Fix typo

NEWS.md

@@ -2,21 +2,16 @@
 ## New classes and methods
 * Add `biplot()` to produce PCA and CA biplots.
 * Add `plot_individuals()` and `plot_variables()` methods for `PCA` class.
-* Add `tidy()` and `augment()` to get coordinates with extra informations.
+* Add `tidy()` and `augment()` to get coordinates in tidy format with extra information.
 * Add `wrap_hull()` to compute convex hull around coordinates.
 * Add a **ggplot2** layer: `stat_hull()` (thanks to [**ggplot2** documentation](https://ggplot2.tidyverse.org/articles/extending-ggplot2.html))
 
 ## Enhancements
-* `plot_rows` and `plot_columns()`
+* `plot_rows` and `plot_columns()` gained new arguments allowing to highlight additional information by varying different graphical elements.
 * `get_coordinates()` gained a new argument allowing to select principal or standard coordinates.
 
 ## Breaking changes
-* Remove `plot()` methods for both `PCA` and `CA` classes.
-
-## Bugfixes & changes
-* `plot()`, `plot_rows()` and `plot_columns()`.
-
-## Breaking changes
+* Remove `plot()` methods for `PCA` and `CA` classes.
 * Remove `bootstrap()` and `jackknife()` methods for `numeric` and `integer` vectors.
 
 # dimensio 0.2.2

R/AllGenerics.R

@@ -436,7 +436,7 @@ setGeneric(
 #' @references
 #'  Aitchison, J. and Greenacre, M. (2002). Biplots of Compositional Data.
 #'  *Journal of the Royal Statistical Society: Series C (Applied Statistics)*,
-#'  51:4: 375‑92. \doi{10.1111/1467-9876.00275}.
+#'  51(4): 375-92. \doi{10.1111/1467-9876.00275}.
 #'
 #'  Greenacre, M. J. *Biplots in Practice*. Bilbao: Fundación BBVA, 2010.
 #' @author N. Frerebeau

README.Rmd

@@ -88,7 +88,7 @@ X <- pca(iris, center = TRUE, scale = TRUE)
 
 ### Visualize
 
-The package also to quickly visualize the results:
+The package allows to quickly visualize the results:
 
 * `plot_rows()`/`plot_individuals()` displays row/individual principal coordinates.
 * `plot_columns()`/`plot_variables()` displays columns/variable principal coordinates. `plot_variables()` depicts the variables by rays emanating from the origin (both their lengths and directions are important to the interpretation).

README.md

@@ -105,7 +105,7 @@ X <- pca(iris, center = TRUE, scale = TRUE)
 
 ### Visualize
 
-The package also to quickly visualize the results:
+The package allows to quickly visualize the results:
 
 -   `plot_rows()`/`plot_individuals()` displays row/individual principal
     coordinates.