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Generalized Student's t ‐distribution mixtures for autoradiographic image spread modelling
Author(s) -
Aykroyd Robert G.
Publication year - 2016
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201500067
Subject(s) - line (geometry) , goodness of fit , class (philosophy) , mathematics , sensitivity (control systems) , simple (philosophy) , experimental data , algorithm , computer science , statistics , artificial intelligence , geometry , philosophy , epistemology , electronic engineering , engineering
In this paper, a new class of models for autoradiographic hot‐line data is proposed. The models, for which there is theoretical justification, are a linear combination of generalized Student's t ‐distributions and have as special cases all currently accepted line‐spread models. The new models are used to analyse experimental hot‐line data and compared with the fit of current models. The data are from a line source labelled with iodine‐125 in a resin section of 0.6 μ m in thickness. It will be shown that a significant improvement in goodness of fit, over that of previous models, can be achieved by choosing from this new class of models. A single model from this class will be proposed that has a simple form made up of only two components, but which fits experimental data significantly better than previous models. A short sensitivity analysis indicates that estimation is reliable. The modelling approach, although motivated by and applied to autoradiography, is appropriate for any mixture modelling situation.