Runs Test for Residual Randomness

Performs a nonparametric runs test to evaluate whether a sequence of residuals is randomly distributed around a reference mean. The function also computes three-sigma control limits used to identify potential residual outliers.

Usage

do_runs_test(x, type = NULL, mixing = "two.sided")

Arguments

x

Numeric vector of residuals.

type

Character string specifying the assumed mean of the residuals. If "resid" (default), the residual mean is assumed to be zero. Otherwise, the empirical mean of x is used.

mixing

Character string specifying the alternative hypothesis for the runs test:

• "two.sided": tests for both positive and negative autocorrelation (default).

• "less": left-tailed test detecting positive autocorrelation.

Value

A list containing:

• sig3lim: Numeric vector of length two giving the lower and upper three-sigma control limits for the residuals.

• p.runs: P-value from the runs test for randomness.

A small p-value (e.g., < 0.05) indicates evidence that the residual sequence is not random and may exhibit autocorrelation or other systematic patterns.

Details

The runs test evaluates whether residuals exhibit non-random structure (e.g., positive or negative autocorrelation).

See also

Other Model Diagnostics: do_jitter(), do_likelihood_profile(), do_retrospective(), get_catch_fits_plot(), get_comp_prop(), get_idx_fits(), get_idx_fits_plot(), get_model_rep_from_mcmc(), get_nLL_plot(), get_osa(), get_retrospective_plot(), get_retrospective_relative_difference(), plot_resids()