Update Dataset_study.rmd
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@ -277,10 +277,32 @@ SL_vect
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library(stringr)
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library(stringr)
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E=10
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E=10
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x=c(0.00,0.05,0.1,0.15,0.20)
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lambda0=1
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lambda1=2
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lambda1=2
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while (exp(-lambda0*max) > 10^(-9)){
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max = max + 1
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}
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max
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# en fonction de lambda0 tq P(Expo(lambda
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#0)>=max)<10^-9
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t=seq(0,max,0.1)
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x=floor(E*log(lambda1/lambda0)+(lambda0-lambda1)*t)
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head(x)
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range(x)
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s=seq(-15,6,0.1)
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##tronquer la queue des x (x négatifs)
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A=1/(lambda0-lambda1)
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B=A*log(lambda1/lambda0)
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proba.s=lambda0*exp(-lambda0*(A*s-B))
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proba.s
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barplot(proba.s)
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##trouver 1/lambda en fonction intervalle seq
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## ecart ou rapport entre les lambda qui est le + important ?
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for (lambda0 in c(5,50,500,5000,50000) ) {
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for (lambda0 in c(5,50,500,5000,50000) ) {
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for (lambda1 in c(2,20,200,2000,20000) ) {
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for (lambda1 in c(2,20,200,2000,20000) ) {
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S_vect=vector(length=length(x))
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S_vect=vector(length=length(x))
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@ -296,6 +318,7 @@ for (lambda0 in c(5,50,500,5000,50000) ) {
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print(S)
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print(S)
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S_vect[j]=S
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S_vect[j]=S
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}
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}
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print(S_vect)
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print(S_vect)
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p <- barplot(S_vect, main=str_c("lambda0=", as.character(lambda0), "et", "lambda1=", as.character(lambda1), sep=" " ))
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p <- barplot(S_vect, main=str_c("lambda0=", as.character(lambda0), "et", "lambda1=", as.character(lambda1), sep=" " ))
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p
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p
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