fitPTLmodel {LCA} | R Documentation |
Calibrate Polynomial-Tail Laplace (PTL) model prdictions for LCA analysis
Description
Fits PTL models to randomly sampled pairs of the dataset, to enable prediction of PTL model parameter values based on hyperparameter d
.
Usage
fitPTLmodel(x,nPairs=10000)
Arguments
x |
Numeric data input array, standardised to range (0,1) |
nPairs |
Numeric value specifying the number of samplings of pairs of objects to use to obtain hyperparameter fits |
Details
Evaluates parameters for PTL model fits to the distributions of feature-wise differences between each of a specified (large) number of pairs of objects represented in dataset x
. Obtains subsequent model fits explaining the individual PTL parameters alpha
,beta
,gamma
in terms of the global (Euclidean) distances between the corresponding pairs of objects.
Value
List with the following components:
alpha |
Object of class |
beta |
Object of class |
gamma |
Object of class |
Author(s)
Ed Curry e.curry@imperial.ac.uk