rGAI

rGAI extends generalized additive models (GAI) by incorporating covariates and flexible seasonal variation models to analyze seasonal count data and estimate lifespan and multi-brood population structure.

Key Features:

• Covariate Inclusion: Integrates environmental covariates to model site-specific influences on seasonal variation.
• Flexible Seasonal Variation Models: Supports Normal distribution mixtures and stopover models for lifespan estimation in multi-brood populations.
• Bootstrapping Capabilities: Implements parametric and non-parametric bootstrapping for parameter and GAI uncertainty assessment.

Scientific Applications:

• Ecological Population Dynamics: Analyzes seasonal invertebrate trends, phenological shifts, and multi-brood population structures.

Methodology:

Fits parametric GAI models to count data, incorporating covariates and flexible seasonal variation descriptions via Normal distribution mixtures and stopover models, and assesses parameter and GAI uncertainty with parametric and non-parametric bootstrapping.