2016-05-26 4 views
0

時系列の構築に関するアドバイスが必要です。私は、408ヶ月間に渡って多数の場所の海面温度の月次データを含むファイルをたくさん持っています。あなたは、私がAを抽出している時系列を構築するには時系列の傾向の構築と分析

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") 

を見ることができるので、私はこれは、データフレームのほんの一部である次のような構造を持つデータフレームに

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

を毎月の値を集計しています場所にあるすべての毎月の値に対応するデータフレームの行の列に置き換え、(経度および緯度によって定義される)と、新たなデータフレームを作成

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") 

enter image description here

[今すぐ、その添加剤の傾向に季節成分およびランダム成分を分解し、元のデータ

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

enter image description here

から季節のコンポーネントを削除し、どのように私は、このデータ(sst1_noseason)のための線形回帰を得るのですか?私はlm()を試しましたが、データフレーム内には単一のvarしかないので、私はできないと思います。毎月の日付で新しい日付列(時間)を作成し、 lm (sst ~ time)を実行する必要がありますか?

時系列を扱う他のRパッケージがありますか?私はggseasとtidyrを見てきましたが、有望に見えますが、この分析をどのような場合でも実行するには日付列より作成する必要があるかもしれません。

私の最終的な目的は、各経度と緯度地点のトレンドに単一の値を設定し、海面温度の気候傾向が最も高い地域を探すための地図をプロットすることです。

おそらくもっと良い手順があり、時空間分析を実行している別のRパッケージを指すことができます。どんな助けもありがとう。あなたの助け

答えて

1

を事前に

おかげで、彼らは通常のように直感的ではありませんとに対処するための追加的な語彙を必要とするため、私は、Rに特化したクラスのファンではありません。ここでは、動物園のパッケージを使用して、data.frameに作られたのだ、時系列に変換しようとする試みです:

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 

プロットは、同様にdata.frameでよりintuitveです:

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

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

enter image description here

さらに、plotlyなどの対話型パッケージを使用して、ggplotlyで作成されたプロットをナビゲートできます。

library(plotly) 
ggplotly(p) 
+0

ありがとう@ adam-quekこれは、6.025e-05が時系列の回帰勾配、傾向であると思われます。おそらく、トレンドを適切に評価するために、あなたの提案をsst1_noseasonに適用する必要があります。 – pacomet

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