#
# Use BabySS and BabyECG data for this example.
#
# Want to predict future values of BabySS from future values of BabyECG
#
# Build model on first 256 values of both
#
data(BabyECG)
data(BabySS)
BabyModel <- makewpstDO(timeseries=BabyECG[1:256], groups=BabySS[1:256],
mincor=0.5)
#
# The results (ie print out answer)
BabyModel
#Stationary wavelet packet discrimination object
#Composite object containing components:[1] "BPd" "BP" "filter"
#Fisher's discrimination: done
#BP component has the following information
#BP class object. Contains "best basis" information
#Components of object:[1] "nlevelsWT" "BasisMatrix" "level" "pkt" "basiscoef"
#[6] "groups"
#Number of levels 8
#List of "best" packets
#Level id Packet id Basis coef
#[1,] 4 0 0.7340580
#[2,] 5 0 0.6811251
#[3,] 6 0 0.6443167
#[4,] 3 0 0.6193434
#[5,] 7 0 0.5967620
#[6,] 0 3 0.5473777
#[7,] 1 53 0.5082849
#
Run the code above in your browser using DataLab