Linear regression of time series over multiple col

2019-08-26 05:26发布

问题:

I have the following problem. I want to compute the regression of an annual time series in matrix form. In total, I have 56 time series I extracted from gridpoints of an area I want to examine, so that I've got 56 values per year. I've plotted all values as points in a figure. Now I want to add a regression line to this figure, which contains all data.

My goal is to compute the regression for the whole matrix.

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()

figure:

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

Some sample data, if I use 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")

回答1:

Try modifying your lm statement to

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