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Change lambda lists in list_of_lambda

This commit is contained in:
Paul-Corbalan 2022-05-09 23:11:16 +02:00
parent 40f1d8cba1
commit 8b1fbfda02
1 changed files with 16 additions and 9 deletions
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25
Comparaison_of_methods.rmd
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@ -84,6 +84,7 @@ EmpDistrib <- function(lambda, n_sample,T,tau){
scan=rbind(scan,ScanStat(pp,T, tau)[2]) scan=rbind(scan,ScanStat(pp,T, tau)[2])
index=rbind(index,ScanStat(pp,T, tau)[1]) index=rbind(index,ScanStat(pp,T, tau)[1])
} }
scan=unlist(scan)
min_scan=min(scan)-1 min_scan=min(scan)-1
max_scan=max(scan) max_scan=max(scan)
table1=table(factor(scan, levels = min_scan:max_scan)) table1=table(factor(scan, levels = min_scan:max_scan))
@ -206,7 +207,7 @@ for (i in 1:NbSeqH1){
pvalue=c(pvalue,result[2]) pvalue=c(pvalue,result[2])
index_scan=c(index_scan,result[3]) index_scan=c(index_scan,result[3])
} }
ScS_H1 = data.frame(num=1:NbSeqH1, scan_stat=scan, pvalue_scan=pvalue, class=(pvalue<0.05)*1, begin_scan=index_scan) ScS_H1 = data.frame(num=1:NbSeqH1, scan_stat=scan, pvalue_scan=pvalue, class=as.numeric(pvalue<0.05), begin_scan=index_scan)
ScS_H1 ScS_H1
sum(ScS_H1$class[which(ScS_H1$class=='1')])/NbSeqH1 sum(ScS_H1$class[which(ScS_H1$class=='1')])/NbSeqH1
@ -227,7 +228,7 @@ ScanStatMC <- function(NbSeq, T, tau, Emp, pp0){
index_scan=c(index_scan,result[3]) index_scan=c(index_scan,result[3])
} }
ScS_H0=data.frame(num=(1:NbSeq), scan_stat=scan, pvalue_scan=pvalue,class=c(pvalue<0.05)) ScS_H0=data.frame(num=(1:NbSeq), scan_stat=scan, pvalue_scan=pvalue,class=as.numeric(pvalue<0.05))
return(ScS_H0) return(ScS_H0)
} }
``` ```
@ -361,7 +362,6 @@ LocalScoreMC <- function(lambda0, lambda1, NbSeq, T, X_seq, P_X, tbe0){
for (i in 1:NbSeq){ for (i in 1:NbSeq){
x = floor(E*log(dexp(tbe0[[i]], rate = lambda1)/dexp(tbe0[[i]], rate = lambda0))) x = floor(E*log(dexp(tbe0[[i]], rate = lambda1)/dexp(tbe0[[i]], rate = lambda0)))
X = c(X,x)
LS = localScoreC(x)$localScore[1] LS = localScoreC(x)$localScore[1]
daudin_result = daudin(localScore = LS, score_probabilities = P_X, sequence_length = length(x), sequence_min = min_X, sequence_max = max_X) daudin_result = daudin(localScore = LS, score_probabilities = P_X, sequence_length = length(x), sequence_min = min_X, sequence_max = max_X)
@ -379,15 +379,23 @@ LocalScoreMC <- function(lambda0, lambda1, NbSeq, T, X_seq, P_X, tbe0){
NbSeq = 10**2 NbSeq = 10**2
T = 10 T = 10
list_of_lambda0 = c(2) list_of_lambda = list()
list_of_lambda1 = c(3) list_of_lambda[[1]] = c(1, 3)
list_of_lambda[[2]] = c(1, 4)
list_of_lambda[[3]] = c(1, 5)
list_of_lambda[[4]] = c(2, 4)
list_of_lambda[[5]] = c(2, 5)
list_of_lambda[[6]] = c(2, 6)
list_of_lambda[[7]] = c(4, 5)
list_of_lambda[[8]] = c(4, 8)
list_of_lambda[[9]] = c(4, 10)
for (lambda0 in list_of_lambda0){ for (Lambda in list_of_lambda){
lambda0 = Lambda[1]
lambda1 = Lambda[2]
Sensitivity = c() Sensitivity = c()
Specificity = c() Specificity = c()
accepted_lambda = c() accepted_lambda = c()
for (lambda1 in list_of_lambda1){
if (lambda0 < lambda1){ if (lambda0 < lambda1){
accepted_lambda = c(accepted_lambda,lambda1) accepted_lambda = c(accepted_lambda,lambda1)
@ -461,7 +469,6 @@ for (lambda0 in list_of_lambda0){
cat("---\n") cat("---\n")
} }
}
titleSens=TeX(paste(r'(Sensitivity for $\lambda_0=$)', lambda0)) titleSens=TeX(paste(r'(Sensitivity for $\lambda_0=$)', lambda0))
plot(x=accepted_lambda,y=Sensitivity, type='l', main = titleSens) plot(x=accepted_lambda,y=Sensitivity, type='l', main = titleSens)