不規則な時系列データ - 定期的にすることはできますか？ r

Question

私は1日に複数のデータポイントを意味する5時間ごとに情報を取得するようにプログラムされたデータを持っています。問題は、データロガーが故障したり、バッテリが消耗したり、データが失われたり、失敗したりすることがあります。

すべての分析は、これらの日付に基づいています。私は、この日付/タイムスタンプに基づいてすべてをソートし、フィルタリングして選択する必要があります。現時点では、自分のデータを選択してサブセット化するために、長文のスクリプトを実行しています。さらに私はいくつかのデータロガー（個人）を持っているので、バッチ処理も行っています。例えば、私は、サブセットと日ごとに1つだけのデータポイントを使用したいと私

#Subset data by minimum time interval 
    SubsetData = T 
    MinInterval = 47 #minimum time interval (in hours) between consecutive locations 
    ########### 
    ##Setting the date and time to be recognized as date time 
    loc$DateTime = as.POSIXct(strptime(loc$DT,"%m/%d/%Y %H:%M",tz="UTC"),tz="UTC") 
    ### Code to subset data based on minimum time interval between locations 
    if (SubsetData ==T){ 
      row = 0 
      EndLoc = 2 
      SubData1 = loc[1,] 
      IDNames = levels(loc$ID) 
    for (n in 1:length(IDNames)){ 
     IndivData = loc[loc$ID==IDNames[n],] 
     row = row+1 
     SubData1[row,]=IndivData[1,] 
    while (EndLoc<nrow(IndivData)){ 
      timediff = difftime(IndivData$DateTime[EndLoc],SubData1$DateTime[row],units = "hours") 
    if (timediff>MinInterval){ 
     row = row+1 
     SubData1=rbind(SubData1,IndivData[EndLoc,]) 
     EndLoc = EndLoc+1 
     } else{ 
       EndLoc = EndLoc+1 
       } 
     } #end while loop 
     } #end loop through individuals 
    loc = SubData1 
    } #end conditional to subset data 
    } 
    ### End Code to subset data' 

ので、より簡単な操作をするために、時系列データに私のデータを作成する方法はありますか？私はZoo package a xtsの議論を見ましたが、これらはデータが規則的な時系列であることを必要とするようです。私は、データがts形式であることを必要とするため、特定のスクリプトを使用しなくてもよく、データをその素敵なフォーマットにする方法を見つけることができません。これを自分自身に教える良いリソースはありますか？私はTSを使用すべきでしょうか？ガボールが言ったように、動物園のよくある質問は、日ごとに複数の観測を凝集させる方法があり、不規則な時系列を扱うことができ structure(list(ID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("c_002", "c_402"), class = "factor"), Long = c(-147.635233, -147.635232, -147.63632, -147.636136, -147.63628, -147.635743, -147.631785, -147.619598, -147.605088, -147.602119, -147.179737, -147.133275, -147.106584, -147.033649, -147.016078, -147.031872, -146.940969, -146.862538, -146.751214, -146.696238, -146.710799), Latitude = c(67.911827, 67.911193, 67.911048, 67.911169, 67.911625, 67.911767, 67.919419, 67.926327, 67.925352, 67.926318, 70.017026, 70.041163, 70.057988, 70.087812, 70.117134, 70.147184, 70.145115, 70.136103, 70.1276, 70.103395, 70.079301), DT = structure(c(2L, 3L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 14L, 393L, 395L, 396L, 398L, 399L, 401L, 402L, 404L, 405L, 407L, 409L), .Label = c("05/01/2006 00:00", "05/01/2006 00:01", "05/01/2006 05:00", "05/01/2006 05:01", "05/01/2006 10:00", "05/01/2006 15:01", "05/01/2006 20:00", "05/01/2006 20:01", "05/02/2006 01:00", "05/02/2006 06:00", "05/02/2006 11:00", "05/02/2006 16:01", "05/02/2006 21:00", "05/02/2006 21:01", "05/03/2006 02:00", "05/03/2006 02:01", "05/03/2006 07:00", "05/03/2006 07:01", "05/03/2006 12:00", "05/03/2006 17:00", "05/03/2006 17:01", "05/03/2006 22:00", "05/03/2006 22:01", "05/04/2006 03:00", "05/04/2006 03:01", "05/04/2006 08:00", "05/04/2006 08:01", "05/04/2006 13:00", "05/04/2006 18:00", "05/04/2006 23:00", "05/04/2006 23:01", "05/05/2006 04:00", "05/05/2006 09:00", "05/05/2006 09:01", "05/05/2006 14:00", "05/05/2006 19:00", "05/06/2006 00:00", "05/06/2006 00:01", "05/06/2006 05:00", "05/06/2006 05:01", "05/06/2006 10:00", "05/06/2006 10:01", "05/06/2006 15:01", "05/06/2006 20:00", "05/06/2006 20:01", "05/07/2006 01:00", "05/07/2006 01:01", "05/07/2006 06:00", "05/07/2006 06:01", "05/07/2006 11:00", "05/07/2006 16:00", "05/07/2006 16:01", "05/07/2006 21:00", "05/08/2006 02:00", "05/08/2006 07:01", "05/08/2006 12:00", "05/08/2006 17:00", "05/08/2006 17:01", "05/08/2006 22:00", "05/08/2006 22:01", "05/09/2006 03:00", "05/09/2006 03:01", "05/09/2006 08:00", "05/09/2006 08:01", "05/09/2006 13:00", "05/09/2006 13:01", "05/09/2006 18:00", "05/09/2006 23:00", "05/09/2006 23:01", "05/10/2006 04:00", "05/10/2006 04:01", "05/10/2006 09:00", "05/10/2006 09:01", "05/10/2006 14:00", "05/10/2006 14:01", "05/10/2006 19:00", "05/10/2006 19:03", "05/11/2006 00:00", "05/11/2006 05:00", "05/11/2006 10:00", "05/11/2006 10:01", "05/11/2006 15:01", "05/11/2006 15:02", "05/11/2006 20:00", "05/11/2006 20:01", "05/12/2006 01:00", "05/12/2006 01:01", "05/12/2006 06:00", "05/12/2006 11:00", "05/12/2006 16:00", "05/12/2006 16:01", "05/12/2006 21:00", "05/12/2006 21:01", "05/13/2006 02:00", 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"07/10/2006 20:00", "07/11/2006 01:00", "07/11/2006 01:01", "07/11/2006 06:00", "07/11/2006 06:01", "07/11/2006 11:00", "07/11/2006 11:01", "07/11/2006 16:00", "07/11/2006 21:00", "07/12/2006 02:00", "07/12/2006 02:01", "07/12/2006 07:01", "07/12/2006 12:00", "07/12/2006 12:01", "07/12/2006 17:00", "07/12/2006 17:01", "07/12/2006 22:00", "07/12/2006 22:01", "07/13/2006 03:01", "07/13/2006 08:01", "07/13/2006 08:02", "07/13/2006 13:00", "07/13/2006 13:01", "07/13/2006 18:01", "07/13/2006 23:01", "07/14/2006 04:00", "07/14/2006 04:01", "07/14/2006 09:00", "07/14/2006 09:01", "07/14/2006 14:00", "07/14/2006 14:01", "07/14/2006 19:00", "07/14/2006 19:01", "07/15/2006 00:00", "07/15/2006 00:01", "07/15/2006 05:00", "07/15/2006 10:01", "07/15/2006 15:00", "07/15/2006 15:01", "07/15/2006 20:02", "07/15/2006 20:03", "07/16/2006 01:00", "07/16/2006 01:01", "07/16/2006 06:00", "07/16/2006 06:01", "07/16/2006 11:00", "07/16/2006 11:03", "07/16/2006 16:01", "07/16/2006 21:00", "07/16/2006 21:02", 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"07/25/2006 00:00", "07/25/2006 00:01", "07/25/2006 05:00", "07/25/2006 05:01", "07/25/2006 10:01", "07/25/2006 15:00", "07/25/2006 15:01", "07/25/2006 20:01", "07/26/2006 01:00", "07/26/2006 01:01", "07/26/2006 06:00", "07/26/2006 11:00", "07/26/2006 16:01", "07/26/2006 21:00", "07/26/2006 21:01", "07/27/2006 02:00", "07/27/2006 02:01", "07/27/2006 07:00", "07/27/2006 07:01", "07/27/2006 12:00", "07/27/2006 17:00", "07/27/2006 22:01", "07/28/2006 03:00", "07/28/2006 03:01", "07/28/2006 08:00", "07/28/2006 08:01", "07/28/2006 13:00", "07/28/2006 18:00", "07/28/2006 23:01", "07/29/2006 04:00", "07/29/2006 04:03", "07/29/2006 09:00", "07/29/2006 14:00", "07/29/2006 19:00", "07/30/2006 00:00", "07/30/2006 00:01", "07/30/2006 05:00", "07/30/2006 05:01", "07/30/2006 10:00", "07/30/2006 10:01", "07/30/2006 15:00", "07/30/2006 20:01", "07/31/2006 01:01", "07/31/2006 01:03", "07/31/2006 06:00", "07/31/2006 06:01", "07/31/2006 11:00", "07/31/2006 11:01", "07/31/2006 16:00", "07/31/2006 21:01"), class = "factor")), .Names = c("ID", "Long", "Latitude", "DT"), class = "data.frame", row.names = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 706L, 707L, 708L, 709L, 710L, 711L, 712L, 713L, 714L, 715L, 716L))

Answer 1

ライブラリ（動物園）、および：ここでは

は私のデータがどのように見えるかのサンプルです：

z <- zoo(x=data.frame(....), order.by=loc$DateTime) # translate 'loc' into zoo somehow 

za <- aggregate(z, identity, mean) # take the mean of identically timed objects 

...とローカルフィットデータに欠落データを埋める：

g <- seq(start(z),end(z),by=1/frequency(z)) 
zi <- na.locf(z,xout=g)