Nothing
# Function used to summarize the simulation results. results in this case just include Biase and MSE
# param.estim is the dataset of the estimates from the simulation study
simulationBiasMSE <- function(param.estim, R2 = 0.81, ktau = 0.378, nb.simul, dec = 3, CP = 0, cpR, cpT){
# recherche des lignes correspondantes aux simulations qui n'ont pas convergees (concerne le cas des programmes esimees par MPI-OpenMP)
somme_row <- NULL
for(i in 1:nrow(param.estim))
somme_row[i] <- sum(param.estim[i,])
#on les exclu du dataframe
donnee <- param.estim[somme_row!=0,]
d <- data.frame(parametre = c("R2_adj","Ktau","R:n(%)"))
d$True <- c(R2, ktau, "")
d$Mean <- NA
d$Biais <- NA
d$MSE <- NA
if(CP == 1) d$CP <- NA
#Ktau
m_ktau <- mean(donnee$tau[!is.na(donnee$tau)])
b_tau <- ktau-m_ktau # biais Ktau
mse_tau <- mean((ktau-donnee$tau[!is.na(donnee$tau)])^2) # MSE
#R2_adj
m_r2_ad <- mean(donnee$R2trial[!is.na(donnee$R2trial)])
b_r2_ad <- R2-m_r2_ad # biais Ktau
mse_r2_ad <- mean((R2-donnee$R2trial[!is.na(donnee$R2trial)])^2) # MSE
#NA
n_NA <- nb.simul - nrow(donnee)
#sauvagarde dans d
if(CP == 0){
d[1,3:5] <- c(round(m_r2_ad, dec),round(b_r2_ad, dec),round(mse_r2_ad, dec))
d[2,3:5] <- c(round(m_ktau, dec),round(b_tau, dec),round(mse_tau, dec))
d[3,3:5] <- c("",paste(n_NA,"(",round(100*n_NA/nb.simul),")",sep = ""),"")
}else{
d[1,3:6] <- c(round(m_r2_ad, dec),round(b_r2_ad, dec),round(mse_r2_ad, dec), cpR)
d[2,3:6] <- c(round(m_ktau, dec),round(b_tau, dec),round(mse_tau, dec), cpT)
d[3,3:6] <- c("",paste(n_NA,"(",round(100*n_NA/nb.simul),")",sep = ""),"","")
}
return(d)
}
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