从每周数据中获取每月时间序列 [英] Getting a monthly time series from weekly data

问题描述

我查了几个关于时间序列聚合的问题，但没有找到我想要的.

I've checked a few questions on time series aggregation, but haven't found what I was looking for.

我有一个zoo 对象，包含超过 10 年的每周数据，并且我计算了这个系列的月滚动平均值.我想使用与此相对应的月度数据，并为此将每个月的最后一个每周数据点(作为整个月的代表)提取到一个单独的时间序列中.

I have a zoo object of weekly data over 10 years, and I've calculated the monthly rolling mean of this series. I want to work with monthly data that corresponds to this, and to that end pull the last weekly data point for each month, as representative for the whole month, into a separate time series.

我已经尝试了 aggregate ts 函数，但由于间距不均匀(即 4 周，并非总是一个月等)，因此遇到了问题.

I've tried the aggregate ts function but am having trouble since the spacing is not even (i.e. 4 weeks not always a month, etc).

推荐答案

月份的长度不同这一事实应该没有问题.看下面的例子:

The fact that months have a different length should be no problem. Look at the following example:

> library(xts)
> dates  <- as.Date("2013-01-01") + 7*(0:52)
> y.week <- zoo(rnorm(365),order.by=dates)
> head(y.week)
2013-01-01 2013-01-08 2013-01-15 2013-01-22 2013-01-29 2013-02-05 
 0.3648757 -0.7247121  0.4815929  0.5967042  1.6272563  0.8472303 
> y.mon  <- aggregate(y.week,
+                     by = format(dates,format="%Y-%m"),
+                     FUN=sum)
> head(y.mon)
   2013-01    2013-02    2013-03    2013-04    2013-05    2013-06 
 2.3457170  1.9640368 -0.3259688 -0.8710992  0.5430847 -0.1107915 

查看 strptime 的帮助页面以查看您可以使用的格式字符串代替上面的 "%Y-%m".

Look at the help page for strptime to see the format strings you can use in place of "%Y-%m" above.

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