Question

我有以下问题。我想以矩阵形式计算年度时间序列的回归。总的来说，我有56个时间序列，我从我想要检查的区域的网格点中提取出来，所以我每年得到56个值。我已将所有值绘制为图中的点。现在我想在这个图中添加一个回归线，其中包含所有数据。

我的目标是计算整个矩阵的回归。

library(zoo)

pdf(file="/home/user/name.pdf", pointsize=20, onefile = FALSE, width=18, height=11, paper = "special")
plot(mat.zoo[,1], pch=20, type="p", ylim=c(8,max(mat.zoo)),
     yaxt = "n", xaxt = "n", lwd = 1.5, main = "Some title", 
     ylab = "ylabtext", xlab ="", col = "black")

tt <- time(mat.zoo)
ix <- seq(1, length(tt), by=1) #every year a tick
labs <- format(tt[ix])
axis(side = 1, at = tt[ix], labels = labs,  tcl = -0.7, cex.axis = 1)

for (i in 2:ncol(mat.zoo)) {  
  #plot every column
  points(mat.zoo[,i], pch=20, lwd = 1.5)
}

## create ticks at every first y value 
axis(side = 2, at = seq(0, max(mat.zoo), by = 1), labels = FALSE)
iy <- seq(0, max(mat.zoo), 2)
axis(side = 2, at = iy, cex.axis = 1)

#this line doesn't work
abline( lm(mat.zoo ~ tt), col="light blue", lwd=3 )

dev.off()

图：

http://i.imgur.com/Ny5ERj1.png

一些示例数据，如果我使用dput（）

structure(c(14.6108611110572, 15.0943707315979, 16.4246753285039, 
15.4777258564571, 15.3910647660091, 14.9576052728563, 14.577379912167, 
15.6818364395762, 15.3935454316438, 14.6986382632628, 14.9616178291156, 
14.6208764396762, 17.4073263088521, 16.3932907105236, 16.4711871055354, 
15.7165524844793, 15.910687798697, 15.2800531253961, 16.2585353059321, 
14.9642915613775, 15.5682258772038, 15.7581733353644, 16.3600126905042, 
15.9906231843285, 16.4740591781654, 16.6207709477207, 16.7107736486755, 
15.3495937400046, 15.081738134456, 17.8213361743775, 17.0073514277019, 
16.0639354869614, 15.7564229038361, 16.4711872385234, 16.1474456418556, 
16.1012429675788, 14.935862417968, 14.649232718741, 14.7248073786802, 
16.3713171174875, 16.5047383689279, 15.6553509485205, 15.8069612127912, 
15.0880755914505, 15.9605131388024, 15.1647608142339, 15.0206531342878, 
15.8533914806642, 16.1936611693424, 14.4341552680467, 15.0030002589802, 
16.2373036559464, 15.4563912060316, 15.7540478676699, 14.4544119112367, 
14.1481450642128, 15.8808048538232, 15.3109864936677, 14.6184823877101, 
14.759740997088, 14.4554473653311, 17.1869089559961, 16.032779242263, 
15.9154018617995, 15.7003191635601, 16.1782858717824, 15.005330870126, 
16.1074524252519, 15.387333324397, 15.4238444378858, 15.7384875972114, 
16.3306448173221, 15.8050630623362, 16.5357139417134, 15.7318155157117, 
16.6027108391727, 15.3521994865507, 14.6028494060288, 17.0695642066462, 
16.5601941440799, 16.0704699986853, 15.9527367313925, 15.8492898967367, 
15.8094909404139, 15.9223122951851, 14.7427484210632, 14.3087395573591, 
14.9164340340289, 16.5109060631933, 16.1756705822203, 15.6869363317253, 
15.302941446409, 14.7871569748782, 16.2405108282472, 14.9030204259848, 
15.1076128392841, 15.7835364136346, 16.2406871099921, 13.9434587358454, 
14.8761562136977, 16.5604955686145, 15.3055531556642, 15.528200122034, 
14.3683664247369, 14.8660671257497, 16.2483828855783, 15.5912163679296, 
14.5206758668367, 15.0572249827849, 14.2126710362867, 16.7430589790551, 
15.913830135814, 15.5309377608968, 15.4301657033962, 16.1024796689616, 
14.9412190564665, 15.5415580911515, 15.6185795702858, 15.246965832492, 
15.5331896889331, 16.0527261022428, 16.2496153707101, 16.1013003488606, 
15.4012992267683, 16.6433171425044, 15.3443805149379, 15.0832591147848, 
17.2409394600713, 16.3670395392329, 15.8028463074112, 16.230362038712, 
15.8533914346074, 16.0962730847646, 15.4780493166121, 14.7644838005869, 
14.0160611132642, 14.7363498686371, 16.5339052116905, 16.1142787861115, 
15.1343982378726, 15.0479243093561, 14.8394739356758, 16.2015436792666, 
14.8852279610404, 15.171354759099, 15.8823805835669, 16.082598536468, 
13.6882801770178, 15.1822273858009, 16.7314060285488, 15.1822255101789, 
15.6470428935629, 14.6219009419668, 14.5344414346855, 17.0856674074961, 
15.6276761713817, 14.9656277726849, 15.0416098763217, 14.8660691394921, 
16.8350823196938, 15.7276830387531, 15.6464050524098, 15.7889210440969, 
15.8260661780512, 15.0685110014866, 15.5003231376182, 15.1818971179834, 
15.2523764253926, 15.2397513974873, 16.4076206985996, 16.2609962527472, 
15.9563455712026, 14.6758308266033, 15.9928106586864, 15.3388404382473, 
15.3352069271315, 17.491711796634, 16.3110401122382, 15.6722694212894, 
16.0979740581832, 15.9314161173117, 15.5309368794019, 15.5425227514293, 
14.8653903137068, 14.3680198631293, 14.6030824713595, 16.7764724794758, 
15.7590262768357, 14.9562687841841, 14.7258278360439, 15.00733114536, 
16.1086825085102, 14.8246425174662, 15.6697167018262, 15.5235314139726, 
15.810753562246), .Dim = c(49L, 4L), .Dimnames = list(c("1", 
"367", "732", "1097", "1462", "1828", "2193", "2558", "2923", 
"3289", "3654", "4019", "4384", "4750", "5115", "5480", "5845", 
"6211", "6576", "6941", "7306", "7672", "8037", "8402", "8767", 
"9133", "9498", "9863", "10228", "10594", "10959", "11324", "11689", 
"12055", "12420", "12785", "13150", "13516", "13881", "14246", 
"14611", "14977", "15342", "15707", "16072", "16438", "16803", 
"17168", "17533"), c("GB.1", "GB.2", "GB.3", "GB.4")), index = c(1960, 
1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 
1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 
1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 
1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 
2005, 2006, 2007, 2008), class = "zoo")

Answer 1

尝试将lm声明修改为

lm(as.vector(mat.zoo) ~ rep(tt, length.out = length(mat.zoo)))

多列时间序列的线性回归

1 个答案: