The common input parameters of this function are:

Near the end of the script we have written a few code lines and suggestions on the way to implement the new model step by step:


STEP 1: Include your model

Change the newModel_Name text by the name you will give to your model.

STEP 2: Check input parameters

As an option, you could include a check for the number of input parameters, to make sure that it coincides with the number of parameters your model needs. It would also be useful to verify that the values are correct (non-negative values, between the allowed maximum and minimum,...). In that case, the program should display the values of the input parameters like it is done with the implemented models.

STEP 3: Call your own model function

At the start of the script, some variables are created. In this step, you will need the following ones:

Furthermore you have to create a new variable to save the results of the preprocess: results_model_matrix. This variable will contain one row for each study to be preprocessed and one column for each parameter the model returns. Two additional columns are required to include the mean square error and the correlation coefficient obtained from the fit.

The implementation of the new model will be included, as previously mentioned, in a new Matlab function QModeling_newModel_Name. Each time a study is preprocessed, the main program will call this function with the following input parameters:

The time of execution will be controlled by the tic-toc commands of Matlab.

STEP 4: Save the results

Once you have run the main script, the results should be saved in a text file called PreprocessingModelName_Results at the save_path directory.