hills {DAAG} | R Documentation |
The record times in 1984 for 35 Scottish hill races.
hills
This data frame contains the following columns:
A.C. Atkinson (1986) Comment: Aspects of diagnostic regression analysis. Statistical Science 1, 397-402.
Also, in MASS library, with time in minutes.
A.C. Atkinson (1988) Transformations unmasked. Technometrics 30, 311-318. [ "corrects" the time for Knock Hill from 78.65 to 18.65. It is unclear if this based on the original records.]
print("Transformation - Example 6.4.3") pairs(hills, labels=c("dist\n\n(miles)", "climb\n\n(feet)", "time\n\n(hours)")) pause() pairs(log(hills), labels=c("dist\n\n(log(miles))", "climb\n\n(log(feet))", "time\n\n(log(hours))")) pause() hills0.loglm <- lm(log(time) ~ log(dist) + log(climb), data = hills) oldpar <- par(mfrow=c(2,2)) plot(hills0.loglm) pause() hills.loglm <- lm(log(time) ~ log(dist) + log(climb), data = hills[-18,]) summary(hills.loglm) plot(hills.loglm) pause() hills2.loglm <- lm(log(time) ~ log(dist)+log(climb)+log(dist):log(climb), data=hills[-18,]) anova(hills.loglm, hills2.loglm) pause() step(hills2.loglm) pause() summary(hills.loglm, corr=TRUE)$coef pause() summary(hills2.loglm, corr=TRUE)$coef par(oldpar) pause() print("Nonlinear - Example 6.9.4") hills.nls0 <- nls(time ~ (dist^alpha)*(climb^beta), start = c(alpha = .909, beta = .260), data = hills[-18,]) summary(hills.nls0) plot(residuals(hills.nls0) ~ predict(hills.nls0)) # residual plot pause() hills$climb.mi <- hills$climb/5280 hills.nls <- nls(time ~ alpha + beta*dist + gamma*(climb.mi^delta), start=c(alpha = 1, beta = 1, gamma = 1, delta = 1), data=hills[-18,]) summary(hills.nls) plot(residuals(hills.nls) ~ predict(hills.nls)) # residual plot