ApplyModel
Location: ..\cubatch\Common\ApplyModel.m
function
Pred = ApplyModel (PredFun,X,Y,Model_Parameters,Pred,InitialSize,FillInMode,PreProcess,varargin);
Description:
Applies a model, as defined within Model_Parameters, to a new set of
data, represented by X (and Y when necessary).
In order to allow "on-line" applications, 'filling in' is also supported,
according to Nomikos and Mc. Gregor
Inputs:
PredFun: function computing the prediction for the desired model.
It can be a string (for MatLab©
5.3 or superior) or
a function handle (for MatLab©
6.x or superior)
X: double array with the new data
Y: double array with the Y data (in case an additional array is
needed - see Instrumental Variables Models)
Model_Parameters: model's parameters as required by PredFun
(i.e. as a structure ModelOut.model)
PredIn: structure where to save the results (i.e. structure
ModelOut.prediction)
InitialSize: size of the batch before the filling-in
(stored in ModelOut.info.initialsize)
FillInMode: fill-in mode in case the model
can be applied "on-line" (i.e.
the last mode has been given name
'time'
- case insensitive) and the length of the new
"batch" is not identical to the NOC batches. It can
either be
'Current
deviation'
or
'Zero'
PreProcess: PreProcess: Stores the preprocessing information for the model of
reference.
It contains two fields: 'modx' (for X) and
'mody' (for Y). Each of them has two fields: 'cen' and
'scal', which are row vectors of the same
length as the original X and Y and refer to centre and scaling.
1 means centre/scale according to mean and standard deviation.
The 'scal' values can also be 2 (scaling with
Root Mean Squares) or 3 (scaling with Frobenius norm)
.
varargin: additional inputs as (and if) required by PredFun
Outputs:
PredOut: structure (ModelOut.prediction)
holding the results for the new set of data.
Called by:
PARAFACApply,
nPLS1Apply
Subroutines:
Internal: Names and hyperlinks
External: Nway\nprocess
Author:
Giorgio Tomasi
Royal Agricultural and Veterinary University
MLI, LMT, Chemometrics group
Rolighedsvej 30
DK-1958 Frederiksberg C
Danmark
Last modified: 26-Oct-2002 23:07:10
Contact: Giorgio Tomasi, gt@kvl.dk
References
[1] Nomikos P., Mac Gregor J.F.,
"Monitoring batch process using multiway principal component analysis", AIChE
journal, Vol 40, n°8, 1994, 1361-1373