Update of distribtion via MC
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@ -189,42 +189,40 @@ LS_H0
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## A reformater
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## A reformater
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```{r}
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# distribtion des scores via MC
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# distribtion des scores via MC
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# Nb seq. pp -> Nb seq. tbe -> dist. tbe (vérif) + Nb seq. Scores -> distr scores
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# Nb seq. pp -> Nb seq. tbe -> dist. tbe (vérif) + Nb seq. Scores -> distr scores
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PoissonProcess <- function(lambda,T) {
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A = 1/(lambda0-lambda1)
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return(sort(runif(rpois(1,lambda*T),0,T)))
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B = A*log(lambda1/lambda0)
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}
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lambda0=2
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ppH1 = PoissonProcess(lambda1,T)
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lambda1=3
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n1 = length(ppH1)
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Ti=100000
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tbe1 = ppH1[2:n1]-ppH1[1:n1-1]
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pp1=PoissonProcess(lambda1,Ti)
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print(tbe1)
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print(pp1)
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print(ks.test(tbe1,'exp'))
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n1=length(pp1)
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x = log(lambda1/lambda0)+(lambda0-lambda1)*tbe1 # ne pas mettre le floor ni le E (certes égale à 1)
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tbe1=pp1[2:n1]-pp1[1:n1-1]
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tbe1
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ks.test(tbe1,'exp',lambda)
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x=log(lambda1/lambda0)+(lambda0-lambda1)*tbe1 # ne pas mettre le floor ni le E (certes égale à 1)
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hist(x)
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hist(x)
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summary(x)
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print(summary(x))
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# Calcul du maximum des scores
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# Calcul du maximum des scores
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E=1
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E = 1
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# THEO à faire !!! max.s=log(lambda1/lambda0)
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# THEO à faire !!! max.s = log(lambda1/lambda0)
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maxXk = floor(E*(log(lambda1/lambda0)))
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maxXk = floor(E*(log(lambda1/lambda0)))
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maxXk
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maxXk
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while (maxXk < 3) {
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while (maxXk < 3) {
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E = E+1
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E = E+1
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maxXk = floor(E*(log(lambda1/lambda0)))
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maxXk = floor(E*(log(lambda1/lambda0)))
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}
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}
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E
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print(E)
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x=floor(E*(log(lambda1/lambda0)+(lambda0-lambda1)*tbe1))
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x = floor(E*(log(lambda1/lambda0)+(lambda0-lambda1)*tbe1))
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dist.emp.scores=table(x)/sum(table(x))
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dist.emp.scores = table(x)/sum(table(x))
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dist.emp.scores
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dist.emp.scores
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hist(x)
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hist(x)
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range(x)
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print(range(x))
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x.verif=seq(range(x)[1],range(x)[2],1)
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x.verif = seq(range(x)[1],range(x)[2],1)
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dist.theo.scores=lambda0*exp(-lambda0*(A*x.verif-B))
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dist.theo.scores = lambda0*exp(-lambda0*(A*x.verif-B))
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dist.theo.scores
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print(dist.theo.scores)
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dist.emp.scores
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print(dist.emp.scores)
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```
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