Bootstrapping tools
Python package for bootstrap resampling by blocks on ecological time series data.
Estimates population growth rates (λ) by fitting a power law model (N(t) = N₀ · λᵗ) to seasonal count data and computing confidence intervals via block resampling. Designed for wildlife monitoring datasets (e.g., seabird burrow counts on Mexican Pacific islands).
Key features
- Block resampling — preserves temporal autocorrelation in time series.
- Power law fitting — estimates growth rate λ from seasonal population counts.
- Confidence intervals — bootstrap-derived intervals with p-value computation.
- LaTeX output — formatted interval strings for inclusion in publications.
- Abstract base class — extensible
AbstractSeriesBootstrapperfor custom parametrizers.
Installation
pip install bootstrapping_tools
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