On this R-data statistics page, you will find information about the beav1 data set which pertains to Body Temperature Series of Beaver 1. The beav1 data set is found in the MASS R package. You can load the beav1 data set in R by issuing the following command at the console data("beav1"). This will load the data into a variable called beav1. If R says the beav1 data set is not found, you can try installing the package by issuing this command install.packages("MASS") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the beav1 R data set. The size of this file is about 1,909 bytes.

Body Temperature Series of Beaver 1

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

beav1

Format

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.

Note

The observation at 22:20 is missing.

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

beav2

Examples

beav1 <- within(beav1,
               hours <- 24*(day-346) + 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)

--

Dataset imported from https://www.r-project.org.