beav2(MASS)
beav2()所属R语言包:MASS
Body Temperature Series of Beaver 2
2海狸体内温度系列
译者:生物统计家园网 机器人LoveR
描述----------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.
雷诺兹(1994年)描述了一个海狸在北部和中部威斯康星州的蓖麻黄花长期的温度变化研究的一小部分。测量体温遥测四女,每隔10分钟,但有用于数据从一个周期不到一天每两个动物。
用法----------Usage----------
beav2
格式----------Format----------
The beav2 data frame has 100 rows and 4 columns. This data frame contains the following columns:
beav2数据框有100行和第4列。这个数据框包含下列资料:
Day of observation (in days since the beginning of 1990), November 3–4.
观察日(自1990年开始在天),11月3-4。
Time of observation, in the form 0330 for 3.30am.
时间的观察,在形式0330为上午03时半。
Measured body temperature in degrees Celsius.
测量体温摄氏度。
Indicator of activity outside the retreat.
活动指示灯以外的撤退。
源----------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.
雷诺兹的PS(1994)的时间序列分析,海狸体温。第11章,朗格,北,瑞安,研究,台球,研究,Brillinger,征服,研究和温室,J. EDS(1994)生物统计学中的案例研究。纽约:John Wiley和Sons。
参考文献----------References----------
Modern Applied Statistics with S. Fourth edition. Springer.
参见----------See Also----------
beav1
beav1
举例----------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$activ, type = "s", lty = 2)
temp <- ts(temp, start = 8+2/3, frequency = 6)
activ <- ts(activ, start = 8+2/3, frequency = 6)
acf(temp[activ == 0]); acf(temp[activ == 1]) # also look at PACFs[也期待在PACFs]
ar(temp[activ == 0]); ar(temp[activ == 1])
arima(temp, order = c(1,0,0), xreg = activ)
dreg <- cbind(sin = sin(2*pi*beav2$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)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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