Performs a permutational test for the coda_glmnet() algorithm:
It provides the distribution of results under the null hypothesis by
implementing the coda_glmnet() on different rearrangements of the response variable.
Usage
coda_glmnet_null(
x,
y,
niter = 100,
covar = NULL,
lambda = "lambda.1se",
alpha = 0.9,
sig = 0.05
)
Value
a list with "accuracy" and "confidence interval"
Arguments
x
abundance matrix or data frame (rows are samples, columns are variables (taxa))
y
outcome (binary or continuous); data type: numeric, character or factor vector
niter
number of iterations (default = 100)
covar
data frame with covariates (default = NULL)
lambda
penalization parameter (default = "lambda.1se")
alpha
elastic net parameter (default = 0.9)
sig
significance level for the confidence interval (default = 0.05)