# Prvni priklad - ANOVA 
# nacteni dat
rm(list=ls())
load("cviceni8.RData")
brambory <- data8$pr1

skup<-factor(rep(c("A","B","C","D"),times=c(4,3,5,3)))
attach(brambory)
y <- c(A,B,C,D)
model <- lm(y~skup)
anova(model)
# Scheffeho test
install.packages("agricolae")
library(agricolae)
(scheffe.test(model,"skup"))

# pripadne Kruskal - Wallisuv test
(kruskal(y,skup))

# posouzeni homogenity rozptylu
x11(12,9)
plot(skup,y,xlab="odrudy",ylab="hmotnost")  # graficky
library(car)
leveneTest(y~skup)        # levenuv test
bartlett.test(y~skup) # bartlettuv test

# posouzeni normality
# KS test
ks.test((A-mean(A))/sd(A),"pnorm")
ks.test((B-mean(B))/sd(B),"pnorm")
ks.test((C-mean(C))/sd(C),"pnorm")
ks.test((D-mean(D))/sd(D),"pnorm")

# Shapiro-Wilk
shapiro.test(A)
shapiro.test(B)
shapiro.test(C)
shapiro.test(D)

detach(brambory)

# Druhy priklad
# nacteni dat
rm(list=ls())
load("cviceni8.RData")
nj <- data8$pr2$nj
pj <- data8$pr2$pj

source("anovabinom.R")
(anovabinom(nj,pj))

# Treti priklad
# nacteni dat
rm(list=ls())
load("cviceni8.RData")
x <- data8$pr3$x
y <- data8$pr3$y
mod3 <- lm(y~1+x+I(x^2)+I(x^3))
mod2 <- lm(y~1+x+I(x^2))
mod1 <- lm(y~1+x)
anova(mod3,mod2)
anova(mod2,mod1)
x11(width=8,height=5)
plot(x,y)
curve(predict(mod3,data.frame(x=x)),add=T,col="red")
curve(predict(mod2,data.frame(x=x)),add=T,col="green")
curve(predict(mod1,data.frame(x=x)),add=T,col="cyan")
legend("bottomright",legend=c("M3","M2","M1"),col=c("red","green","cyan"),lty=c(1,1,1))
#----------------------------------------------------------------------------------------