##-------------------------------------------------------------------------------------------------------- ## SCRIPT : TD Teneurs en protéines avec BUGS - Mise au format BUGS des données ## ## Authors : ## Authors : Collectif BioBayes ## Last update : 2019-02-25 ## R version 3.5.1 (2018-07-02) -- "Feather Spray" ## Copyright (C) 2018 The R Foundation for Statistical Computing ## Platform: x86_64-w64-mingw32/x64 (64-bit) ##-------------------------------------------------------------------------------------------------------- library(R2WinBUGS) #Les données Y=c(11.9,10.3,12.4,12.1,12.4,12.7,11.5,13.6,9.9,11.1,10.6,12,12.8,11.6,11.2,10.3, 12.9,10.3,11.5,14.1,12.6,12.7,11.9,9.2,12.5,11.9,11.3,11,10,15.9,10.6,11.6, 11.4,10.9,14.6,10.7,9.4,13,12.5,12.9,11.1,12.9,13.2) INN=c(1,0.8,0.8,1,0.7,0.9,1,0.9,0.6,0.7,0.7,0.7,0.9,0.8,0.8,0.6,0.9,0.69,0.72,1.1,0.97,0.98,0.87, 0.62,0.73,1.09,0.76,0.86,0.75,1.03,0.75,0.86,0.82,0.77,0.88,0.84,0.72,0.81,0.74,0.94,0.78,0.92,1.07) SPAD=c(45.5,42.6,47.8,48.6,48.2,48.8,48.9,49.9,48.6,44.9,50.2,46.1,51.6,50.9,40.4, 47.6,49.9,37.2,44.87,48,46.03,45.8,46.87,38.67,42.67,44.23,39.67,39.4,39.43,44.73,38.27,44.6,45.5,46.1, 38,43.6,43.5,44,49.9,51,48.8,48.7,49.6) ###Covariables centrées-réduites INN_cr= (INN-mean(INN))/sd(INN) SPAD_cr= (SPAD-mean(SPAD))/sd(SPAD) #Répertoire de travail setwd("D:/Sophie/Biobayes/Biobayes 2019/TD1_Teneursproteines/BUGS") #Modèle univarié SPAD bugs.data(data =list(Y=Y,covar_cr=SPAD_cr,N=43,m=mean(SPAD),s=sd(SPAD),pi=pi),data.file="data_univarie_SPAD.txt") #Modèle univarié INN bugs.data(data =list(Y=Y,covar_cr=INN_cr,N=43,m=mean(INN),s=sd(INN),pi=pi),data.file="data_univarie_INN.txt") #Modèle bivarié INN bugs.data(data =list(Y=Y,SPAD_cr=SPAD_cr,INN_cr=INN_cr,N=43,m_INN=mean(INN),s_INN=sd(INN),m_SPAD=mean(SPAD),s_SPAD=sd(SPAD),pi=pi),data.file="data_bivarie.txt") #Modèle sans covariable bugs.data(data =list(Y=Y,N=43,pi=pi),data.file="data_sanscov.txt") #Modèle prédiction INNpred_cr<- (0.95-mean(INN))/sd(INN) bugs.data(data =list(Y=c(Y,NA),covar_cr=c(INN_cr,INNpred_cr),N=44,m=mean(INN), s=sd(INN),pi=pi),data.file="data_prediction.txt")