# Zur Erinnerung
# (Daten von Mareike PlŸschke)
mp = read.table(file.path(pfad, "mp.txt"))
mp.lm = lm(durv1 ~ peak, data = mp)
abline(mp.lm)
# Werte vorhersagen
predict(mp.lm)
new = data.frame(peak = 2)
predict(mp.lm, new)
with(mp, plot(peak, durv1, ylim = c(-50, 250), xlim=c(0, 2)))
abline(mp.lm)
points(2, predict(mp.lm, new))
summary(mp.lm)

# Es gab eine signifikante lineare Beziehung zwischen
# durv1 und peak (R^2 = 0.46,  p < 0.001)




library(MASS)


ydata = read.table(file.path(pfad, "ydata.txt"))
names(ydata)

pairs(ydata)

regm = lm(F2 ~ DORSX+DORSY+LIPX+LIPY, data = ydata)
coef(regm)
summary(regm)

n = with(ydata, length(F2))
1-(1-0.3939) * (  (n-1)/(n-4-1) )

library(MASS)
stepAIC(regm)


summary(regm)
lip.lm = lm(F2 ~ LIPX + LIPY, data = ydata)
summary(lip.lm)


epg = read.table(paste(pfad, "epg.txt", sep="/"))
with(epg, plot(COG, F2))
regp = lm(F2 ~ COG + I(COG^2), data = epg)
k = coef(regp)
with(epg, plot(COG, F2))
curve(k[1] + k[2]*x + k[3]*x^2, add=T)
summary(regp)
stepAIC(regp)

#############################################


regp = lm(F2 ~ COG + I(COG^2), data = epg)
shapiro.test(resid(regp))
plot(resid(regp))
abline(h=0, lty=2)
acf(resid(regp))
plot(regp, 4)
with(epg, plot(COG, F2, cex = 10*sqrt(cooks.distance(regp))))
with(epg, text(COG, F2, as.character(1:length(F2))))