beav2                  package:MASS                  R Documentation

Body Temperature Series of Beaver 2

Description:

     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.

Usage:

     data(beav2)

Format:

     The 'beav2' data frame has 100 rows and 4 columns. This data frame
     contains the following columns:

     'day' Day of observation (in days since the beginning of 1990),
          November 3-4.

     'time' Time of observation, in the form '0330' for 3.30am

     'temp' Measured body temperature in degrees Celcius

     'activ' Indicator of activity outside the retreat

Source:

     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.

References:

     Venables, W. N. and Ripley, B. D. (2002) _Modern Applied
     Statistics with S._ Fourth edition.  Springer.

See Also:

     'beav1'

Examples:

     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)

     temp <- ts(temp, start = 8+2/3, frequency = 6)
     activ <- ts(activ, start = 8+2/3, frequency = 6)
     acf(temp[activ == 0]); acf(temp[activ == 1]) # also look at PACFs
     ar(temp[activ == 0]); ar(temp[activ == 1])

     arima(temp, order = c(1,0,0), xreg = activ)
     dreg <- cbind(sin = sin(2*pi*beav2$hours/24), cos = cos(2*pi*beav2$hours/24))
     arima(temp, order = c(1,0,0), xreg = cbind(active=activ, dreg))

     library(nlme)
     beav2.gls <- gls(temp ~ activ, data = beav2, corr = corAR1(0.8),
                      method = "ML")
     summary(beav2.gls)
     summary(update(beav2.gls, subset = 6:100))
     detach("beav2"); rm(temp, activ)

