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Data and models from multi-model inference of non-random mating from an information theoretic approach

This is a co-submission with Multi-model inference of non-random mating from an information theoretic approach [1]. These data corresponds to the complete simulated data set jointly with the set of models defined for analysing the data. The simulated data set was obtained using the program MateSim [...

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Detalles Bibliográficos
Autor principal: Carvajal-Rodríguez, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941146/
https://www.ncbi.nlm.nih.gov/pubmed/31909101
http://dx.doi.org/10.1016/j.dib.2019.104969
Descripción
Sumario:This is a co-submission with Multi-model inference of non-random mating from an information theoretic approach [1]. These data corresponds to the complete simulated data set jointly with the set of models defined for analysing the data. The simulated data set was obtained using the program MateSim [2]. The simulated cases correspond to one-sex competition and mate choice models. For each simulation run, the population frequencies (premating individuals) and the sample of 500 mating pairs were generated randomly for a hypothetical trait with two classes at each sex. Some datasets represent larger population size species (n = 10 000) and the mating process was represented as a sampling with replacement, and the population frequencies were constant over the mating season. The minimum phenotype frequency (MPF) allowed was 0.1. Five different model cases were simulated, namely random mating, female competition with mate choice (with independent or compound parameters) and male competition with mate choice (with independent or compound parameters). Each case was simulated 1000 times. Other datasets represent monogamous species (with large or small population size) and the mating process was without replacement (from the point of view of the available phenotypes). These data sets were used to test the performance of the multi-model inference methodology proposed in [1]. The data may be useful for testing any new/old statistics for measuring sexual selection or assortative mating patterns.