prepare for release

friendly · May 1, 2024 · c82d3d9 · c82d3d9
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diff --git a/.build-steps.R b/.build-steps.R
@@ -5,13 +5,14 @@ Sys.setenv(RGL_USE_NULL = TRUE)
 # revdep
 #remotes::install_github("r-lib/revdepcheck")
 #library(revdepcheck)
+revdepcheck::revdep_reset()
 revdepcheck::revdep_check(num_workers = 4)
 
 # get list of possibly misspelled words
-wds <- spelling::spell_check_package()
+wds <- spelling::spell_check_package() |> print()
 cat(paste(wds[, "word"], collapse = "\n"))
 # to add all words
-update_wordlist()
+spelling::update_wordlist()
 
 library(devtools)
 

diff --git a/R/datasets.R b/R/datasets.R
@@ -2502,7 +2502,7 @@ NULL
 #'   among adult male and female Chinstrap penguin (Pygoscelis antarcticus) 
 #'   nesting along the Palmer Archipelago near Palmer Station, 2007-2009 ver 6. 
 #'   Environmental Data Initiative} \doi{10.6073/pasta/c14dfcfada8ea13a17536e73eb6fbe9e}
-#' @source {Originally published in: Gorman KB, Williams TD, Fraser WR (2014) 
+#' @source {Originally published in: Gorman K.B., Williams T.D., Fraser W.R. (2014) 
 #'   Ecological Sexual Dimorphism and Environmental Variability within a 
 #'   Community of Antarctic Penguins (Genus Pygoscelis). PLoS ONE 9(3): e90081.} 
 #'   \doi{10.1371/journal.pone.0090081}

diff --git a/R/etasq.R b/R/etasq.R
@@ -20,7 +20,7 @@
 #' \eqn{\eta^2} = SSH / (SSH + SSE).  These are identical in one-way designs.
 #' 
 #' Partial eta-squared describes the proportion of total variation attributable
-#' to a given factor, partialing out (excluding) other factors from the total
+#' to a given factor, partialling out (excluding) other factors from the total
 #' nonerror variation. These are commonly used as measures of effect size or
 #' measures of (non-linear) strength of association in ANOVA models.
 #' 

diff --git a/README.Rmd b/README.Rmd
@@ -193,7 +193,7 @@ knitr::kable(dsets)
 
 This example illustrates HE plots using the classic `iris` data set. How
 do the means of the flower variables differ by `Species`? This dataset
-was the imputus for R. A. Fisher (1936) to propose a method of
+was the impetus for R. A. Fisher (1936) to propose a method of
 discriminant analysis using data collected by Edgar Anderson (1928).
 Though some may rightly deprecate Fisher for being a supporter of
 eugenics, Anderson's `iris` dataset should not be blamed.
@@ -246,22 +246,45 @@ heplot(iris.mod, hypotheses=hyp,
 ### All pairwise HE plots
 
 All pairwise HE plots are produced using the `pairs()` method for MLM
-objects.
-
-```{r, iris3, out.width="100%"}
+objects.In the plot, note how the means of most pairs of variables are very
+highly correlated, in the order Setosa < Versicolor < Virginica, but this
+pattern doesn't hold for relations with `Sepal.Width`.
+
+```{r, iris3}
+#| out.width="100%",
+#| fig.height = 6,
+#| fig.width = 6
 pairs(iris.mod, hypotheses=hyp, hyp.labels=FALSE,
       fill=TRUE, fill.alpha=0.1)
 ```
 
+### Canonical discriminant view
+
+For more than two response variables, a multivariate effect can be viewed more simply by projecting
+the data into canonical space --- the linear combinations of the responses which show the greatest
+differences among the group means relative to within-group scatter. The computations are performed
+with the [`candisc`](http://github.com/friendly/candisc) package, which has an `heplot.candisc()`
+method.
+
+```{r iris-can}
+library(candisc)
+iris.can <- candisc(iris.mod) |> print()
+
+# HE plot in canonical space
+heplot(iris.can)
+```
+
+
 ### Covariance ellipses
 
 MANOVA relies on the assumption that within-group covariance matrices are all equal.
 It is useful to visualize these in the space of some of the predictors.
-`covEllipses()` provides this both for classical and robust estimates.
+`covEllipses()` provides this both for classical and robust (`method="mve"`) estimates.
 The figure below shows these for the three Iris species and the 
 pooled covariance matrix, which is the same as the **E** matrix used
 in MANOVA tests.
 ```{r iris4, out.width="80%"}
+par(mar=c(4,4,1,1)+.1)
 covEllipses(iris[,1:4], iris$Species)
 covEllipses(iris[,1:4], iris$Species, 
             fill=TRUE, method="mve", add=TRUE, labels="")

diff --git a/README.md b/README.md
@@ -187,7 +187,7 @@ method tags. Their names are linked to the documentation on the
 
 This example illustrates HE plots using the classic `iris` data set. How
 do the means of the flower variables differ by `Species`? This dataset
-was the imputus for R. A. Fisher (1936) to propose a method of
+was the impetus for R. A. Fisher (1936) to propose a method of
 discriminant analysis using data collected by Edgar Anderson (1928).
 Though some may rightly deprecate Fisher for being a supporter of
 eugenics, Anderson’s `iris` dataset should not be blamed.

diff --git a/docs/articles/HE_manova.html b/docs/articles/HE_manova.html
diff --git a/docs/articles/HE_mmra.html b/docs/articles/HE_mmra.html
diff --git a/docs/index.html b/docs/index.html
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
@@ -4,7 +4,7 @@ pkgdown_sha: ~
 articles:
   HE_manova: HE_manova.html
   HE_mmra: HE_mmra.html
-last_built: 2024-04-30T21:44Z
+last_built: 2024-05-01T15:00Z
 urls:
   reference: https://friendly.github.io/heplots/reference
   article: https://friendly.github.io/heplots/articles

diff --git a/docs/reference/MockJury.html b/docs/reference/MockJury.html
diff --git a/docs/reference/Overdose-1.png b/docs/reference/Overdose-1.png
diff --git a/docs/reference/Overdose-2.png b/docs/reference/Overdose-2.png
diff --git a/docs/reference/Overdose-3.png b/docs/reference/Overdose-3.png
diff --git a/docs/reference/Overdose.html b/docs/reference/Overdose.html