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Simulations and analyses of Mahalanobis distance-based habitat suitability

ecdf_compare_niche.Rd

The objective is to compare the performance of habitat suitability calculated based on chi-squared cumulative distribution function and Empirical Cumulative Distribution Function (ECDF)

Usage

ecdf_compare_niche(
  p_vals = 1:5,
  n_vals = seq(20L, 500L, 20L),
  n_reps = 30L,
  seed = NULL
)

Arguments

p_vals

Integer vector; number of predictor variables (dimensions).

n_vals

Integer vector; number of records (sample sizes).

n_reps

Integer; number of replicates per combination.

seed

Optional integer for reproducibility.

Value

A list with:

  • cor_plot: ggplot of correlation vs sample size.

  • suit_plot: ggplot of suitability vs Mahalanobis distance.

  • cond_plot: ggplot of correlation vs condition number.

  • cor_df: raw correlation data.

  • obs_df: observation-level data.

  • cov_df: covariance diagnostics.

Details

Performs replicated simulations of multivariate normal data to evaluate the agreement between suitability derived from chi-squared distribution and empirical cumulative distribution function (ECDF).

Author

Matheus T. Baumgartner

Examples

# Create ECDF-niche based on personalized options:
n <- ecdf_compare_niche(p_vals = 1:3,
                        n_vals = seq(50L, 500L, 50L),
                        n_reps = 10L,
                        seed = 1991)