Maximum Likelihood Estimate of Payoffs from Time Series
Data files
Nov 04, 2015 version files 36.96 KB
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codes-description.txt
1.28 KB
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dirichlet_calling.m
6.22 KB
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dirichlet_sim.m
2.13 KB
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dirichletLF0.m
1 KB
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dirichletLF1.m
1.12 KB
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dirichletLF2.m
1.21 KB
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dirichletLFsim.m
934 B
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logratio_calling.m
4.70 KB
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logratio_sim.m
2.13 KB
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logratioLF0.m
1.24 KB
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logratioLF1.m
1.36 KB
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logratioLFsim.m
1.17 KB
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panel_allele-description
782 B
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panel_allele.mat
2.04 KB
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var_calling.m
4.47 KB
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var_sim.m
2.12 KB
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varLF0.m
1.01 KB
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varLF1.m
1.13 KB
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varLFsim.m
920 B
Abstract
We fit the data to a structural model estimated via maximum likelihood (ML) techniques. The model in the matlab code joins discrete time replicator dynamics with a stochastic structure, given by the Dirichlet distribution or, alternatively, by the logistic distribution.
This software can be used in the MatLab to estimate payoff matrices from time series data on the frequency of strategies over generations (discrete). Full details can be found in the book by Daniel Friedman and Barry Sinervo, "Evolutionary Games in Natural, Social, and Virtual Worlds", (Publisher: Oxford University Press, 2016).