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Comparison_Lambda_Values

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elisaduz 2022-04-19 11:24:55 +02:00
parent de2ada97d5
commit f5a35a44ce
1 changed files with 23 additions and 4 deletions
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27
Comparaison_of_methods.rmd
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@ -263,15 +263,36 @@ ScoreDistribEmpiric <- function(lambda0, lambda1, n_sample, T){
} }
``` ```
```{r}
lambda0=5
lambda1=7
distrib_mc=ScoreDistribEmpiric(lambda0,lambda1,10000,T)
score_moyen=mean(distrib_mc[,1])
print(score_moyen)
score_max=max(distrib_mc[,1])
print(score_max)
score_min=min(distrib_mc[,1])
print(score_min)
amplitude=abs(score_max-score_min)
print(amplitude)
E=ComputeE(lambda0, lambda1)
print(E)
barplot(distrib_mc[,2])
```
```{r} ```{r}
ScoreDistribElisa <- function(lambda0, lambda1, T){ ScoreDistribElisa <- function(lambda0, lambda1, T){
E = ComputeE(lambda0, lambda1) E = ComputeE(lambda0, lambda1)
score_max = floor(E*log(lambda1/lambda0)) score_max = floor(E*log(lambda1/lambda0))
## score_min compute ## score_min compute
score_min_c = floor(E*log(lambda1/lambda0)+E*(lambda0-lambda1)*T) score_min_c = floor(E*log(lambda1/lambda0)+E*(lambda0-lambda1)*T)
l = seq(score_min_c,score_max,1) l = seq(score_min_c,score_max,1)
borne_inf = (l-E*log(lambda1/lambda0))/(E*(lambda0-lambda1)) borne_inf = (l-E*log(lambda1/lambda0))/(E*(lambda0-lambda1))
borne_sup = (l+1-E*log(lambda1/lambda0))/(E*(lambda0-lambda1)) borne_sup = (l+1-E*log(lambda1/lambda0))/(E*(lambda0-lambda1))
@ -289,11 +310,9 @@ distrib_score_mc=ScoreDistribEmpiric(2,3,10000,T)
distrib_score_theo=ScoreDistribElisa(2,3,T) distrib_score_theo=ScoreDistribElisa(2,3,T)
distrib_score_mc
distrib_score_theo
length(distrib_score_mc[,2])
length(distrib_score_theo[,2])
#diff_distrib_score=abs(distrib_score_mc[,2]-distrib_score_theo[,2])
#par(mfrow = c(1,2)) #par(mfrow = c(1,2))
barplot(distrib_score_mc[,2],col="blue",axes=F) barplot(distrib_score_mc[,2],col="blue",axes=F)