时间序列分析之季节模型的R脚本

Posted 2021-05-02 正经思考笔记

library(tseries)

x=read.table("F:/data/file1.csv",sep=",",header=T)

x

m=ts(x$ZZL,start=1)

plot(m)

m.dif<-diff(m)

plot(m.dif)

m.dif1_6<-diff(diff(m),6)

plot(m.dif1_6)

acf(m.dif1_12)

pacf(m.dif1_12)

m.fit<-arima(m.dif1_12,seasonal = list(order=c(0,1,0),period=12,transform.par=T,fixed = c(NA,0,0,NA)))

m.fit

adf.test(m)

for(i in 1:2)print(Box.test(m.dif1_12,type="Ljung-Box",lag=6*i))

acf(m)

pacf(m)

library(zoo)

library(forecast)

auto.arima(m)

m.fit=arima(m,order=c(1,0,0),method="CSS")

m.fit

t1=0.5529/0.0439

pt(t1,df=365,lower.tail=F)

for(i in 1:2) print(Box.test(m.fit$residual,lag=6*i))

m.fore<-forecast(m.fit,h=5)

m.fore

L1<-m.fore$fitted-1.96*sqrt(m.fit$sigma2)

U1<-m.fore$fitted+1.96*sqrt(m.fit$sigma2)

L2<-ts(m.fore$lower[,2],start= 1)

U2<-ts(m.fore$upper[,2],start = 1)

c1<-min(m,L1,L2)

c2<-max(m,L2,U2)

plot(m,type = "p",pch=8,xlim = c(1,366),ylim = c(c1,c2))

lines(m.fore$fitted,col=2,lwd=2)

lines(m.fore$mean,col=2,lwd=2)

lines(L1,col=4,lty=2)

lines(L2,col=4,lty=2)

lines(U1,col=4,lty=2)

lines(U2,col=4,lty=2)

封面是著名网黄猫日喔