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27 lines
642 B
Plaintext
27 lines
642 B
Plaintext
#-*- mode: Fundamental; -*-
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#read in data
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xm<-matrix(scan("freqhist",0),ncol=2,byrow=T)
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xr<-xm[,1]
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xnr<-xm[,2]
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xn<-sum(xr*xnr)
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# make averaging transform
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xnrz<-nrzest(xr, xnr)
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# get Linear Good-Turing estimate
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xf<-lsfit(log(xr), log(xnrz))
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xcoef<-xf$coef
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xrst<-rstest(xr,xcoef)
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xrstrel<-xrst/xr
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# get Turing estimate
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xrtry<-xr == c(xr[-1] - 1, 0)
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xrstarel<-rep(0, length(xr))
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xrstarel[xrtry]<-(xr[xrtry] + 1) / xr[xrtry] * c(xnr[-1], 0) [xrtry] / xnr[xrtry]
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# make switch from Turing to LGT estimates
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tursd<-rep(1, length(xr))
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for (i in 1:length(xr)) if (xrtry[i])
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tursd[i]<-(i+1) / xnr[i] * sqrt(xnr[i+1] * (1 + xnr[i+1] / xnr[i]))
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