This simulated data set consists in 50 subgroups, each with 5 observations, on 4 variables.
There is an isolated location shift involving
only the first variable at time
a step shift, involving the third and fourth variables,
t=31. The in-control distribution
is Student's t with 3 degrees of freedom, zero mean
and such that
See the example for the exact code used to simulate the data.
A 4x5x50 array.
data(Student) mphase1(Student) # # Replication of the simulation # # Generation of the in-control observations set.seed(1) m <- 50 n <- 5 p <- 4 df <- 3 Sigma <- outer(1:p,1:p,function(i,j) 0.8^abs(i-j)) Sigma xnorm <- crossprod(chol(Sigma),matrix(rnorm(p*n*m),p)) xchisq <- sqrt(rchisq(n*m,df)/(df-2)) x <- array(sweep(xnorm,2,xchisq,"/"),c(p,n,m)) # Then, we add an isolated shift at time 10 # (only for the first variable) x[1,,10] <- x[1,,10]+1 # and, a step shift starting at time 31 # (only for the third and fourth variable) x[3:4,,31:50] <- x[3:4,,31:50] + c(0.50,-0.25) dimnames(x)<-list(paste("X",1:4,sep=""),NULL,NULL) identical(x,Student)
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