Question

R code to obtain the goodness of fit G^2, its p-value, and its AIC value given a dataset?

Answer 1

1. In case of discrete data (for example Goodness-of-fit test for poisson distribution) :

library(vcd)

gf<-goodfit(x.poi,type= "poisson",method= "MinChisq")

summary(gf)

plot(gf,main="Count data vs Poisson distribution")

2. In case of continuous data (for example Goodness-of-fit test for gamma distribution) :

x.gam.cut<-cut(x.gam,breaks=c(0,3,6,9,12,18))

table(x.gam.cut)

## computing expected frequencies

(pgamma(3,shape=a.est,rate=l.est)-pgamma(0,shape=a.est,rate=l.est))*200

(pgamma(6,shape=a.est,rate=l.est)-pgamma(3,shape=a.est,rate=l.est))*200

(pgamma(9,shape=a.est,rate=l.est)-pgamma(6,shape=a.est,rate=l.est))*200

(pgamma(12,shape=a.est,rate=l.est)-pgamma(9,shape=a.est,rate=l.est))*200

(pgamma(18,shape=a.est,rate=l.est)-pgamma(12,shape=a.est,rate=l.est))*200

f.ex<-c(20,71,61,31,17) ## expected frequencies vector

f.os<-vector()

for(i in 1:5) f.os[i]<- table(x.gam.cut)[[i]]   ## empirical frequencies

X2<-sum(((f.os-f.ex)^2)/f.ex)   ## chi-square statistic

gdl<-5-2-1   ## degrees of freedom

1-pchisq(X2,gdl)   ## p-value