
116 2022-06-06  4.26184417   Jun 2022 2022-06-01       NA
117 2022-06-11  4.36752037   Jun 2022 2022-06-01       NA
118 2022-06-12  3.72681436   Jun 2022 2022-06-01       NA
119 2022-06-16  2.87711001   Jun 2022 2022-06-01       NA
120 2022-06-21  1.85298122   Jun 2022 2022-06-01       NA
121 2022-06-24  1.97062782   Jun 2022 2022-06-01       NA
122 2022-06-26  1.02315321   Jun 2022 2022-06-01       NA
123 2022-07-01  0.53259576   Jul 2022 2022-07-01 2.911490
124 2022-07-05  0.27650357   Jul 2022 2022-07-01 2.911490
125 2022-07-09  2.12036558   Jul 2022 2022-07-01 2.911490
126 2022-07-10  1.46841567   Jul 2022 2022-07-01 2.911490
127 2022-07-13  1.70380225   Jul 2022 2022-07-01 2.911490
128 2022-07-16  1.78176310   Jul 2022 2022-07-01 2.911490
129 2022-07-19  0.81990646   Jul 2022 2022-07-01 2.911490
130 2022-07-24  0.74859838   Jul 2022 2022-07-01 2.911490
131 2022-07-26  2.19314923   Jul 2022 2022-07-01 2.911490
132 2022-07-31  2.64465329   Jul 2022 2022-07-01 2.911490
133 2022-08-02  2.68588621   Aug 2022 2022-08-01 2.939545
134 2022-08-03  2.26338938   Aug 2022 2022-08-01 2.939545
135 2022-08-07  0.21014215   Aug 2022 2022-08-01 2.939545
136 2022-08-09  1.34147937   Aug 2022 2022-08-01 2.939545
137 2022-08-11 -0.11916070   Aug 2022 2022-08-01 2.939545
138 2022-08-14  0.62078681   Aug 2022 2022-08-01 2.939545
139 2022-08-19  2.52989038   Aug 2022 2022-08-01 2.939545
140 2022-08-20  1.08599722   Aug 2022 2022-08-01 2.939545
141 2022-08-23  1.78778155   Aug 2022 2022-08-01 2.939545
142 2022-08-26  1.52558406   Aug 2022 2022-08-01 2.939545
143 2022-08-28 -0.04656010   Aug 2022 2022-08-01 2.939545
144 2022-09-02 -1.56122775   Sep 2022 2022-09-01 2.788698
145 2022-09-03 -3.16276392   Sep 2022 2022-09-01 2.788698
146 2022-09-07 -3.69367045   Sep 2022 2022-09-01 2.788698
147 2022-09-11 -5.15542603   Sep 2022 2022-09-01 2.788698
148 2022-09-12 -4.46750926   Sep 2022 2022-09-01 2.788698
149 2022-09-15 -2.36740032   Sep 2022 2022-09-01 2.788698
150 2022-09-19 -3.65443079   Sep 2022 2022-09-01 2.788698
151 2022-09-23 -2.86669195   Sep 2022 2022-09-01 2.788698
152 2022-09-24 -2.09764971   Sep 2022 2022-09-01 2.788698
153 2022-09-29 -1.76544713   Sep 2022 2022-09-01 2.788698
154 2022-10-02 -2.77382373   Oct 2022 2022-10-01 2.656716
155 2022-10-06 -2.89327634   Oct 2022 2022-10-01 2.656716
156 2022-10-08 -3.17367168   Oct 2022 2022-10-01 2.656716
157 2022-10-11 -2.61068214   Oct 2022 2022-10-01 2.656716
158 2022-10-13 -2.98312090   Oct 2022 2022-10-01 2.656716
159 2022-10-16 -2.00614751   Oct 2022 2022-10-01 2.656716
160 2022-10-19 -2.38072837   Oct 2022 2022-10-01 2.656716
161 2022-10-20 -1.32801690   Oct 2022 2022-10-01 2.656716
162 2022-10-25 -2.37719391   Oct 2022 2022-10-01 2.656716
163 2022-10-29 -3.63734916   Oct 2022 2022-10-01 2.656716
164 2022-11-02 -0.39630922   Nov 2022 2022-11-01 2.343147
165 2022-11-07 -0.81316681   Nov 2022 2022-11-01 2.343147
166 2022-11-10 -0.51493922   Nov 2022 2022-11-01 2.343147
167 2022-11-12  0.12163046   Nov 2022 2022-11-01 2.343147
168 2022-11-16 -0.36215017   Nov 2022 2022-11-01 2.343147
169 2022-11-21  0.15471187   Nov 2022 2022-11-01 2.343147
170 2022-11-23  0.52367640   Nov 2022 2022-11-01 2.343147
171 2022-11-26  0.30829589   Nov 2022 2022-11-01 2.343147
172 2022-11-29  0.37358893   Nov 2022 2022-11-01 2.343147
173 2022-11-30  0.33952167   Nov 2022 2022-11-01 2.343147
174 2022-12-03  2.46797357   Dec 2022 2022-12-01 2.183792
175 2022-12-05  1.72663748   Dec 2022 2022-12-01 2.183792
176 2022-12-08  0.63064121   Dec 2022 2022-12-01 2.183792
177 2022-12-11  0.66842961   Dec 2022 2022-12-01 2.183792
178 2022-12-12  0.97891036   Dec 2022 2022-12-01 2.183792
179 2022-12-14  1.41543384   Dec 2022 2022-12-01 2.183792
180 2022-12-16  0.95706850   Dec 2022 2022-12-01 2.183792
181 2022-12-18 -0.10625763   Dec 2022 2022-12-01 2.183792
182 2022-12-22  1.15692755   Dec 2022 2022-12-01 2.183792
183 2022-12-23  0.80727716   Dec 2022 2022-12-01 2.183792
184 2022-12-28 -0.05823570   Dec 2022 2022-12-01 2.183792
185 2023-01-02 -0.29451527   Jan 2023 2023-01-01 1.964800
186 2023-01-05 -0.49169117   Jan 2023 2023-01-01 1.964800
187 2023-01-08  0.61822912   Jan 2023 2023-01-01 1.964800
188 2023-01-13  0.70296641   Jan 2023 2023-01-01 1.964800
189 2023-01-14  1.45702020   Jan 2023 2023-01-01 1.964800
190 2023-01-18  0.95772818   Jan 2023 2023-01-01 1.964800
191 2023-01-20  1.17217349   Jan 2023 2023-01-01 1.964800
192 2023-01-25  0.84748758   Jan 2023 2023-01-01 1.964800
193 2023-01-29  0.94207111   Jan 2023 2023-01-01 1.964800
194 2023-02-03  0.04670775   Feb 2023 2023-02-01 1.772121
195 2023-02-04 -1.26409378   Feb 2023 2023-02-01 1.772121
196 2023-02-06  0.73311960   Feb 2023 2023-02-01 1.772121
197 2023-02-09  1.33382843   Feb 2023 2023-02-01 1.772121
198 2023-02-10  0.08255706   Feb 2023 2023-02-01 1.772121
199 2023-02-11 -0.52860885   Feb 2023 2023-02-01 1.772121
200 2023-02-14 -1.71408894   Feb 2023 2023-02-01 1.772121

如果你想在 slider 中使用自定义函数您可以在那里使用不可见的函数样式。喜欢

data %>%
  mutate(dummy = floor_date(Date, 'month'),
         B = slide_index_dbl(A, dummy, \(x) mean(x, na.rm=T), .before = months(12), .after = months(-1), .complete = T))

关于不同窗口大小的滚动统计，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/68176417/

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