建立和分析时间序列的趋势

Question

我需要有关建立时间序列的建议。我有一堆文件，包含408个月内多个地点的海面温度月度数据。我在数据框中汇总了具有以下结构的月度值

longitude, latitude, SST for month 1, SST for month 2, .... SST for month n

这只是数据框的一小部分，因此您可以看到

dput(sst_subset)
structure(list(lon = c(-19.875, -19.625, -19.375, -19.125), lat = c(30.125,
30.125, 30.125, 30.125), sst = c(293.197412803228, 293.092251515256,
292.999348291526, 293.013219258958), sst.1 = c(292.490350607051,
292.504279178168, 292.502850606771, 292.438922036772), sst.2 = c(291.994832184947,
291.887412832509, 291.832896704695, 291.810638640677), sst.3 = c(292.095993473008,
292.066660140331, 292.091993473098, 292.110326806021), sst.4 = c(293.071606354427,
293.095799902274, 293.106445063326, 293.116122482465), sst.5 = c(294.981993408501,
294.996326741514, 295.004660074661, 295.018993407674), sst.6 = c(295.568703072806,
295.600315975326, 295.597735330222, 295.49418694544), sst.7 = c(296.250961122073,
296.175154672154, 296.079348222683, 296.052251449095)), .Names = c("lon",
"lat", "sst", "sst.1", "sst.2", "sst.3", "sst.4", "sst.5", "sst.6",
"sst.7"), row.names = c(NA, 4L), class = "data.frame")

为了建立一个时间序列，我提取了一行数据框，它对应于一个位置的所有月值（由经度和纬度定义），转换为一列并创建一个新的数据框

ncolumnes<-ncol(sst_all)
sst_point1<-sst_all[1:3,ncolumnes]
sst1_df <- as.data.frame(t(sst_point1))

dput(sst1_ts)
structure(c(293.197412803228, 292.490350607051, 291.994832184947,
292.095993473008, 293.071606354427, 294.981993408501, 295.568703072806,
296.250961122073, 296.73166003606, 296.385154667461, 294.611660083445,
293.484186990367, 292.372896692626, 291.348207775437, 291.627090257683,
291.957326809441, 292.71063862056, 293.545326773947, 295.897412742879,
296.671928854599, 296.681326703851, 296.483864342674, 294.934660076226,
293.76709020985, 292.45870314232, 291.399993488565, 291.446767681068,
291.918993476964, 292.889025713347, 293.71099343691, 294.01418697852,
296.219025638916, 296.90166003226, 296.119993383065, 294.936326742855,
293.405154734069, 291.834509607885, 291.638564911804, 291.527412840556,
292.055326807251, 292.020961216621, 294.573660084295, 295.850315969738,
295.978380483004, 296.863660033109, 297.228380455065, 296.00866005222,
294.711606317771, 293.067735386772, 291.577136341748, 291.426445100877,
291.602993484028, 292.42096120768, 293.742993436195, 294.709348253305,
295.973219192797, 296.913993365318, 296.213219187433, 294.494326752735,
293.59225150408, 292.492251528667, 291.838207764485, 292.225477341082,
292.385993466526, 294.063864396765, 295.407326732328, 295.98386435385,
297.471928836718, 297.880660010378, 297.070638523107, 294.419993421063,
293.154509578381, 292.307735403759, 291.263441767479, 291.197412847932,
292.566660129155, 293.590316020253, 294.627660083088, 295.085477277156,
296.166122414292, 296.608660038809, 296.143864350273, 294.568660084407,
293.292251510786, 292.269670888481, 291.425350630855, 291.424832197687,
291.351326822986, 292.945799905626, 296.319660045269, 297.158380456629,
297.712251411991, 297.68699334804, 296.391928860858, 294.519660085502,
292.856445068914, 291.953864443927, 291.813922050742, 291.561606388179,
291.680660148958, 293.242574092542, 294.903326743593, 295.748057907507,
297.715799799009, 298.00999334082, 297.161606263009, 295.690326726002,
294.133541814562, 292.727412813734, 292.312493468169, 291.931928960546,
291.646326816392, 291.639670902563, 293.339326778551, 295.357090174311,
297.108703038385, 298.576993328147, 296.577735308317, 295.347660066995,
293.425154733622, 292.446445078078, 291.951027959007, 291.967735411359,
291.957993476093, 292.77838055453, 294.320326756624, 295.738703069007,
296.466122407586, 296.747993369028, 296.3506385392, 294.958326742363,
293.579348278562, 292.182574116234, 291.279279205549, 291.659993482754,
291.872993477993, 292.670316040816, 294.635326749583, 295.305477272238,
296.348057894096, 297.221993358433, 296.08612241608, 294.042993429489,
292.95160635711, 292.009670894293, 291.243207777784, 290.859025758721,
291.319993490353, 292.587412816863, 294.628660083066, 294.788057928965,
296.454832085258, 296.454326708925, 296.265477250781, 295.604326727924,
294.013219236607, 293.043541838926, 292.523922034872, 292.038703151708,
292.477326797818, 294.406122453631, 295.478993397392, 296.886122398199,
297.362251419814, 297.879993343726, 296.978703041291, 295.939326720436,
293.980638592173, 293.048703129133, 291.979993475601, 291.462896712966,
292.266326802534, 293.046445064667, 294.074993428774, 295.435477269333,
296.886122398199, 297.262660024191, 296.517090148383, 295.193326737111,
293.43967086233, 292.486122496546, 292.043564902752, 291.806767673021,
292.480660131077, 293.707735372467, 295.127326738586, 295.877735323964,
296.78192885214, 297.788326679108, 297.02450949188, 295.75766005783,
294.890315991195, 293.371606347722, 292.426422037051, 292.379670886022,
292.746993458457, 293.078057967186, 294.512993418984, 295.54612242815,
296.109348222013, 297.133660027074, 296.816767561039, 295.519326729824,
294.220638586809, 292.947412808816, 291.781422051468, 291.450638648723,
292.118660139168, 293.846122466148, 294.885993410647, 295.964832096211,
297.745154637062, 298.001326674347, 297.287735292448, 295.068993406557,
293.324509574581, 291.593864451974, 291.534821071758, 291.633219289804,
292.017993474752, 292.164187019871, 293.516660107921, 295.506122429044,
296.33321918475, 297.117660027432, 296.34741273282, 294.993660074907,
293.8032192413, 293.077735386549, 292.511779178, 292.344832177124,
292.459326798221, 293.437412797864, 295.860326722202, 296.416444989342,
297.083864329263, 298.678993325867, 297.782251410427, 295.657993393391,
293.652251502739, 293.274186995061, 292.307136325432, 291.922251541408,
291.564993484877, 292.452574110199, 293.996326763866, 294.823219218502,
296.541283696229, 297.421660020637, 296.747735304518, 295.771993390843,
294.041928913384, 293.317090219908, 292.421422037163, 292.680316040593,
292.577660128909, 293.240316028076, 295.254993402399, 296.815477238487,
297.524186900066, 298.126326671553, 297.598380446795, 295.563326728841,
294.207735361291, 293.43805795914, 293.115855519178, 292.753864426046,
292.466993464716, 292.925154744798, 296.035326718291, 296.538380470487,
298.612573972513, 298.241993335634, 297.065154652261, 295.770993390866,
293.72934827521, 292.379670886022, 291.370350632085, 291.601928967922,
292.473326797908, 293.597412794288, 294.678993415274, 296.042896610595,
297.383541741919, 297.729326680427, 296.714186918171, 295.008993407898,
293.465154732728, 292.365154757315, 292.279993468896, 291.722896707154,
292.651993460581, 293.469670861659, 295.145993404835, 296.262896605677,
297.257090131842, 297.550326684428, 297.544832060895, 296.194326714737,
294.499670838637, 293.095799902274, 292.836064885038, 292.445799916802,
292.78566012426, 293.216445060867, 294.3869934218, 295.256767595908,
296.333864346026, 296.692993370257, 296.250315960797, 295.23466006952,
293.713864404588, 292.874187004001, 292.378614156346, 291.931606379908,
292.099326806267, 293.999348269175, 295.055660073521, 296.170638543223,
296.729670788792, 297.024993362837, 296.646444984201, 294.817993412167,
293.368057960704, 292.39579991792, 291.174279207896, 291.343541876924,
291.974660142387, 292.742574103717, 294.785993412882, 296.685477241393,
297.067735297365, 297.318326689613, 297.265154647791, 296.419993376359,
294.439993420616, 293.224509576816, 293.140707735371, 292.928057970539,
293.028326785502, 293.116767643741, 294.067993428931, 295.034832116997,
296.24192886421, 297.204660025487, 297.0212836855, 295.618993394263,
294.195477297049, 293.26644505975, 292.1507077575, 291.842574123834,
292.212326803741, 292.898380551848, 293.698660103853, 294.868057927177,
296.104832093081, 297.440660020212, 296.802574012969, 295.234993402846,
293.692574082483, 292.617090235554, 291.535510726915, 291.344832199475,
292.175660137894, 293.799025693007, 295.795993390307, 296.195799832983,
297.432573998888, 298.643659993323, 297.612251414226, 296.027326718469,
294.692896640769, 293.446122475089, 292.611779175765, 292.494832173771,
293.027326785525, 293.948380528378, 294.144326760558, 295.259670821649,
296.524509503055, 297.014660029734, 296.854832076317, 295.413326732193,
294.306122455866, 292.857735391466, 291.982493475545, 291.549025743299,
292.710993459262, 293.044832161478, 294.210660092408, 296.063864352061,
296.959993364289, 298.161660004097, 297.040315943139, 295.179326737424,
293.474509571228, 292.265799920826, 291.409993488342, 291.042574141715,
291.81732681257, 293.374186992826, 294.908993410133, 296.215799832536,
297.686767541593, 298.667326659461, 297.63999334909, 295.589993394911,
294.077412783559), .Dim = c(408L, 1L), .Dimnames = list(NULL,
    "1"), .Tsp = c(1982, 2015.91666666667, 12), class = "ts")

然后分解其附加趋势，季节性和随机成分，并从原始数据中删除季节性成分

sst1_dec<-decompose(sst1_ts)
sst1_noseason<-sst1_ts - sst1_dec$seasonal

现在，我如何获得此数据的线性回归（sst1_noseason）？我试过lm（），但由于数据帧中只有一个var，我想我不能。我应该使用月度日期构建新的日期列（时间），然后运行lm (sst ~ time)吗？

是否还有其他R套件处理可以做得更好的时间序列？我看过ggseas和tidyr，他们看起来很有希望但是我可能需要构建比date列来运行这个分析无论如何。

我的最终目标是在每个经度和纬度点获得趋势的单一值，并绘制地图以查找海面温度气候趋势最高的区域。

也许有一个更好的程序，你可以指向另一个运行时空分析的R包。任何帮助将不胜感激。

提前感谢您的帮助

Answer 1

我不是R中专门课程的粉丝，因为他们通常不那么直观，需要额外的词汇来处理。这是尝试使用动物园包将您制作的时间序列转换为data.frame：

library(zoo)

df1 <- data.frame(zoo(sst1_ts), time=as.yearmon(time(sst1_ts)))
df1$jday <- as.Date(df1$time)

(fit1<-lm(X1 ~ jday, df1))

Call:
lm(formula = X1 ~ jday, data = df1)

Coefficients:
(Intercept)         jday  
  2.937e+02    6.025e-05 

绘图也更适合data.frame：

library(ggplot2)
base <- ggplot(df1, aes(jday, X1)) + geom_line()  + stat_smooth(method="lm") 

p<-base + scale_x_date(date_labels = "%Y")

您可以进一步使用交互式软件包（如plotly）来导航使用ggplotly创建的图。

library(plotly)
ggplotly(p)