Finds parameters alpha, beta and gamma in PTL model to fit an observed distribution of differences in each feature's values between two given objects from a dataset.
getPTLparams(x1,x2)Numeric data input vector, standardised to range (0,1)
Numeric data input vector, standardised to range (0,1)
List with the following elements:
Numeric value specifying pair-wise global distance between objects x1 and x2
Numeric value specifying value of parameter beta in best PTL fit
Numeric value specifying value of parameter alpha in best PTL fit
Numeric value specifying value of parameter gamma in best PTL fit
Uses iterative NLS fitting to determine parameters of PTL model to represent the distribution of the differences observed between two objects selected from the dataset being analysed with LCA.