Jointly visualise ABC and XYZ analyses.
abcxyz(imp, frc, outplot = c(TRUE, FALSE), error = NULL, ...)
an obkect of class abc that is the output of function abc.
abc
an obkect of class abc that is the output of function xyz.
xyz
if TRUE, then provide a visualisation of the analyses.
TRUE
vector of forecast errors for each series that will be distributed in each class, presented as an average.
additional arguments passed to the plot.
A list containing:
class: a matrix containing the number of time series in each class.
class
error: a matrix containing the averaged error for each class, if the argument error was used.
error
Ord K., Fildes R., Kourentzes N. (2017) Principles of Business Forecasting, 2e. Wessex Press Publishing Co., p.515-518.
abc, xyz.
# NOT RUN { x <- abs(matrix(cumsum(rnorm(5400,0,1)),36,150)) abcxyz(abc(x),xyz(x,type="cv")) # }
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