我找不到如何mts为时间序列制作对象的工作示例。
我做了一个输入数据的例子。有一个频率为4 的时间序列。mts我想将它分成4 个以格式表示的时间序列（在 文档中描述ts）：
要给
结果的类类，如果为 NULL 或“无”，则为无。单个系列的默认值为 "ts"，多个系列的默认值为 c( "mts" , "ts", "matrix")。
我怎么能拆分它？我找不到任何有关如何创建“mts”对象的示例文档。
Qtr1 Qtr2 Qtr3 Qtr4
1 100.00 102.09 102.50 102.60
2 102.66 102.01 100.70 102.21
3 102.50 102.81 102.91 103.08
4 103.25 101.70 101.10 101.49
5 100.12 99.40 99.28 97.75
6 96.65 99.03 99.28 99.91
7 99.29 98.57 98.45 100.27
8 100.65 102.12 101.55 101.55
9 99.51 99.95 98.91 96.87
10 95.14 94.82 96.04 96.91
11 95.53 93.14 92.97 94.54
12 91.72 92.35 94.79 94.78
13 95.50 95.97 94.64 96.56
14 96.45 95.13 94.32 92.92
structure(c(100, 102.09, 102.5, 102.6, 102.66, 102.01, 100.7,
102.21, 102.5, 102.81, 102.91, 103.08, 103.25, 101.7, 101.1,
101.49, 100.12, 99.4, 99.28, 97.75, 96.65, 99.03, 99.28, 99.91,
99.29, 98.57, 98.45, 100.27, 100.65, 102.12, 101.55, 101.55,
99.51, 99.95, 98.91, 96.87, 95.14, 94.82, 96.04, 96.91, 95.53,
93.14, 92.97, 94.54, 91.72, 92.35, 94.79, 94.78, 95.5, 95.97,
94.64, 96.56, 96.45, 95.13, 94.32, 92.92, 92.58, 89.74, 87.7,
89.5, 86.69, 87.91, 89.12, 88.93, 89.95, 90.42, 90.22, 90.75,
90.2, 89.5, 90.52, 90.88, 90.98, 91.85, 92.03, 91.85, 92.54,
92.69, 92.36, 92.35, 91.56, 92.67, 92.88, 92.26, 92.36, 92.51,
92.26, 92.47, 92.65, 92.89, 91.67, 91.95, 92.77, 92.59, 91.83,
92.2, 91.47, 92.33, 92.03, 92.74, 92.74, 93.13, 94.61, 95.23,
95.04, 95.35, 96.46, 96.6, 95.93, 95.61, 95.22, 95.34, 95.58,
95.64, 94.41, 94.73, 93.64, 92.87, 92.89, 93.67, 94.69, 94.51,
94.14, 94.53, 94.63, 95.15, 94.67, 95.75, 96.16, 96.99, 97.3,
97.97, 98.34, 98.28, 97.85, 97.54, 97.48, 97.09, 97.28, 97.8,
97.08, 96.28, 94.58, 92.94, 91.26, 91.92, 91.03, 92.13, 94.45,
94.68, 95.02, 95.79, 92.29, 89.45, 91.52, 93.9, 94.51, 95.47,
95.1, 93.4, 92.55, 93.33, 94.33, 95.8, 96.19, 96.4, 96.72, 96.34,
96.7, 96.22, 97.27, 96.84, 97.08, 97.14, 97.45, 97.65, 96.6,
96.99, 95.89, 95.62, 96.48, 97.5, 97.57, 98.43, 98.37, 99.31,
99.27, 99.38, 98.45, 97.56, 98.06, 97.39, 97.69, 98.21, 98.12,
97.56, 97.97, 98.01, 98.47, 98.14, 97.87, 99.25, 99.73, 99.55,
99.8, 99.74, 98.96, 98.12, 98.07, 98.12, 98.53, 97.87, 98.66,
98.89, 98.9, 99.94, 99.66, 98.7, 98.59, 99.22, 98.68, 98.74,
99.39, 100.06, 99.77, 99.48, 98.73, 99.41, 98.95, 98.35, 97.54,
98.64, 97.71, 98.44, 98.85, 98.31, 98.22, 97.72, 97.27, 97.31,
97.31, 97.27, 96.9, 95.1, 94.73, 94.03, 95.68, 95.94, 97.13,
97.39, 96.62, 96.93, 97.26, 97.48, 98.23, 98.1, 97.52, 96.88,
96.81, 97.39, 98.39, 97.93, 98.48, 98.64, 97.77, 97.74, 98.44,
99.1, 99.16, 99.27, 100.41, 99.54, 100.67, 100.21, 100.87, 101.45,
101.42, 101.52, 101.55, 101.7, 101.8, 102.18, 102.16, 102.05,
101.86, 102.97, 103.43, 103.75, 103.85, 103.86, 103.99, 103.87,
103.39, 104.23, 103.47, 102.98, 103.01, 102.92, 102.75, 102.24,
102.22, 103.86, 104.07, 103.72, 102.97, 102.86, 103.26, 102.72,
103.57, 103.35, 103.88, 103.86, 104.56, 104.79, 104.9, 104.66,
105.25, 105.1, 105.4, 105.61, 106.15, 106.28, 106.15, 105.53,
105.67, 105.94, 106.88, 107.58, 107.64, 107.61, 107.35, 107.41,
107.53, 107.91, 108.02, 107.77, 108.07, 108.4, 108.69, 108.71,
107.81, 107.18, 108.02, 107.87, 107.53, 107.64, 108.33, 108.87,
108.71, 108.45, 108.64, 108.7, 108.74, 108.79, 109.23, 109.42,
109.82, 109.52, 108.95, 109.26, 109.36, 109.35, 110.22, 110.72
), .Dim = c(364L, 1L), index = structure(c(1447632000, 1447718400,
1447804800, 1447891200, 1447977600, 1448236800, 1448323200, 1448409600,
1448496000, 1448582400, 1448841600, 1448928000, 1449014400, 1449100800,
1449187200, 1449446400, 1449532800, 1449619200, 1449705600, 1449792000,
1450051200, 1450137600, 1450224000, 1450310400, 1450396800, 1450656000,
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1451865600, 1451952000, 1452038400, 1452124800, 1452211200, 1452470400,
1452556800, 1452643200, 1452729600, 1452816000, 1453075200, 1453161600,
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1453939200, 1454025600, 1454284800, 1454371200, 1454457600, 1454544000,
1454630400, 1454889600, 1454976000, 1455062400, 1455148800, 1455235200,
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1492992000, 1493078400), tzone = "UTC", tclass = "Date"), .indexCLASS = "Date", tclass = "Date", .indexTZ = "UTC", tzone = "UTC", .Dimnames = list(
NULL, "Series 1"), class = "ts", .Tsp = c(1, 91.75, 4))
使用xts和zoo包，您可以创建单独的时间序列并按如下方式合并它们：
library("xts")
library("zoo") #for as.yearqtr
#tsDF, your input data
#extract individual time series
tsMat = matrix(tsDF,ncol=4)
#setup hypothetical indices as yearqtr e.g. 1990 Q1, 1992 Q2 etc.
startYear1 = 1990
startYear2 = 1990
startYear3 = 1991
startYear4 = 1992
index1=seq(startYear1,by=1,length.out=nrow(tsMat))
index2=seq(startYear2,by=1,length.out=nrow(tsMat))
index3=seq(startYear3,by=1,length.out=nrow(tsMat))
index4=seq(startYear4,by=1,length.out=nrow(tsMat))
index1 = as.yearqtr(paste(index1,"Q1",sep=" "))
index2 = as.yearqtr(paste(index2,"Q2",sep=" "))
index3 = as.yearqtr(paste(index3,"Q3",sep=" "))
index4 = as.yearqtr(paste(index4,"Q4",sep=" "))
#combine indices in a list
listIndices = list(index1,index2,index3,index4)
nameVec = paste0("Qtr",1:4)
#Use lapply to create individual xts time series with its correponding index created above
tsList =
lapply(1:ncol(tsMat), function(x) {
xtsObj = xts(tsMat[,x],order.by=listIndices[[x]])
colnames(xtsObj) = nameVec[x]
return(xtsObj)
})
输出：
#Use Reduce function to merge the list output from previous step
tsAggregate = Reduce(function(x,y) merge.xts(x,y),tsList)
head(tsAggregate,10)
# Qtr1 Qtr2 Qtr3 Qtr4
#1990 Q1 100.00 NA NA NA
#1990 Q2 NA 91.95 NA NA
#1991 Q1 102.09 NA NA NA
#1991 Q2 NA 92.77 NA NA
#1991 Q3 NA NA 97.57 NA
#1992 Q1 102.50 NA NA NA
#1992 Q2 NA 92.59 NA NA
#1992 Q3 NA NA 98.43 NA
#1992 Q4 NA NA NA 100.21
#1993 Q1 102.60 NA NA NA
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