wilcoxon_filter | R Documentation |
Simple univariate filter using Wilcoxon (Mann-Whitney) test using the matrixTests package.
wilcoxon_filter(
y,
x,
force_vars = NULL,
nfilter = NULL,
p_cutoff = 0.05,
rsq_cutoff = NULL,
rsq_method = "pearson",
type = c("index", "names", "full"),
exact = FALSE,
keep_factors = TRUE,
...
)
y |
Response vector |
x |
Matrix or dataframe of predictors |
force_vars |
Vector of column names within |
nfilter |
Number of predictors to return. If |
p_cutoff |
p value cut-off |
rsq_cutoff |
r^2 cutoff for removing predictors due to collinearity.
Default |
rsq_method |
character string indicating which correlation coefficient
is to be computed. One of "pearson" (default), "kendall", or "spearman".
See |
type |
Type of vector returned. Default "index" returns indices, "names" returns predictor names, "full" returns a matrix of p-values. |
exact |
Logical whether exact or approximate p-value is calculated.
Default is |
keep_factors |
Logical affecting factors with 3 or more levels.
Dataframes are coerced to a matrix using data.matrix. Binary
factors are converted to numeric values 0/1 and analysed as such. If
|
... |
Further arguments passed to matrixTests::row_wilcoxon_twosample |
Integer vector of indices of filtered parameters (type = "index") or
character vector of names (type = "names") of filtered parameters. If
type
is "full"
full output from matrixTests::row_wilcoxon_twosample
is returned.
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