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Estimating Heterogeneous Birth Probabilities using the EM Algorithm: A Probabilistic Approach to Population Dynamics Modeling

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The approach enhances accuracy of estimating birth probabilities among diverse population subgroups, revealing significant patterns.
Utilizing the EM algorithm, the method effectively estimates parameters from binary birth outcome data using a finite mixture model.
In synthetic datasets, the technique demonstrates quick and accurate convergence despite potential noise and imbalances.
Model selection via Bayesian Information Criterion aids in identifying optimal subgroup numbers, enhancing interpretability in fertility research.

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Probabilistic framework reveals diverse birth probabilities in populations, indicating improved demographic insights.

Meshram et al. (2025) studied this question.

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