PubMed · 7512268
Model properties underlying non-identifiability in single channel inference.
Abstract
Models of ion channel kinetics subserve inferential methods applied to patch clamp data. For Markov models the density function of a sojourn time in a class of states is a mixture of exponentials. Determination of kinetic parameters from density functions may be complicated by non-uniqueness of solutions. This non-identifiability is investigated analytically for a class of two states, assuming detailed balance; relations between model properties, observable density parameters, and non-uniqueness are presented. The results are further developed in terms of similarity transform methods. Additional information provided by joint distributions is discussed. An example is given where identifiability of a model can be demonstrated explicitly. Attention is drawn to instances where the number of components in a density function may be misleading when used to infer the number of underlying states.
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R O Edeson, F G Ball, G F Yeo, R K Milne, S S Davies. 1994-01-22. Model properties underlying non-identifiability in single channel inference.. https://doi.org/10.1098/rspb.1994.0004
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