Reynolds (1994) describes a small part of a study of the long-term temperature dynamics of beaver Castor canadensis in north-central Wisconsin. Body temperature was measured by telemetry every 10 minutes for four females, but data from a one period of less than a day for each of two animals is used there.
The
beav2
data frame has 100 rows and 4 columns.
This data frame contains the following columns:
0330
for 3.30am
P. S. Reynolds (1994) Time-series analyses of beaver body temperatures.
Chapter 11 of
Lange, N., Ryan, L., Billard, L., Brillinger, D., Conquest, L.
and Greenhouse, J. eds (1994)
Case Studies in Biometry.
New York: John Wiley and Sons.
beav2 <- beav2 # make local copy attach(beav2) beav2$hours <- 24*(day-307) + trunc(time/100) + (time%%100)/60 plot(beav2$hours, beav2$temp, type = "l", xlab = "time", ylab = "temperature", main = "Beaver 2") usr <- par("usr"); usr[3:4] <- c(-0.2, 8); par(usr=usr) lines(beav2$hours, beav2$activ, type = "s", lty = 2) attach(beav2) temp <- rts(temp, start = 8+2/3, frequency = 6, units = "hours") activ <- rts(activ, start = 8+2/3, frequency = 6, units = "hours") acf(temp[activ==0]); acf(temp[activ==1]) # also look at PACFs ar(temp[activ==0]); ar(temp[activ==1]) arima.mle(temp, xreg = rep(1, length(temp)), model = list(ar=0.75)) arima.mle(temp, xreg = cbind(1, activ), model = list(ar=0.75)) beav2.gls <- gls(temp ~ activ, data = beav2, corr = corAR1(), method = "ML") summary(beav2.gls) summary(update(beav2.gls, subset = 6:100))