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Scan-Statistics-Project-4Y-INSA
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Update Dataset_study.rmd 

Ajout_Code_Troncage
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elisaduz 2022-03-19 11:56:36 +01:00
parent fb7958adae
commit fd3ab9ac2e
1 changed files with 76 additions and 1 deletions
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Dataset_study.rmd
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@ -279,7 +279,7 @@ library(stringr)
E=10
lambda0=1
lambda1=2
max=0
while (exp(-lambda0*max) > 10^(-9)){
max = max + 1
@ -292,6 +292,11 @@ t=seq(0,max,0.1)
x=floor(E*log(lambda1/lambda0)+(lambda0-lambda1)*t)
head(x)
range(x)
s=seq(-15,6,0.1)
##tronquer la queue des x (x négatifs)
A=1/(lambda0-lambda1)
@ -328,6 +333,76 @@ p
```
```{r}
library(stringr)
E=10
lambda0=1
lambda1=2
max=0
while (exp(-lambda0*max) > 10^(-9)){
max = max + 1
}
max
# en fonction de lambda0 tq P(Expo(lambda
#0)>=max)<10^-9
t=seq(0,max,0.1)
probaseuilmin = 10^-9
x=floor(E*log(lambda1/lambda0)+(lambda0-lambda1)*t)
head(x)
range(x)
s=seq(-15,6,0.1)
##tronquer la queue des x (x négatifs)
A=1/(lambda0-lambda1)
B=A*log(lambda1/lambda0)
proba.s=lambda0*exp(-lambda0*(A*s-B))
proba.s = proba.s/sum(proba.s)
barplot(proba.s)
# Troncage à un score minimal
minXk = as.numeric(x[max(which(proba.s<(probaseuilmin)))]) # On définit la classe pour proba < probaseuilmin
names(proba.s) = as.character(x)
proba.s[as.character(minXk)] = sum(proba.s[which(proba.s<probaseuilmin)]) # probabilité de la classe SCORE < minXk
proba.s = proba.s[which(x>=minXk)] # On ne garde que les scores supérieurs à minXk
subtitle = paste("lambda0=",lambda0,";lambda1=",lambda1,";E=",E,sep="")
barplot(proba.s, col="steelblue",xlab="Score",ylab="Probabilité", main = paste("Probabilité d'apparition de chaque score\nLoi géométrique : ",subtitle,sep=""))
barplot(proba.s)
##trouver 1/lambda en fonction intervalle seq
## ecart ou rapport entre les lambda qui est le + important ?
for (lambda0 in c(5,50,500,5000,50000) ) {
for (lambda1 in c(2,20,200,2000,20000) ) {
probaS_vect=vector(length=length(s))
for (j in 1:length(x))
{
A=1/(lambda0-lambda1)
B=A*log(lambda1/lambda0)
probaS=floor(E*lambda0*exp(-lambda0*(A*x[j]-B)))
# print(s)
probaS_vect[j]=probaS
}
probaS_vect = probaS_vect/sum(probaS_vect)
print(probaS_vect)
p <- barplot(probaS_vect, main=str_c("lambda0=", as.character(lambda0), "et", "lambda1=", as.character(lambda1), sep=" " ))
p
}
}
```
Import data of rainfall in France every 3 hours.