library(Hmisc) # First read in the temperature data, and assign column names. temperatureDF <- read.table("data/temp.dat", col.names = c("Temp", "Time")) temperature <- temperatureDF$Temp time <- temperatureDF$Time # We now want to regress our data against sinusoids with a period of 72. # First create the sinusoids. cosine <- cos(2 * pi * time/72) sine <- sin(2 * pi * time/72) # Then fit a linear model. lm.temperature <- lm(temperature ~ cosine + sine) temperatureResiduals <- lm.temperature$residuals x<-matrix(0, nrow = 350, ncol = 2) y<-temperatureResiduals[3:352] for(i in 1:2){ x[,i]<-Lag(temperatureResiduals, i)[3:352] } ar.reg<-lm(y~x-1) summary(ar.reg) par(oma = rep(2, 4)) par(mar = c(5, 5, 1, 1)) par(mfrow=c(2,1)) plot(temperature, type="l", xaxt = "n", yaxt = "n", xlab = "Time (Hours)", ylab = expression(paste("Temperature (",degree,"C)")), main = "", lwd = 3, cex.lab = 1.6, col = "darkgrey") axis(1, at = seq(from = 0, to = 288, by = 72), labels = seq(from = 0, to = 96, by = 24), cex.axis = 1.5) axis(2, at = seq(from = 36.5, to = 38.5, by = 0.5), labels = seq(from = 36.5, to = 38.5, by = 0.5), cex.axis = 1.5) plot(temperature, type="l", xaxt = "n", yaxt = "n", xlab = "Time (Hours)", ylab = expression(paste("Temperature (",degree,"C)")), main = "", lwd = 2, cex.lab = 1.6, col = "darkgrey") lines(2:351, lm.temperature$fitted[3:352]+ar.reg$fitted, col = 2, lwd = 3, lty = 5) axis(1, at = seq(from = 0, to = 288, by = 72), labels = seq(from = 0, to = 96, by = 24), cex.axis = 1.5) axis(2, at = seq(from = 36.5, to = 38.5, by = 0.5), labels = seq(from = 36.5, to = 38.5, by = 0.5), cex.axis = 1.5) dev.print(device = postscript, "18.8.eps", horizontal = TRUE)