Change ScoreDistribElisa to ScoreDistribTheo
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@ -290,7 +290,7 @@ barplot(distrib_mc[,2])
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```
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```{r}
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ScoreDistribElisa <- function(lambda0, lambda1, T){
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ScoreDistribTheo <- function(lambda0, lambda1, T){
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E = ComputeE(lambda0, lambda1)
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score_max = floor(E*log(lambda1/lambda0))
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@ -312,7 +312,7 @@ ScoreDistribElisa <- function(lambda0, lambda1, T){
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```{r}
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distrib_score_mc = ScoreDistribEmpiric(2,3,10000,T)
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distrib_score_theo = ScoreDistribElisa(2,3,T)
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distrib_score_theo = ScoreDistribTheo(2,3,T)
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plot_graph_distrib_score <- function(distrib_score_theo, distrib_score_mc){
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# length(distrib_score_mc[,2])
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@ -419,7 +419,7 @@ for (lambda0 in (2)){
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#print(confusionMatrix(factor(LS_H0$class), factor(SS_H0$class)))
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#cat("- Elisa version:\n")
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Score = ScoreDistribElisa(lambda0, lambda1, T)
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Score = ScoreDistribTheo(lambda0, lambda1, T)
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Emp = EmpDistrib(lambda0,n_sample,T,tau)
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X_seq = Score$Score_X
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@ -506,7 +506,7 @@ for (i in (1:NbSeq)) {
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#print(confusionMatrix(factor(LS_H0$class), factor(SS_H0$class)))
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#cat("- Elisa version:\n")
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Score = ScoreDistribElisa(lambda0, lambda1, T)
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Score = ScoreDistribTheo(lambda0, lambda1, T)
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Emp = EmpDistrib(lambda0,n_sample,T,tau)
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X_seq = Score$Score_X
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