Software implementation of SIC method for MATLAB

 

Introduction
Syntax
Program installation
Program workflow
Extras
Download

Introduction

Now the  SIC method is implemented in MATLAB script-language. The program includes two main modules: SIC_result and SIC_OSP, named in accordance with their basic functionality. The SIC_result module calculates the estimation of the maximum error deviation Beta and SIC intervals, using the calibration and test datasets, provided by the user. The SIC_OSP module employs the output of the SIC_result procedure for calculation of  the SIC-Residuals,  SIC-Leverages and construction of the Object Status Plot.

Syntax

Output=Sic_result(Tc, Tt, Yc, Yt, Yc_pred, Yt_pred, Beta, nPC, MeanY, SdevY)

Tc matrix of scores for calibration set Xc
Tt matrix of scores for test set Xt
Yc calibration set Yc after preprocessing
Yt test set Yt (optional for new object) after  preprocessing
Yc_pred predicted values for Yc after  preprocessing
Yt_pred predicted values for Yt after preprocessing
Beta parameter that defines how  the MED ‘Beta’ will be calculated. 
Admissible are either the string expressions ‘betasic’or ’betamin’,  or a positive numeric value.
nPC number of principal components used in modeling
MeanY mean value for Yc, used for post-processing
SdevY Standard deviation for Yc, also used for post-processing.


Output - MATLAB structure with the following fields
{

MeanY, SdevY used for post-processing
nPC   number of principal components  Y_test - test set Y
Y_pred   predicted Y (PLS or PCR)
Vmax, Vmin SIC-interval  for the test set
Beta   value of ’Beta’, used in the model
RMSEC   Root-Mean Square Error of Calibration
RMSEP   Root-Mean Square Error of Prediction

}

 

Result=Sic_OSP(mod)
Result - Structure, that contains SIC-Residuals, SIC-Leverages & Boundary for the test dataset from the input structure Mod - Model from the SIC_result module.
{

Res   SIC-Residuals vector
Lev   SIC-Leverage vector
Bound   Boundary values, shows how close is the object to model boundary
Bnum   number of boundary objects

}

 

Prerequisites

We provide two versions of the SIC software.

 

Version 1  uses standard LINPROG solver for solving the linear program problem as a part of the SIC algorithm.

MATLAB Optimization tool-box is required to use LINPROG function.

 

We also provide a "non-linprog" version of our program.

Version 2  uses popular GLPKMEX solver for solving the linear program problem. Version of GLPKMEX compatible with SIC software can be found in the Download section.

The installation of GLPKMEX into the Matlab environment is similar to the installation of the SIC software.

Program installation

First of all be sure, that the program files are accessible for your MATLAB IDE. There are two ways to do it. You may put the files into your current working directory (i.e. C:\MATLAB6p5\work), or change your working directory, in such a way that files are located inside.

 


To use SIC program independently from the current working directory, add the path of the SIC program files to the MATLAB Path.



Program workflow


After all necessary data are input in your MATLAB workspace (as shown in the picture above), you may start working with the program by typing the following command




To construct the OSP for your data use the following command




Extras

To calculate the OSP for the calibration set (to find  boundary samples), you should replace the test set with the calibration set in the programs input.



If the Ytest is unknown, you may enter an empty matrix instead of it. The programs output should be changed as follows




It is possible to define the absolute outlier (sample #28) on the plot, even without the SIC-Residuals.

Download

This is a beta release of the program. The authors do not assume responsibility for any expense, damage or loss caused by your use of this software, however it comes down. Any feedback is welcomed. Please, contact the author Yury Zontov  

 

You may download a free version of the program by clicking the link 

 

SIC software with Linprog

SIC software with Glpkmex

GLPKMEX



All the registered trademarks used herein are registered to whoever it is that owns them. This notification is given in lieu of any specific list of trademarks and their owners, which would not be as inclusive and would probably take a lot longer to type. 

 

 

 

First presented at the Tenth Scandinavian Symposium on Chemometrics
 Lappeenranta, Finland, June 2007

 

 



Last modification: 28.05.13