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R 使用XTS将每日时间序列转换为每月时间序列_R_Time Series_Xts - Fatal编程技术网

R 使用XTS将每日时间序列转换为每月时间序列

R 使用XTS将每日时间序列转换为每月时间序列,r,time-series,xts,R,Time Series,Xts,我使用xts包中的to.monthly命令将间隔不均的时间序列转换为月度时间序列,但在答案中省略了一些月份 例如,我的数据集如下:DXts [,1] 2001-03-22 57.0 2001-05-09 42.0 2001-08-15 56.0 2001-09-17 58.0 2002-03-11 66.0 2002-05-29 53.0 2002-07-17 53.0 2002-09-11 48.0 2003-03-21 63.0 2003-03-23 64.0 2003

我使用
xts
包中的
to.monthly
命令将间隔不均的时间序列转换为月度时间序列,但在答案中省略了一些月份

例如,我的数据集如下:DXts

           [,1]
2001-03-22 57.0
2001-05-09 42.0
2001-08-15 56.0
2001-09-17 58.0
2002-03-11 66.0
2002-05-29 53.0
2002-07-17 53.0
2002-09-11 48.0
2003-03-21 63.0
2003-03-23 64.0
2003-05-22 42.0
2003-07-22 45.0
2003-09-09 51.0
2004-03-15 57.0
2004-05-16 44.0
2004-07-28 58.0
2004-09-20 59.0
2005-03-18 64.0
2005-05-27 38.0
2005-07-21 52.0
2005-09-15 54.0
2006-09-09 54.0
2007-09-06 62.0
2008-09-05 62.0
2009-09-14 49.3
2010-09-14 60.2
2011-09-13 64.6
2012-09-12 70.2
2013-05-09 39.7
2013-06-06 51.3
2013-07-11 52.3
2013-08-09 53.1
2013-09-05 52.7
2013-10-17 56.6
2013-11-06 57.1
2013-12-04 55.3
2014-01-10 60.3
2014-02-07 66.1
2014-03-11 62.7
2014-04-07 63.1
2014-05-09 38.4
2014-06-05 46.4
2014-07-10 54.0
2014-08-12 57.3
2014-09-06 62.1
2014-10-07 62.1
2014-12-04 76.4
2015-01-10 66.0
2015-02-11 67.9
2015-03-02 70.1

DXts<- xts(udata2[,-1], order.by=as.Date(udata2[,1], Dformat))
2006-2009年的数据也丢失了


提前感谢您的帮助。

这是一个…现在已修复。几天后将在CRAN上。这是一个…现在已修复。几天后就要上岸了。
         DXts.Open
Mar 2001      57.0
May 2001      42.0
Aug 2001      56.0
Sep 2001      58.0
Mar 2002      66.0
May 2002      53.0
Jul 2002      53.0
Sep 2002      48.0
Mar 2003      63.0
May 2003      42.0
Jul 2003      45.0
Sep 2003      51.0
Mar 2004      57.0
May 2004      44.0
Jul 2004      58.0
Sep 2004      59.0
Mar 2005      64.0
May 2005      38.0
Jul 2005      52.0
Sep 2012      54.0
May 2013      39.7
Jun 2013      51.3
Jul 2013      52.3
Aug 2013      53.1
Sep 2013      52.7
Oct 2013      56.6
Nov 2013      57.1
Dec 2013      55.3
Jan 2014      60.3
Feb 2014      66.1
Mar 2014      62.7
Apr 2014      63.1
May 2014      38.4
Jun 2014      46.4
Jul 2014      54.0
Aug 2014      57.3
Sep 2014      62.1
Oct 2014      62.1
Dec 2014      76.4
Jan 2015      66.0
Feb 2015      67.9
Mar 2015      70.1