如何解决如何将不规则年份间隔的数据帧转换为ts以进行时间序列分析?
我有一个具有不规则时间间隔的数据集,我试图将其可视化为时间序列数据并预测2019年。我想知道如何将R中的数据转换为“ ts”,以及数据的频率在不规则的时间(年)间隔内可用? 我的数据如下所示:(这是一部分,完整的数据集包括2102个观测值)
structure(list(Year = structure(c(1L,1L,2L,3L,5L,4L,4L),.Label = c("1993","1999","2006","2011","2016"),class = "factor"),Region = c("South","South","North","East","West","West"),statename = c("Andhra Pradesh","Andhra Pradesh","Uttarakhand","Haryana","NCT of Delhi","Rajasthan","uttar Pradesh","Bihar","Sikkim","Arunachal Pradesh","Nagaland","Manipur","Mizoram","KERALA","LAKSHADWEEP","MADHYA PRADESH","MADHYA PRADESH"
),statecode = c(28,28,5,6,7,8,9,10,11,12,13,14,15,32,31,23,23),disctrictcode = c(1,2,3,4,17,18,20,NA,218,219,220,221,222,223,224,225,226,227,228,601,594,590,587,465,461,459,457,441,447,420),LPG = c(1.5625,1.79640718562874,2.40963855421687,0.609756097560976,5.76923076923077,19.6319018404908,5.07246376811594,1.05263157894737,1.69491525423729,3.2,5.94059405940594,1.11111111111111,5.23255813953488,4.6875,1.08108108108108,4.54545454545455,1.5748031496063,4.76190476190476,18.2117388919364,10.1745936183022,55.607476635514,2.84514925373134,3.67709936719685,2.55157437567861,29.6979865771812,16.6825548141087,8.89787664307381,22.8630278063852,35.2459016393443,16.0183066361556,11.5853658536585,14.9032992036405,11.4190687361419,11.9521912350598,10.4426787741203,10.2941176470588,8.53658536585366,14.2228739002933,10.6060606060606,7.45098039215686,25.0891561083135,35.0948454610251,11.2079289927582,2.85374554102259,1.94829277137229,1.83006535947712,2.22847511653655,1.54357439899654,3.90050051315975,2.78252669830342,1.60864503942542
)),row.names = c(1L,6L,7L,8L,9L,10L,388L,389L,390L,391L,392L,393L,394L,395L,396L,397L,398L,810L,811L,812L,813L,814L,815L,816L,817L,818L,819L,820L,910L,911L,912L,913L,914L,915L,916L,917L,918L,919L,920L,1740L,1741L,1742L,1743L,1744L,1745L,1746L,1747L,1748L,1749L,1750L),class = "data.frame")
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