modified some text

NEWS.md

@@ -1,17 +1,20 @@
 # LearnNonparam 1.2.2
 
 - R side
-    - Changed the default value of `n_permu` to `1e4`.
-    - Added support for test statistics defined using Rcpp in `define_pmt`.
-    - Added support for `null_value` other than zero in two-sample location tests.
-    - Added the `LearnNonparam.pmt_progress` option.
-    - Replaced `KSampleF` and `RCBDF` with `OneWay` and `RCBDOneWay`.
-    - Stopped exporting abstract classes (`TwoSampleTest`, `KSampleTest`, etc.).
-    - Improved the efficiency of `ChiSquare`, `Difference`, `JonckheereTerpstra`, `KruskalWallis`, `RatioMeanDeviance` and `Studentized`.
-    - Fixed many bugs.
+    - Changed the default value of `n_permu` to `1e4`
+    - Added support for test statistics defined using Rcpp in `define_pmt`
+    - Added support for `null_value` other than zero in two-sample location tests
+    - Added support for `scoring` in `TwoSampleAssociationTest`
+    - Added the `LearnNonparam.pmt_progress` option
+    - Added `attr(t$n_permu, "n_used")`
+    - Replaced `KSampleF` and `RCBDF` with `OneWay` and `RCBDOneWay`
+    - Replaced `multicomp.*` with `multcomp.*`
+    - Stopped exporting abstract classes (`TwoSampleTest`, `KSampleTest`, etc.)
+    - Improved the efficiency of `ChiSquare`, `Difference`, `JonckheereTerpstra`, `KruskalWallis`, `RatioMeanDeviance` and `Studentized`
+    - Fixed many bugs
 
-- C++ side:
-    - Introduced a new progress bar, which is built at compile time to minimize runtime overhead.
+- C++ side
+    - Introduced a new progress bar, which is built at compile time to minimize runtime overhead
 
 # LearnNonparam 1.2.1
 

README.Rmd

@@ -9,7 +9,7 @@ output:
 ```{r, setup, include = FALSE}
 knitr::opts_chunk$set(
     collapse = TRUE, comment = "#>",
-    fig.path = "man/figures/README",
+    fig.path = "man/figures/README", fig.align = "center",
     asciicast_theme = if (Sys.getenv("IN_PKGDOWN") == "true") "pkgdown" else "readme"
 )
 asciicast::init_knitr_engine(
@@ -98,11 +98,11 @@ options(LearnNonparam.pmt_progress = TRUE)
     ```
 
     ```{asciicast, save_plot, include = FALSE}
-    ggplot2::ggsave("./man/figures/README/ggplot.svg", device = "svg")
+    ggplot2::ggsave("./man/figures/README/histogram.svg", device = "svg")
     ```
 
-    ```{r, include_plot, echo = FALSE, out.width = "100%", out.height = "75%"}
-    knitr::include_graphics("./man/figures/README/ggplot.svg")
+    ```{r, include_plot, echo = FALSE, out.width = "100%"}
+    knitr::include_graphics("./man/figures/README/histogram.svg")
     ```
 
 - Modify some active bindings and see how the results change
@@ -118,7 +118,7 @@ LearnNonparam::pmts()
 ```
 </details>
 
-The `define_pmt` function allows users to define new permutation tests. Take Cramér-von Mises test as an example:
+The `define_pmt` function allows users to define new permutation tests. Take Cramér-Von Mises test as an example:
 
 ```{asciicast, define}
 t <- define_pmt(
@@ -132,8 +132,8 @@ t <- define_pmt(
         G_y <- seq_len(n_y) / n_y
         # return a closure to calculate the test statistic
         function(x, y) {
-            x <- sort(x)
-            y <- sort(y)
+            x <- sort.int(x)
+            y <- sort.int(y)
             F <- approxfun(x, F_x, "constant", 0, 1, ties = "ordered")
             G <- approxfun(y, G_y, "constant", 0, 1, ties = "ordered")
             sum(c(F_x - G(x), G_y - F(y))^2)
@@ -142,7 +142,7 @@ t <- define_pmt(
     # reject the null hypothesis when the test statistic is large
     rejection = "r",
     scoring = "none", n_permu = 1e4,
-    name = "Cramér-von Mises Test",
+    name = "Two-Sample Cramér-Von Mises Test",
     alternative = "samples are from different distributions"
 )
 

README.md

@@ -67,7 +67,8 @@ options(LearnNonparam.pmt_progress = TRUE)
 
   <picture>
   <source media="(prefers-color-scheme: dark)" srcset="man/figures/README/test-dark.svg">
-  <img src="man/figures/README/test.svg" /> </picture>
+  <img src="man/figures/README/test.svg" style="display: block; margin: auto;" />
+  </picture>
 
 - Check the results
 
@@ -77,33 +78,37 @@ options(LearnNonparam.pmt_progress = TRUE)
 
   <picture>
   <source media="(prefers-color-scheme: dark)" srcset="man/figures/README/statistic-dark.svg">
-  <img src="man/figures/README/statistic.svg" /> </picture>
+  <img src="man/figures/README/statistic.svg" style="display: block; margin: auto;" />
+  </picture>
 
   ``` r
   t$p_value
   ```
 
   <picture>
   <source media="(prefers-color-scheme: dark)" srcset="man/figures/README/p_value-dark.svg">
-  <img src="man/figures/README/p_value.svg" /> </picture>
+  <img src="man/figures/README/p_value.svg" style="display: block; margin: auto;" />
+  </picture>
 
   ``` r
   t$print()
   ```
 
   <picture>
   <source media="(prefers-color-scheme: dark)" srcset="man/figures/README/print-dark.svg">
-  <img src="man/figures/README/print.svg" /> </picture>
+  <img src="man/figures/README/print.svg" style="display: block; margin: auto;" />
+  </picture>
 
   ``` r
   t$plot(style = "ggplot2", binwidth = 1)
   ```
 
   <picture>
   <source media="(prefers-color-scheme: dark)" srcset="man/figures/README/plot-dark.svg">
-  <img src="man/figures/README/plot.svg" /> </picture>
+  <img src="man/figures/README/plot.svg" style="display: block; margin: auto;" />
+  </picture>
 
-  <img src="./man/figures/README/ggplot.svg" width="100%" height="75%" />
+  <img src="./man/figures/README/histogram.svg" width="100%" style="display: block; margin: auto;" />
 
 - Modify some active bindings and see how the results change
 
@@ -114,7 +119,8 @@ options(LearnNonparam.pmt_progress = TRUE)
 
   <picture>
   <source media="(prefers-color-scheme: dark)" srcset="man/figures/README/modify-dark.svg">
-  <img src="man/figures/README/modify.svg" /> </picture>
+  <img src="man/figures/README/modify.svg" style="display: block; margin: auto;" />
+  </picture>
 
 <details>
 <summary>
@@ -151,7 +157,7 @@ See <code>pmts()</code> for tests implemented in this package.
 </details>
 
 The `define_pmt` function allows users to define new permutation tests.
-Take Cramér-von Mises test as an example:
+Take Cramér-Von Mises test as an example:
 
 ``` r
 t <- define_pmt(
@@ -165,8 +171,8 @@ t <- define_pmt(
         G_y <- seq_len(n_y) / n_y
         # return a closure to calculate the test statistic
         function(x, y) {
-            x <- sort(x)
-            y <- sort(y)
+            x <- sort.int(x)
+            y <- sort.int(y)
             F <- approxfun(x, F_x, "constant", 0, 1, ties = "ordered")
             G <- approxfun(y, G_y, "constant", 0, 1, ties = "ordered")
             sum(c(F_x - G(x), G_y - F(y))^2)
@@ -175,7 +181,7 @@ t <- define_pmt(
     # reject the null hypothesis when the test statistic is large
     rejection = "r",
     scoring = "none", n_permu = 1e4,
-    name = "Cramér-von Mises Test",
+    name = "Two-Sample Cramér-Von Mises Test",
     alternative = "samples are from different distributions"
 )
 
@@ -184,7 +190,8 @@ t$test(rnorm(20, 1), rnorm(20, 0))$print()
 
 <picture>
 <source media="(prefers-color-scheme: dark)" srcset="man/figures/README/define-dark.svg">
-<img src="man/figures/README/define.svg" /> </picture>
+<img src="man/figures/README/define.svg" style="display: block; margin: auto;" />
+</picture>
 
 ## References