add DL badge

README.Rmd

@@ -15,6 +15,7 @@ knitr::opts_chunk$set(
 [![R-CMD-check](https://github.com/tnagler/wdm-r/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/tnagler/wdm-r/actions/workflows/R-CMD-check.yaml)
 [![Coverage status](https://codecov.io/gh/tnagler/wdm-r/branch/master/graph/badge.svg)](https://codecov.io/github/tnagler/wdm-r?branch=master)
 [![CRAN status](https://www.r-pkg.org/badges/version/wdm)](https://cran.r-project.org/package=wdm)
+![CRAN downloads](http://cranlogs.r-pkg.org/badges/wdm)
 
 R interface to the [wdm](https://github.com/tnagler/wdm) C++ library, which
 provides efficient implementations of weighted dependence measures and related 

README.md

@@ -6,16 +6,17 @@
 status](https://codecov.io/gh/tnagler/wdm-r/branch/master/graph/badge.svg)](https://codecov.io/github/tnagler/wdm-r?branch=master)
 [![CRAN
 status](https://www.r-pkg.org/badges/version/wdm)](https://cran.r-project.org/package=wdm)
+![CRAN downloads](http://cranlogs.r-pkg.org/badges/wdm)
 
 R interface to the [wdm](https://github.com/tnagler/wdm) C++ library,
 which provides efficient implementations of weighted dependence measures
 and related independence tests:
 
--   Pearsons’s rho
--   Spearmans’s rho
--   Kendall’s tau
--   Blomqvist’s beta
--   Hoeffding’s D
+- Pearsons’s rho
+- Spearmans’s rho
+- Kendall’s tau
+- Blomqvist’s beta
+- Hoeffding’s D
 
 All measures are computed in *O(n* log *n)* time, where *n* is the
 number of observations.
@@ -25,13 +26,13 @@ documentation](https://tnagler.github.io/wdm-r/).
 
 ### Installation
 
--   the stable release from CRAN:
+- the stable release from CRAN:
 
 ``` r
 install.packages("wdm")
 ```
 
--   the development version from [GitHub](https://github.com/) with:
+- the development version from [GitHub](https://github.com/) with:
 
 ``` r
 # install.packages("devtools")
@@ -65,9 +66,9 @@ x <- rnorm(100)
 y <- rpois(100, 1)  # all but Hoeffding's D can handle ties
 w <- runif(100)
 wdm(x, y, method = "kendall")               # unweighted
-#> [1] -0.01835054
+#> [1] -0.1206219
 wdm(x, y, method = "kendall", weights = w)  # weighted
-#> [1] -0.02273855
+#> [1] -0.01751542
 ```
 
 ##### Dependence in a matrix
@@ -76,14 +77,14 @@ wdm(x, y, method = "kendall", weights = w)  # weighted
 x <- matrix(rnorm(100 * 3), 100, 3)
 wdm(x, method = "spearman")               # unweighted
 #>            [,1]       [,2]       [,3]
-#> [1,] 1.00000000 0.02384638 0.04360036
-#> [2,] 0.02384638 1.00000000 0.09418542
-#> [3,] 0.04360036 0.09418542 1.00000000
+#> [1,]  1.0000000 -0.1842904 -0.0060006
+#> [2,] -0.1842904  1.0000000  0.1281728
+#> [3,] -0.0060006  0.1281728  1.0000000
 wdm(x, method = "spearman", weights = w)  # weighted
-#>            [,1]       [,2]       [,3]
-#> [1,] 1.00000000 0.09307647 0.08380492
-#> [2,] 0.09307647 1.00000000 0.14823843
-#> [3,] 0.08380492 0.14823843 1.00000000
+#>             [,1]       [,2]       [,3]
+#> [1,]  1.00000000 -0.1435049 0.03738866
+#> [2,] -0.14350490  1.0000000 0.23603074
+#> [3,]  0.03738866  0.2360307 1.00000000
 ```
 
 ##### Independence test
@@ -93,9 +94,9 @@ 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
-#>      estimate  statistic   p_value n_eff  method alternative
-#> 1 -0.07862879 -0.9162974 0.3595109   100 kendall   two-sided
+#>     estimate statistic   p_value n_eff  method alternative
+#> 1 0.05391935 0.6092239 0.5423761   100 kendall   two-sided
 indep_test(x, y, method = "kendall", weights = w)  # weighted
-#>      estimate  statistic   p_value   n_eff  method alternative
-#> 1 -0.06030227 -0.6043739 0.5455951 76.3268 kendall   two-sided
+#>     estimate statistic   p_value    n_eff  method alternative
+#> 1 0.01193407  0.115073 0.9083872 75.82538 kendall   two-sided
 ```