Description Usage Arguments Value Author(s) Examples
vectorsetup
evaluates the vectors mp (mean of the process) and the two covariance factors up and vp (i.e. covariance of the process is given by up*vp) in the interval [t0, Tfin] with timestep deltat
1 | vectorsetup(obj)
|
obj |
An “inputlist” class object yielding all the input parameters |
Values are returned as a matrix (mp,up,vp)
A. Buonocore, M.F. Carfora
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | ##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## Continuing the Wiener() example:
#### INITIALIZATION OF VECTORS
tempi <- numeric(N+1)
mp <- numeric(N+1)
up <- numeric(N+1)
vp <- numeric(N+1)
# dummy vector
app <- numeric(N)
#### EVALUATION OF MEAN AND COVARIANCE OF THE PROCESS
tempi <- seq(t0, by=deltat, length=N+1)
dum <- vectorsetup(param)
mp <- dum[,1]
up <- dum[,2]
vp <- dum[,3]
## plot of S and m
splot <- S(tempi)
mp1 <- mp - sqrt(2*sigma2)
mp2 <- mp + sqrt(2*sigma2)
matplot(tempi, cbind(mp,mp1,mp2,splot),type="l",lty=c(1,2,2,1),lwd=1,
main="mean of the process vs. threshold",xlab="time(ms)",ylab="")
legend("bottomright",c("mean","threshold"),
lty=c(1,1),col=c("black","blue"))
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