Description Usage Format Note Source References See Also Examples
Reynolds (1994) describes a small part of a study of the longterm temperature dynamics of beaver Castor canadensis in northcentral 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.
1 
The beav1
data frame has 114 rows and 4 columns.
This data frame contains the following columns:
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 Celsius.
activ
Indicator of activity outside the retreat.
The observation at 22:20 is missing.
P. S. Reynolds (1994) Timeseries 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.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23  beav1 < within(beav1,
hours < 24*(day346) + trunc(time/100) + (time%%100)/60)
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 < ts(c(beav1$temp[1:82], NA, beav1$temp[83:114]),
start = 9.5, frequency = 6)
activ < ts(c(beav1$activ[1:82], NA, beav1$activ[83:114]),
start = 9.5, frequency = 6)
acf(temp[1:53])
acf(temp[1:53], 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])
alpha < 0.80
stemp < as.vector(temp  alpha*lag(temp, 1))
sX < X[1, ]  alpha * X[115,]
beav1.ls < lm(stemp ~ 1 + sX, na.action = na.omit)
summary(beav1.ls, cor = FALSE)
rm(temp, activ)

Call:
ar(x = temp[1:53])
Coefficients:
1
0.8222
Order selected 1 sigma^2 estimated as 0.01011
Call:
lm(formula = stemp ~ 1 + sX, na.action = na.omit)
Residuals:
Min 1Q Median 3Q Max
0.21317 0.04317 0.00683 0.05483 0.37683
Coefficients:
Estimate Std. Error t value Pr(>t)
sX 36.85587 0.03922 939.833 < 2e16 ***
sXact 0.25400 0.03930 6.464 3.37e09 ***
sXact1 0.17096 0.05100 3.352 0.00112 **
sXact2 0.16202 0.05147 3.148 0.00215 **
sXact3 0.10548 0.04310 2.448 0.01605 *

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.08096 on 104 degrees of freedom
(5 observations deleted due to missingness)
Multiple Rsquared: 0.9999, Adjusted Rsquared: 0.9999
Fstatistic: 1.81e+05 on 5 and 104 DF, pvalue: < 2.2e16
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