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Scan-Statistics-Project-4Y-INSA
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Update of distribtion via MC

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Paul-Corbalan 2022-04-03 18:31:36 +02:00
parent 425077cf27
commit fb66d1307a
1 changed files with 22 additions and 24 deletions
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46
Comparaison_of_methods.rmd
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@ -189,42 +189,40 @@ LS_H0
```
## A reformater
```{r}
# distribtion des scores via MC
# Nb seq. pp -> Nb seq. tbe -> dist. tbe (vérif) + Nb seq. Scores -> distr scores
PoissonProcess <- function(lambda,T) {
return(sort(runif(rpois(1,lambda*T),0,T)))
}
lambda0=2
lambda1=3
Ti=100000
pp1=PoissonProcess(lambda1,Ti)
print(pp1)
n1=length(pp1)
tbe1=pp1[2:n1]-pp1[1:n1-1]
tbe1
ks.test(tbe1,'exp',lambda)
x=log(lambda1/lambda0)+(lambda0-lambda1)*tbe1 # ne pas mettre le floor ni le E (certes égale à 1)
A = 1/(lambda0-lambda1)
B = A*log(lambda1/lambda0)
ppH1 = PoissonProcess(lambda1,T)
n1 = length(ppH1)
tbe1 = ppH1[2:n1]-ppH1[1:n1-1]
print(tbe1)
print(ks.test(tbe1,'exp'))
x = log(lambda1/lambda0)+(lambda0-lambda1)*tbe1 # ne pas mettre le floor ni le E (certes égale à 1)
hist(x)
summary(x)
print(summary(x))
# Calcul du maximum des scores
E=1
# THEO à faire !!! max.s=log(lambda1/lambda0)
E = 1
# THEO à faire !!! max.s = log(lambda1/lambda0)
maxXk = floor(E*(log(lambda1/lambda0)))
maxXk
while (maxXk < 3) {
E = E+1
maxXk = floor(E*(log(lambda1/lambda0)))
}
E
print(E)
x=floor(E*(log(lambda1/lambda0)+(lambda0-lambda1)*tbe1))
dist.emp.scores=table(x)/sum(table(x))
x = floor(E*(log(lambda1/lambda0)+(lambda0-lambda1)*tbe1))
dist.emp.scores = table(x)/sum(table(x))
dist.emp.scores
hist(x)
range(x)
x.verif=seq(range(x)[1],range(x)[2],1)
dist.theo.scores=lambda0*exp(-lambda0*(A*x.verif-B))
dist.theo.scores
dist.emp.scores
print(range(x))
x.verif = seq(range(x)[1],range(x)[2],1)
dist.theo.scores = lambda0*exp(-lambda0*(A*x.verif-B))
print(dist.theo.scores)
print(dist.emp.scores)
```