The PLMIX package offers a comprehensive framework aimed at endowing the R sta- tistical environment with some recent methodological advances in modeling and clustering partially ranked data.
Using information on students’ past participation in economic experiments, we analyze whether behavior in public goods games is affected by experience (participation in social dilemma-type experiments) and history (participation in experiments different from social dilemmas). We find that: (1) on average, the amount subjects contribute and expect others to contribute decreases with experience; (2) at the individual level, the proportion of unconditional cooperators decreases with experience, while the proportion of selfish people increases.
Finite mixture models are an important tool in the statistical analysis of data, for example in data clustering. The optimal parameters of a mixture model are usually computed by maximizing the log-likelihood functional via the Expectation-Maximization algorithm. We propose an alternative approach based on the theory of Mean Field Games, a class of differential games with an infinite number of agents. We show that the solution of a finite state space multi-population Mean Field Games system characterizes the critical points of the log-likelihood functional for a Bernoulli mixture.
This study quantitatively examines the validity of mixture formulae as models to describe the microwave-range dielectric properties of biological tissue of varying water content. Mixture formulae, specifically the Maxwell Garnett and Bruggeman models, are used to predict the dielectric properties of ex-vivo bovine muscle and liver tissue samples varying in water content. The tissues are modelled as comprising of cell and macromolecule inclusions in a water matrix.
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