User`s guide

Handling Missing Data and Outliers
% Plot the data in a MATL AB Figure window
plot(data)
% Create multiexperiment data set
% by merging data segments
datam = merge(data(1:340),...
data(500:897),...
data(1001:1200),...
data(1550:2000));
% Model the multiexperiment d ata set
% using "experiments" 1, 2, and 4
m =pem(getexp(d ata m,[1,2,4]))
% Validate the model by comparing its output to
% the output data of experiment 3
compare(getexp(datam,3),m)
See Also
To learn more about the theory of handling missing data and outliers, see the
chapter on preprocessing data in System Identication: Theory for the User,
Second Edition, by Lennart Ljung, Prentice Hall PTR, 1999.
1-93