#
# EPage 214 
#
# Written by:
# -- 
# John L. Weatherwax                2009-04-21
# 
# email: wax@alum.mit.edu
# 
# Please send comments and especially bug reports to the
# above email address.
# 
#-----

save_plots = F

library(DAAG)
library(MASS) # get rlm and lqs

# Fit the models suggested in the book in section 6.1 (without an intercept but comparing regression methods): 
allbacks.lm0 = lm( weight ~ -1 + volume + area, data=allbacks )

if( save_plots ){ postscript("../../WriteUp/Graphics/Chapter6/prob_5_res_vs_fitted.eps", onefile=FALSE, horizontal=FALSE) }

oldpar = par(mfrow=c(1,3))
plot( allbacks.lm0$fitted.values, allbacks.lm0$residuals, main="lm", ylim=c(-200,+250) )

allbacks.rlm = rlm( weight ~ -1 + volume + area, data=allbacks )
plot( allbacks.rlm$fitted.values, allbacks.rlm$residuals, main="rlm", ylim=c(-200,+250) )

allbacks.lqs = lqs( weight ~ -1 + volume + area, data=allbacks )
plot( allbacks.lqs$fitted.values, allbacks.lqs$residuals, main="lqs", ylim=c(-200,+250) )
par(oldpar)

if( save_plots ){ dev.off() }

# Lets look at what the coefficients look like under each of these models:
# 
coefficients(allbacks.lm0)
coefficients(allbacks.rlm)
coefficients(allbacks.lqs)

coefficients( lm( weight ~ -1 + volume + area, data=allbacks[-c(11,13),] ) )
coefficients( rlm( weight ~ -1 + volume + area, data=allbacks[-c(11,13),] ) )
coefficients( lqs( weight ~ -1 + volume + area, data=allbacks[-c(11,13),] ) )