Imprecise Compositional Data Analysis: Alternative Statistical Methods
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Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications, PMLR 103:364366, 2019.
Abstract
This paper briefly describes statistical methods for analyzing imprecise compositional data that might be elicited from approximate measurement or from expert judgments. Two alternative approaches are discussed: Logratio transforms and probabilityratio transforms. The first is wellestablished and the second is under development by the author. The primary focus in this paper is on generalized linear models for predicting imprecise compositional data.
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