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Description

Estimate Diet Proportions Using Multivariate Tweedie Model.

Defines predict function that transforms output from a Tweedie Generalized Linear Mixed Model (using 'glmmTMB'), Generalized Additive Model (using 'mgcv'), or spatio-temporal Generalized Linear Mixed Model (using package 'tinyVAST'), and returns predicted proportions (and standard errors) across a grouping variable from an equivalent multivariate-logit Tweedie model. These predicted proportions can then be used for standard plotting and diagnostics. See Thorson et al. 2022 <doi:10.1002/ecy.3637>.

mvtweedie

DOI

An R package to interpret a Tweedie generalized linear model (GLM) or generalized additive model (GAM) involving multiple classes as an estimate of proportions for each class, implicitly involving a multivariate-logit transformation for parameters and predictions. This approach generalizes the Poisson-to-multinomial transformation to allow for non-integer responses, and can analyze either pre-processed (transformed to proportions) or raw (zero-inflated positive real values) data.

This approach is helpful, e.g., when analyzing diet samples that are heavily zero inflated without pre-processing the samples prior to analysis. In these cases, the Tweedie distribution can be interpreted mechanistically as a thinned and double-marked Poisson point process representing foraging processes.

Citation

Thorson, J. T., Arimitsu, M. L., Levi, T., & Roffler, G. (2022). Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie. Ecology. 103(5): e3637.

Metadata

Version

1.2.0

License

Unknown

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