This function performs a permutation test for the DGrowthR object. It shuffles the "contrast" column in the OD data and calculates the difference in log-likelihoods between the alternative and null models for each permutation. The permutation test helps assess the significance of the difference in models.
Usage
perm_test(
object,
num_perms = 1000,
n.cores = 1,
predict_n_steps = 100,
gp.delete = TRUE,
...
)
# S4 method for class 'DGrowthR'
perm_test(
object,
num_perms = 1000,
n.cores = 1,
predict_n_steps = 100,
gp.delete = TRUE,
...
)Arguments
- object
A DGrowthR object which contains the Gaussian Process regression results.
- num_perms
The number of permutations to perform. Defaults to 1000.
- n.cores
The number of CPU cores to use for parallel processing. Defaults to 1 (no parallel processing).
- predict_n_steps
A numeric value indicating the number of timepoints to make a prediction for with the fitted GP model. More points increases estimate accuracy, but adds compute time.
- gp.delete
A logical value indicating whether to delete the GPsep identifiers after the permutation test. Defaults to TRUE.
- ...
Additional arguments to be passed to the GP modelling function.