

   BBooddyy TTeemmppeerraattuurree SSeerriieess ooff BBeeaavveerr 11

   AArrgguummeennttss::

        day: Day of observation (in days since the beginning of
             1990), December 12-13.

       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

   SSUUMMMMAARRYY::

        The `beaver1' data frame has 114 rows and 4 columns on
        body temperature measurements at 10 minute intervals.

   DDAATTAA DDEESSCCRRIIPPTTIIOONN::

        Reynolds (1994) describes a small part of a study of
        the long-term temperature dynamics of beaver Castor
        canadensis in north-central Wisconsin.  Body tempera-
        ture 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.

        This data frame contains the following columns:

   NNOOTTEE::

        The observation at 22:20 is missing.

   SSOOUURRCCEE::

        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 Green-
        house, J. eds (1994) Case Studies in Biometry.  New
        York: John Wiley and Sons.

   SSeeee AAllssoo::

        `beaver2'

   EExxaammpplleess::

        ### Not usable in R
        attach(beav1)
        beav1$hours <- 24*(day-346) + trunc(time/100) + (time%%100)/60
        detach()
        plot(beav1$hours, beav1$temp, type="l", xlab="time",
           ylab="temperature", main="Beaver 1")
        usr <- par("usr"); usr[3:4] <- c(-0.2, 8); par(usr=usr)
        lines(beav1$hours, beav1$activ, type="s", lty=2)
        temp <- rts(c(temp[1:82], NA, temp[83:114]), start=9.5,
                    frequency=6, units="hours")
        activ <- rts(c(activ[1:82], NA, activ[83:114]), start=9.5,
                     frequency=6, units="hours")

        acf(temp[1:53]) # and also type="partial"
        ar(temp[1:53])
        act <- c(rep(0, 10), activ)
        X <- cbind(1, act=act[11:125], act1 = act[10:124],
                  act2 = act[9:123], act3 = act[8:122])
        arima.mle(temp, xreg=X, model=list(ar=0.82))

