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do_ln
2011 Jan 07
0
Fitting an Inverse Gamma Distribution to Survey Data
...8,6.493770,4.611944,6.103279,5.899687,2.946711,6.338660,5.237273,
3.413553,3.226667,4.193143,6.192375,9.437436,1.863548,3.185567,)
#plot it
hist(iniSal_US_forHist,breaks=seq(1.1,21,by=0.625),col="grey",freq=F,xlim=c(0,21))
#fit it
edm_gm<-fitdistr(iniSal_US_forHist,"gamma")
edm_ln<-fitdistr(iniSal_US_forHist,"log-normal")
#see how the fits look
curve(dgamma(x,scale=edm_gm$estimate["rate"],shape=edm_gm$estimate["shape"]),from=0,to=20,add=T,col="red",lwd=2)
curve(dgamma(x,scale=1/edm_gm$estimate["rate"],shape=edm_gm$estimat...