d <- read.csv("file.csv")
avgHumidity <-numeric(0)#月平均风级
length(avgHumidity)<- 60
for(i in 2012:2016){
for(j in 1:12){
print((i-2012)*12+j)
avgHumidity[(i-2012)*12+j]<-mean(c(d$最大风级[grep(paste(i,"/",j,"/",sep=""),d$日期)],
d$最小风级[grep(paste(i,"/",j,"/",sep=""),d$日期)]),na.rm=TRUE)
}
}
avgHumidityTS<- ts(avgHumidity,frequency=12,start=c(2012,1))
plot.ts(avgHumidityTS,main="长春2012-2016年月平均风级图",xlab="时间",ylab="月平均风级")
lowestTS <-ts(d$最小风级[1:(360*4)],frequency=360,start=c(2012,1))
highestTS <-ts(d$最大风级[1:(360*4)],frequency=360,start=c(2012,1))
plot.ts(highestTS,col="red",main="长春2012-2016年最高最低风级时序图",xlab="时间轴",ylab="风级")
lines(lowestTS,col="blue")
legend("topright",c("最大风级","最小风级"),col=c("red","blue"),lty=1)
highestTS<-ts(d$最大风级,frequency=360,start=c(2012,1))
lowestTS<-ts(d$最小风级,frequency=360,start=c(2012,1))
highestForecasts<-HoltWinters(highestTS)
lowestForecasts<-HoltWinters(lowestTS)
lowestForecasts
highestForecasts
library("forecast")
highestForecast2<- forecast.HoltWinters(highestForecasts,h=360)
lowestForecast2<- forecast.HoltWinters(lowestForecasts,h=360)
highestForecast3<-ts(highestForecast2$mean,frequency=360,start=c(2017,1))
lowestForecast3<-ts(lowestForecast2$mean,frequency=360,start=c(2017,1))
plot(highestForecast3,col="red",ylim=c(0,15),main="长春2017年最大最小风级预测时序图",xlab="时间",ylab="风级")
lines(lowestForecast3,col="blue")
legend("topright",c("最大风级","最小风级"),col=c("red","blue"),lty=1)
附件已添加改一下名就行
为什么会出现下面这问题
highestForecast2$residuals
Time Series:
Start = c(2012, 1)
End = c(2017, 27)
Frequency = 360
[1] NA NA NA NA NA
[6] NA NA NA NA NA
[11] NA NA NA NA NA
[16] NA NA NA NA NA
[21] NA NA NA NA NA
[26] NA NA NA NA NA
[31] NA NA NA NA NA
[36] NA NA NA NA NA
[41] NA NA NA NA NA
[46] NA NA NA NA NA
[51] NA NA NA NA NA
[56] NA NA NA NA NA
[61] NA NA NA NA NA
[66] NA NA NA NA NA
[71] NA NA NA NA NA
[76] NA NA NA NA NA
[81] NA NA NA NA NA
[86] NA NA NA NA NA
[91] NA NA NA NA NA
[96] NA NA NA NA NA
[101] NA NA NA NA NA
[106] NA NA NA NA NA
[111] NA NA NA NA NA
[116] NA NA NA NA NA
[121] NA NA NA NA NA
[126] NA NA NA NA NA
[131] NA NA NA NA NA
[136] NA NA NA NA NA
[141] NA NA NA NA NA
[146] NA NA NA NA NA
[151] NA NA NA NA NA
[156] NA NA NA NA NA
[161] NA NA NA NA NA
[166] NA NA NA NA NA
[171] NA NA NA NA NA
[176] NA NA NA NA NA
[181] NA NA NA NA NA
[186] NA NA NA NA NA
[191] NA NA NA NA NA
[196] NA NA NA NA NA
[201] NA NA NA NA NA
[206] NA NA NA NA NA
[211] NA NA NA NA NA
[216] NA NA NA NA NA
[221] NA NA NA NA NA
[226] NA NA NA NA NA
[231] NA NA NA NA NA
[236] NA NA NA NA NA
[241] NA NA NA NA NA
[246] NA NA NA NA NA
[251] NA NA NA NA NA
[256] NA NA NA NA NA
[261] NA NA NA NA NA
[266] NA NA NA NA NA
[271] NA NA NA NA NA
[276] NA NA NA NA NA
[281] NA NA NA NA NA
[286] NA NA NA NA NA
[291] NA NA NA NA NA
[296] NA NA NA NA NA
[301] NA NA NA NA NA
[306] NA NA NA NA NA
[311] NA NA NA NA NA
[316] NA NA NA NA NA
[321] NA NA NA NA NA
[326] NA NA NA NA NA
[331] NA NA NA NA NA
[336] NA NA NA NA NA
[341] NA NA NA NA NA
[346] NA NA NA NA NA
[351] NA NA NA NA NA
[356] NA NA NA NA NA
[361]1.004040e-018.515679e-027.029268e-025.715599e-025.110153e-02
[366]4.991736e-025.581525e-026.241661e-026.269524e-025.877482e-02
[371]5.253223e-024.562624e-023.952282e-023.829537e-023.443280e-02
[376]2.407467e-021.769808e-021.761810e-022.032520e-021.993991e-02
[381]1.821051e-022.084876e-022.179151e-021.568026e-028.890338e-03
[386]7.056170e-032.657382e-03 -9.563535e-03 -1.897531e-02 -2.312664e-02
[391] -2.957330e-02 -3.110409e-02 -2.690143e-02 -2.457607e-02 -2.252095e-02
[396] -1.653800e-02 -4.305910e-033.726853e-036.659425e-037.862300e-03
[401]6.147606e-031.018774e-021.931391e-022.460170e-022.927498e-02
[406]3.201626e-023.166119e-023.551405e-023.891915e-023.776186e-02
[411]3.673906e-024.277958e-024.811809e-025.283620e-025.283932e-02
[416]4.173097e-023.330246e-022.446458e-021.804268e-022.208932e-02
[421]1.733235e-022.017096e-03 -4.573855e-03 -4.843286e-03 -7.859183e-03
[426] -1.330237e-02 -1.255742e-02 -1.051015e-02 -1.425636e-02 -2.034499e-02
[431] -2.572603e-02 -2.770393e-02 -2.806309e-02 -2.838050e-02 -3.004992e-02
[436] -3.291421e-02 -3.405674e-02 -2.951094e-02 -2.271565e-02 -1.671007e-02
[441] -1.140243e-02 -5.322725e-035.042986e-056.324783e-04 -2.420048e-04
[446] -2.403749e-03 -2.925378e-033.558059e-037.899136e-034.791272e-03
[451]4.822365e-036.238733e-035.460544e-04 -4.485052e-032.179642e-03
[456]1.362536e-021.679647e-021.265460e-028.994082e-031.409230e-02
[461]2.137581e-021.947954e-021.641475e-021.370614e-021.131230e-02
[466]1.197445e-028.392970e-031.061049e-031.367594e-04 -6.801138e-04
[471] -5.568721e-03 -9.889200e-03 -1.092980e-02 -1.184946e-02 -1.682892e-02
[476] -1.845191e-02 -1.433073e-02 -1.207738e-02 -1.564146e-02 -2.018023e-02
[481] -2.419152e-02 -2.634776e-02 -2.547563e-02 -1.914930e-02 -1.078041e-02
[486] -4.772991e-035.362762e-041.061862e-03 -4.029188e-03 -1.130636e-02
[491] -1.634893e-02 -1.386104e-02 -1.166227e-02 -9.719036e-033.317008e-04
[496]7.825506e-035.595319e-04 -5.862029e-03 -1.815089e-034.539316e-03
[501]8.766357e-031.111326e-021.596520e-021.886439e-021.864887e-02
[506]1.845839e-022.245672e-022.876816e-022.879057e-022.325481e-02
[511]1.697351e-028.644400e-03 -2.883408e-03 -6.127071e-037.284491e-04
[516]5.398368e-032.581130e-03 -1.297593e-03 -5.588842e-049.397542e-05
[521] -7.179257e-04 -1.435472e-03 -2.069629e-03 -2.630087e-031.041254e-03
[526]2.897043e-03 -2.407282e-03 -8.484056e-03 -1.246573e-02 -1.459579e-02
[531] -1.231163e-02 -6.126266e-03 -2.048617e-031.662603e-042.123736e-03
[536] -3.129416e-04 -3.855331e-03 -5.597153e-03 -7.136551e-03 -9.885937e-03
[541] -2.223427e+003.694470e-02 -2.969539e+003.747643e-011.331799e+00
[546]3.179001e+005.812920e+003.139351e+007.792666e-01 -3.023744e-01
[551] -1.263868e+00 -1.119178e+00 -9.899142e-012.122938e+00 -3.128746e+00
[556] -2.770107e+00 -4.489812e-011.603785e+001.416601e+00 -7.502190e-01
[561]3.347776e-012.292293e+00 -9.749063e-01 -2.861020e+00 -1.532106e+00
[566]6.423682e-01 -3.434474e+00 -5.038917e+00 -1.454122e+00 -1.280377e+00
[571] -3.129601e+002.229136e+009.623327e-018.427501e-017.342870e-01
[576]3.637040e+005.209395e+006.045748e-011.533513e+00 -6.468933e-01
[581] -5.752936e-013.487985e+003.079051e+007.190306e-012.630501e+00
[586] -6.829471e-013.928426e-012.349165e+007.952353e-02 -9.291304e-01
[591]1.794361e-014.157782e+00 -3.289920e-013.712607e+00 -3.712709e+00
[596] -4.279261e+00 -1.782749e+00 -4.580535e+00 -5.317714e-022.953591e+00
[601] -6.390461e+00 -4.649985e+00 -1.076121e-01 -9.035143e-02 -2.072319e+00
[606] -1.823953e+002.392772e+00 -8.874931e-01 -1.780988e+00 -2.566478e+00
[611] -1.267628e+00 -1.197232e-01 -1.066106e-01 -9.502189e-02 -1.086169e+00
[616] -9.635188e-011.462663e-013.128467e+001.768259e+002.561960e+00
[621]1.262033e+003.120121e+007.608828e-01 -3.325106e-01 -2.988356e-01
[626] -1.260741e+008.877525e-013.776837e+00 -6.795543e-01 -1.612492e+00
[631]1.578269e+00 -5.976169e-01 -3.522022e+00 -1.107342e-014.898556e+00
[636]3.324304e+00 -1.068385e+00 -1.949191e+00 -7.276339e-014.346405e+00
[641]8.293766e-01 -2.276143e+00 -1.936762e-02 -2.026251e+002.070391e-01
reached getOption("max.print") -- omitted 827 entries ]
前三百六十个数据为什么会为为空，求解答