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Update Comparaison_of_methods.rmd 

Computation of the error for the simulation of sequences under H_0 : change of values of lambda
This commit is contained in:
njulia1 2022-05-15 15:38:34 +02:00
parent 980d36c175
commit e3eba7b442
1 changed files with 4 additions and 10 deletions
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Comparaison_of_methods.rmd
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@ -142,8 +142,9 @@ NbSeqH0=10000
NbSeqH1=NbSeqH0 NbSeqH1=NbSeqH0
DataH0=vector("list") DataH0=vector("list")
DataH1=vector("list") DataH1=vector("list")
lambda0=2 lambda0=1
lambda1=5 lambda1=5
T=10 T=10
tau=1 tau=1
@ -301,9 +302,6 @@ ScoreDistribTheo <- 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_c = floor(E*log(lambda1/lambda0)+E*(lambda0-lambda1)*T) score_min_c = floor(E*log(lambda1/lambda0)+E*(lambda0-lambda1)*T)
@ -334,10 +332,6 @@ distrib_score_mc = ScoreDistribEmpiric(2,3,10000,T)
distrib_score_theo = ScoreDistribTheo(2,3,T) distrib_score_theo = ScoreDistribTheo(2,3,T)
plot_graph_distrib_score <- function(distrib_score_theo, distrib_score_mc){ plot_graph_distrib_score <- function(distrib_score_theo, distrib_score_mc){
# 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))
@ -407,13 +401,13 @@ CompareMethods <- function(lambda0, lambda1, NbSeq, T, tau){
} }
#cat("- Empiric version:\n") #cat("- Empiric version:\n")
Score = ScoreDistribEmpiric(lambda0, lambda1, 10**4, T) Score = ScoreDistribEmpiric(lambda0, lambda1, 10**5, T)
LS_H0 = LocalScoreMC(lambda0, lambda1, NbSeq, T, Score$Score_X, Score$P_X, tbe0) LS_H0 = LocalScoreMC(lambda0, lambda1, NbSeq, T, Score$Score_X, Score$P_X, tbe0)
LS_H1 = LocalScoreMC(lambda0, lambda1, NbSeq, T, Score$Score_X, Score$P_X, tbe1) LS_H1 = LocalScoreMC(lambda0, lambda1, NbSeq, T, Score$Score_X, Score$P_X, tbe1)
LS_obtained = c(LS_H0$class, LS_H1$class) LS_obtained = c(LS_H0$class, LS_H1$class)
options(warn = -1) options(warn = -1)
Emp = EmpDistrib(lambda0,10**4,T,tau) Emp = EmpDistrib(lambda0,10**5,T,tau)
SS_H0 = ScanStatMC(NbSeq, T, tau, Emp, pp0) SS_H0 = ScanStatMC(NbSeq, T, tau, Emp, pp0)
SS_H1 = ScanStatMC(NbSeq, T, tau, Emp, pp1) SS_H1 = ScanStatMC(NbSeq, T, tau, Emp, pp1)
SS_obtained = c(SS_H0$class, SS_H1$class) SS_obtained = c(SS_H0$class, SS_H1$class)