Permutation Tests

The permutation module provides permutation-based statistical tests.

PERMANOVA

nuee.permutation.permanova(distance_matrix: ndarray | DataFrame | Series, factors: ndarray | DataFrame | Series, permutations: int = 999, random_state: int | Generator | None = None, distance_method: str = 'bray', **kwargs) → DataFrame[source]

Distance-based PERMANOVA (sequential sums of squares).

Parameters:

  • distance_matrix – Square or condensed distance matrix.

  • factors – DataFrame, Series, or array of predictor variables. Each column is treated as a separate term evaluated sequentially.

  • permutations – Number of permutations for significance testing. Set to 0 or None to skip permutation p-values.

  • random_state – Seed or Generator for reproducible permutations.

Returns:

Dictionary containing a result table (table), the total sum of squares, and the permutation F-statistics.

Return type:

dict

General Permutation Test

nuee.permutation.permtest(statistic_func: Callable, data: ndarray, permutations: int = 999, **kwargs) → dict[source]

General permutation test.

Parameters:

  • statistic_func – Function to calculate test statistic

  • data – Data array

  • permutations – Number of permutations

  • **kwargs – Additional parameters

Returns:

Dictionary with test results

nuee.permutation.permutest(ordination_result: ConstrainedOrdinationResult, permutations: int = 999, *, random_state: int | Generator | None = None) → Dict[str, float | int | ndarray | DataFrame][source]

Permutation test for constrained ordination (RDA/CCA).

Parameters:

  • ordination_result – Constrained ordination result (e.g., from nuee.rda()).

  • permutations – Number of permutations used to build the null distribution.

  • random_state – Optional random seed or Generator for reproducible results.

Returns:

Dictionary containing the ANOVA-style table and permutation details.

Return type:

dict

ANOVA for Constrained Ordination

nuee.permutation.anova_cca(ordination_result: ConstrainedOrdinationResult, permutations: int = 999, *, random_state: int | Generator | None = None) → Dict[str, float | int | ndarray | DataFrame][source]

Permutation ANOVA for constrained ordination results.

Parameters:

  • ordination_result – Result object returned by nuee.rda() or nuee.cca().

  • permutations – Number of permutations used to approximate the null distribution.

  • random_state – Optional seed/Generator for reproducible permutations.

Returns:

Dictionary containing the ANOVA table and permutation metadata.

Return type:

dict