# indep_test: Independence Tests for Weighted Dependence Measures In wdm: Weighted Dependence Measures

## Description

Computes a (possibly weighted) dependence measure between `x` and `y` if these are vectors. If `x` and `y` are matrices then the measure between the columns of `x` and the columns of `y` are computed.

## Usage

 ```1 2 3 4 5 6 7 8``` ```indep_test( x, y, method = "pearson", weights = NULL, remove_missing = TRUE, alternative = "two-sided" ) ```

## Arguments

 `x, y` numeric vectors of data values. `x` and `y` must have the same length. `method` the dependence measure; see Details for possible values. `weights` an optional vector of weights for the observations. `remove_missing` if `TRUE`, all (pairswise) incomplete observations are removed; if `FALSE`, the function throws an error if there are incomplete observations. `alternative` indicates the alternative hypothesis and must be one of `"two-sided"`, `"greater"` or `"less"`. You can specify just the initial letter. `"greater"` corresponds to positive association, `"less"` to negative association.

## Details

Available methods:

• `"pearson"`: Pearson correlation

• `"spearman"`: Spearman's ρ

• `"kendall"`: Kendall's τ

• `"blomqvist"`: Blomqvist's β

• `"hoeffding"`: Hoeffding's D

Partial matching of method names is enabled. All methods except `"hoeffding"` work with discrete variables.

## Examples

 ```1 2 3 4 5 6``` ```x <- rnorm(100) y <- rpois(100, 1) # all but Hoeffding's D can handle ties w <- runif(100) indep_test(x, y, method = "kendall") # unweighted indep_test(x, y, method = "kendall", weights = w) # weighted ```

wdm documentation built on Aug. 2, 2020, 5:06 p.m.