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Bootstrapping tools

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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 AbstractSeriesBootstrapper for custom parametrizers.

Installation

pip install bootstrapping_tools

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