library(ALSM)
library(MASS)
library(onewaytests)
library(dplyr)
library(alr3)
dat<-read.csv("Pokemon.csv")
dat<-select(dat,-c("X.","Generation","Legendary"))
dat <- dat[dat$Name=="Pikachu" | dat$Name=="Bulbasaur" | dat$Name=="Charizard" | dat$Name=="Squirtle" | dat$Name=="Kingler"
           | dat$Name=="Muk" | dat$Name=="Tauros" | dat$Name=="Snorlax" | dat$Name=="Heracross" | dat$Name=="Bayleef" | dat$Name=="Quilava"
           | dat$Name=="Totodile" | dat$Name=="Noctowl" | dat$Name=="Donphan" | dat$Name=="Swellow" | dat$Name=="Sceptile"
           | dat$Name=="Corphish" | dat$Name=="Torkoal" | dat$Name=="Glalie" | dat$Name=="Staraptor" | dat$Name=="Torterra" | dat$Name=="Infernape"
           | dat$Name=="Buizel" | dat$Name=="Gliscor" | dat$Name=="Gible" | dat$Name=="Unfezzant" | dat$Name=="Oshawatt" | dat$Name=="Pignite"
           | dat$Name=="Snivy" | dat$Name=="Scraggy" | dat$Name=="Leavanny" | dat$Name=="Palpitoad" | dat$Name=="Boldore" | dat$Name=="Krookodile"
           | dat$Name=="Greninja" | dat$Name=="Taloneflame" | dat$Name=="Hawlucha" | dat$Name=="Goodra" | dat$Name=="Noivern",]
winrates <- c(0.70,0.86,0.58,0.63,0.50,0.71,0.43,0.73,0.60,0.56,0.40,0.50,0.43,0.43,0.48,0.58,0.33,0.56,0.63,0.33,0.73,0.40,0.43,0.50,0.30,0.44,0.50,0.40,0.57,
          0.57,0.80,0.55,0.78,0.50,0.60,0.43)
dat$WR <- winrates

###############DIAGNOSTICS############################
r.model<-lm(WR~Total+HP+Atk+Def+SpAtk+SpDef+Speed,dat)

#lack of fit test
pureErrorAnova(r.model)

Analysis of Variance Table

Response: WR
          Df  Sum Sq  Mean Sq F value   Pr(>F)
Total      1 0.01167 0.011671  0.7137 0.405127
HP         1 0.00120 0.001205  0.0737 0.788003
Atk        1 0.00796 0.007965  0.4871 0.490797
Def        1 0.12539 0.125388  7.6677 0.009698 **
SpAtk      1 0.04653 0.046534  2.8457 0.102350
SpDef      1 0.00329 0.003288  0.2010 0.657210
Residuals 29 0.47423 0.016353
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

r.model<-lm(WR~Total+HP+Atk+Def+SpAtk+SpDef+Speed,dat)
f.model<-lm(WR~factor(Total)*factor(HP)*factor(Atk)*factor(Def)*factor(SpAtk)*factor(SpDef)*factor(Speed),dat)
anova(r.model,f.model)