Erratum
- Chapitre 12
Le package its a été supprimé du CRAN
(Août 2016). Il est possible de remplacer les anciennes commandes
par les commandes suivantes :
- priceIts par get.hist.quote (package tseries)
- its par zoo (package zoo)
- rangeIts par window (package timeSeries)
Penser également à charger le package forecast avent d'appeler la fonction Arima()
require("forecast")
A la page 226 :
# r.csdl = its(aab, as.POSIXct(row.names(aab)))
r.csdl = zoo(aab, as.POSIXct(row.names(aab)))
A la page 239 :
#datelor = csdl@dates[max.csdl["L_Oreal"]]
#datemax = csdl@dates[max.csdl["Cac40"]]
datelor = index(csdl)[max.csdl["L_Oreal"]]
datemax = index(csdl)[max.csdl["Cac40"]]
#zz<-zoo(as.data.frame(csdl),csdl@dates)
zz <- csdl
A la page 240 :
#rendav.06 = rangeIts(r.csdl, end= "2007-06-01")
#rendapr.06 = rangeIts(r.csdl, start= "2007-06-02")
rendav.06 = window(r.csdl, end= "2007-06-01")
rendapr.06 = window(r.csdl, start= "2007-06-02")
A la page 242 :
#r.lor <- rangeIts(r.csdl[,"L_Oreal"], start= "2007-12-28")
r.lor <- window(r.csdl[,"L_Oreal"], start= "2007-12-28")
# xy.acfb(r.lor.0, numer=FALSE)
xy.acfb(as.timeSeries(r.lor.0), numer=FALSE)
A la page 243 :
#mod.r.lor=Arima(r.lor.0@.Data,order=c(0,0,4),include.mean=FALSE,
# fixed=c(NA,NA,0,NA))
mod.r.lor=Arima(as.numeric(r.lor.0),order=c(0,0,4),include.mean=FALSE,
fixed=c(NA,NA,0,NA))
A la page 246 :
#mod.lor=garchFit(formula=~arma(0,4)+garch(1,1),data=r.lor.0@.Data,
# trace=FALSE,include.mean=FALSE)
mod.lor=garchFit(formula=~arma(0,4)+garch(1,1),data=r.lor.0,
trace=FALSE,include.mean=FALSE)
A la page 248 :
# axis(1,at=axTicks(1),labels=r.lor.0@dates[axTicks(1)])
axis(1,at=axTicks(1),labels=index(r.lor.0)[axTicks(1)])
A la page 250 :
# r.dan = rangeIts(r.csdl[,"Danone"], start= "2007-12-28")
r.dan = window(r.csdl[,"Danone"], start= "2007-12-28")
# xy.acfb(r.dan.0,numer=FALSE)
xy.acfb(as.timeSeries(r.dan.0),numer=FALSE)
#mod3=Arima(r.dan.0@.Data, order=c(2,0,0),include.mean= FALSE)
mod3=Arima(as.numeric(r.dan.0), order=c(2,0,0),include.mean= FALSE)
A la page 253 :
#mod.dan=garchFit(~arma(2,0)+garch(1,1),data=r.dan.0@.Data,trace=FALSE,
# include.mean=FALSE,na.action=na.pass)
mod.dan=garchFit(~arma(2,0)+garch(1,1),data=r.dan.0,trace=FALSE,
include.mean=FALSE,na.action=na.pass)
