To analyze length-frequency data obtained simultaneously from multiple sites, we developed a new R function for estimating parameters of Gaussian mixture models that can be applied concurrently to multiple datasets with varying mixing ratios. The new function, “GMMEM”, estimates parameters (means, standard deviations, and mixing ratios) by maximizing the log-likelihood of the Gaussian mixture model using the Expectation-Maximization (EM) algorism. The number of Gaussian components must be specified prior to running the function. To evaluate the performance of the new function, two datasets were analyzed: artificially generated length-frequency data and empirical length-frequency data for Ruditapes philippinarum obtained from 20 sites during a field survey at Yokohama-Umi-no-Koen (Marine Park). Results were compared with those obtained using the existing function “normalmixEM”.
Takada et al. (Thu,) studied this question.