December 8, 2025Environmental and Ecological StatisticsOpen Access

A linear-circular regression using a finite mixture of the generalized linear regression models

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The study develops a methodology for linear-circular regression that applies maximum likelihood estimation.
Results show the ability to handle complex relationships between linear predictors and circular outcomes effectively.
The approach uses a finite mixture model to combine multiple linear-linear regression models, enhancing prediction accuracy.
Real-world applications include estimating wind directions and analyzing movement patterns of blue periwinkles.

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Implication

This methodology employs maximum likelihood estimation for optimal parameter fit in circular regression applications, implying complex relationship detection.

Cite This Study

A. Elmasry (2025) studied this question.

synapsesocial.com/papers/693624a44fa91c937236c46c https://doi.org/10.1007/s10651-025-00683-5

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Implication

This methodology employs maximum likelihood estimation for optimal parameter fit in circular regression applications, implying complex relationship detection.

A linear-circular regression using a finite mixture of the generalized linear regression models

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Implication

Cite This Study

A linear-circular regression using a finite mixture of the generalized linear regression models

Key Points

Discussion

Implication

Cite This Study

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