# NOT RUN {
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
# }
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