rebuild pkgdown

Author: friendly

cran-comments.md

@@ -16,6 +16,8 @@ o Use the generalized Moore-Penrose inverse from MASS in CMHtest() such that it
   matrix is singular.
 o Converted the package to use roxygen documentation.
 o Added `CrabSatellites` data from {countreg} b/c that's still not available on CRAN
+o Moved `grid` from `Depends:` to `Imports:`
+o Now use markdown in package documentation for easier maintenance, via {roxygen2md}
 
 
 # reverse dependencies

docs/404.html

@@ -251,7 +251,7 @@ the labels for the variables or levels. This is easy when the data are
 in table form: [`aperm()`](https://rdrr.io/r/base/aperm.html) permutes
 the dimensions, and assigning to `names` and `dimnames` changes variable
 names and level labels respectively. We will use the following version
-of `UCBAdmissions` in @(sec:mantel) below.[^1]
+of `UCBAdmissions` in @(sec:mantel) below.[¹](#fn1)
 
 ``` r
 UCB <- aperm(UCBAdmissions, c(2, 1, 3))
@@ -644,8 +644,8 @@ another.
 
 For example, a contingency table in table form (an object of
 `class(table)`) can be converted to a data.frame with
-[`as.data.frame()`](https://rdrr.io/r/base/as.data.frame.html).[^2] The
-resulting `data.frame` contains columns representing the classifying
+[`as.data.frame()`](https://rdrr.io/r/base/as.data.frame.html).[²](#fn2)
+The resulting `data.frame` contains columns representing the classifying
 factors and the table entries (as a column named by the `responseName`
 argument, defaulting to `Freq`. This is the inverse of
 [`xtabs()`](https://rdrr.io/r/stats/xtabs.html).
@@ -668,7 +668,7 @@ as.data.frame(GSStab)
 table of `Treatment` \\\times\\ `Sex` \\\times\\ `Improved`. Note the
 use of [`with()`](https://rdrr.io/r/base/with.html) to avoid having to
 use `Arthritis\$Treatment` etc. within the call to
-[`table()`](https://rdrr.io/r/base/table.html).%[^3]
+[`table()`](https://rdrr.io/r/base/table.html).%[³](#fn3)
 
 ``` r
 Art.tab <- with(Arthritis, table(Treatment, Sex, Improved))
@@ -799,7 +799,7 @@ dim(TV)
 But this 4-way table is too large and awkward to work with. Among the
 networks, Fox and Other occur infrequently. We can also cut it down to a
 3-way table by considering only viewers who persist with the current
-station.[^4]
+station.[⁴](#fn4)
 
 ``` r
 TV2 <- TV[,,1:3,]      # keep only ABC, CBS, NBC
@@ -901,17 +901,19 @@ Jersey: John Wiley & Sons.
 Hartigan, J. A., & Kleiner, B. (1984). A mosaic of television ratings.
 *The American Statistician*, *38*, 32–35.
 
-[^1]: Changing `Admit` to `Admit?` might be useful for display purposes,
+------------------------------------------------------------------------
+
+1.  Changing `Admit` to `Admit?` might be useful for display purposes,
     but is dangerous— because it is then difficult to use that variable
     name in a model formula. See @(sec:tips) for options `labeling_args`
     and `set_labels`to change variable and level names for displays in
     the `strucplot` framework.
 
-[^2]: Because R is object-oriented, this is actually a short-hand for
-    the function
+2.  Because R is object-oriented, this is actually a short-hand for the
+    function
     [`as.data.frame.table()`](https://rdrr.io/r/base/table.html).
 
-[^3]: [`table()`](https://rdrr.io/r/base/table.html) does not allow a
+3.  [`table()`](https://rdrr.io/r/base/table.html) does not allow a
     `data` argument to provide an environment in which the table
     variables are to be found. In the examples in @(sec:table) I used
     `attach(mydata)` for this purpose, but
@@ -921,6 +923,6 @@ Hartigan, J. A., & Kleiner, B. (1984). A mosaic of television ratings.
     [`table()`](https://rdrr.io/r/base/table.html) expression in a
     temporary environment of the data.
 
-[^4]: This relies on the fact that that indexing an array drops
-    dimensions of length 1 by default, using the argument `drop=TRUE`;
-    the result is coerced to the lowest possible dimension.
+4.  This relies on the fact that that indexing an array drops dimensions
+    of length 1 by default, using the argument `drop=TRUE`; the result
+    is coerced to the lowest possible dimension.

docs/articles/A_creating.md

@@ -465,7 +465,7 @@ package gives one implmentation. For an \\r \times c\\ table, the method
 provides a breakdown of the Pearson \\\chi^2\\ for association in up to
 \\M = \min(r-1, c-1)\\ dimensions, and finds scores for the row
 (\\x\_{im}\\) and column (\\y\_{jm}\\) categories such that the
-observations have the maximum possible correlations.%[^1]
+observations have the maximum possible correlations.%[¹](#fn1)
 
 Here, we carry out a simple correspondence analysis of the `HairEye`
 data. The printed results show that nearly 99% of the association
@@ -534,7 +534,9 @@ Landis, R. J., E. R. Heyman, and G. G. Koch. 1978. “Average Partial
 Association in Three-Way Contingency Tables: A Review and Discussion of
 Alternative Tests,” *International Statistical Review* 46: 237–54.
 
-[^1]: Related methods are the non-parametric CMH tests using assumed
+------------------------------------------------------------------------
+
+1.  Related methods are the non-parametric CMH tests using assumed
     row/column scores (), the analogous
     [`glm()`](https://rdrr.io/r/stats/glm.html) model-based methods (),
     and the more general RC models which can be fit using

docs/articles/B_tests.md

@@ -18,10 +18,10 @@ Assume we have a 3-way contingency table based on variables A, B, and C.
 The possible different forms of loglinear models for a 3-way table are
 shown in the table below. @(tab:loglin-3way) The **Model formula**
 column shows how to express each model for
-[`loglm()`](https://rdrr.io/pkg/MASS/man/loglm.html) in R.[^1] In the
-**Interpretation** column, the symbol “\\\perp\\” is to be read as “is
-independent of,” and “\\\\\|\\\\” means “conditional on,” or “adjusting
-for,” or just “given.”
+[`loglm()`](https://rdrr.io/pkg/MASS/man/loglm.html) in R.[¹](#fn1) In
+the **Interpretation** column, the symbol “\\\perp\\” is to be read as
+“is independent of,” and “\\\\\|\\\\” means “conditional on,” or
+“adjusting for,” or just “given.”
 
 | **Model** | **Model formula** | **Symbol** | **Interpretation** |
 |:---|:---|:---|:---|
@@ -279,7 +279,7 @@ of generalized linear models with a log link, this can be expressed as
 
 where the row-multiplicative effect parameters \\\gamma_i\\ and
 corresponding column parameters \\\delta_j\\ are estimated from the
-data.%[^2]
+data.%[²](#fn2)
 
 Similarly, the RC(2) model adds two multiplicative terms to the
 independence model,
@@ -322,12 +322,14 @@ Goodman, L. A. (1979). Simple models for the analysis of association in
 cross-classifications having ordered categories. *Journal of the
 American Statistical Association*, *74*, 537–552.
 
-[^1]: For [`glm()`](https://rdrr.io/r/stats/glm.html), or
+------------------------------------------------------------------------
+
+1.  For [`glm()`](https://rdrr.io/r/stats/glm.html), or
     [`gnm()`](https://rdrr.io/pkg/gnm/man/gnm.html), with the data in
     the form of a frequency data.frame, the same model is specified in
     the form `glm(Freq` \\\sim\\ `..., family="poisson")`, where `Freq`
     is the name of the cell frequency variable and `...` specifies the
     *Model formula*.
 
-[^2]: This is similar in spirit to a correspondence analysis with a
-    single dimension, but as a statistical model.
+2.  This is similar in spirit to a correspondence analysis with a single
+    dimension, but as a statistical model.

docs/articles/C_loglinear.md

@@ -265,7 +265,7 @@ the labels for the variables or levels. This is easy when the data are
 in table form: [`aperm()`](https://rdrr.io/r/base/aperm.html) permutes
 the dimensions, and assigning to `names` and `dimnames` changes variable
 names and level labels respectively. We will use the following version
-of `UCBAdmissions` in @ref(sec:mantel) below. [^1]
+of `UCBAdmissions` in @ref(sec:mantel) below. [¹](#fn1)
 
 ``` r
 UCB <- aperm(UCBAdmissions, c(2, 1, 3))
@@ -740,10 +740,10 @@ another.
 
 For example, a contingency table in table form (an object of
 `class(table)`) can be converted to a data.frame with
-[`as.data.frame()`](https://rdrr.io/r/base/as.data.frame.html). [^2] The
-resulting `data.frame` contains columns representing the classifying
-factors and the table entries (as a column named by the `responseName`
-argument, defaulting to `Freq`. This is the inverse of
+[`as.data.frame()`](https://rdrr.io/r/base/as.data.frame.html).
+[²](#fn2) The resulting `data.frame` contains columns representing the
+classifying factors and the table entries (as a column named by the
+`responseName` argument, defaulting to `Freq`. This is the inverse of
 [`xtabs()`](https://rdrr.io/r/stats/xtabs.html).
 
 ***Example***: Convert the `GSStab` in table form to a data.frame in
@@ -764,7 +764,7 @@ as.data.frame(GSStab)
 table of `Treatment` $`\times`$`Sex` $`\times`$`Improved`. Note the use
 of [`with()`](https://rdrr.io/r/base/with.html) to avoid having to use
 `Arthritis\$Treatment` etc. within the call to
-[`table()`](https://rdrr.io/r/base/table.html).% [^3]
+[`table()`](https://rdrr.io/r/base/table.html).% [³](#fn3)
 
 ``` r
 Art.tab <- with(Arthritis, table(Treatment, Sex, Improved))
@@ -895,7 +895,7 @@ dim(TV)
 But this 4-way table is too large and awkward to work with. Among the
 networks, Fox and Other occur infrequently. We can also cut it down to a
 3-way table by considering only viewers who persist with the current
-station. [^4]
+station. [⁴](#fn4)
 
 ``` r
 TV2 <- TV[,,1:3,]      # keep only ABC, CBS, NBC
@@ -997,17 +997,19 @@ Jersey: John Wiley & Sons.
 Hartigan, J. A., & Kleiner, B. (1984). A mosaic of television ratings.
 *The American Statistician*, *38*, 32–35.
 
-[^1]: Changing `Admit` to `Admit?` might be useful for display purposes,
+------------------------------------------------------------------------
+
+1.  Changing `Admit` to `Admit?` might be useful for display purposes,
     but is dangerous— because it is then difficult to use that variable
     name in a model formula. See @ref(sec:tips) for options
     `labeling_args` and `set_labels`to change variable and level names
     for displays in the `strucplot` framework.
 
-[^2]: Because R is object-oriented, this is actually a short-hand for
-    the function
+2.  Because R is object-oriented, this is actually a short-hand for the
+    function
     [`as.data.frame.table()`](https://rdrr.io/r/base/table.html).
 
-[^3]: [`table()`](https://rdrr.io/r/base/table.html) does not allow a
+3.  [`table()`](https://rdrr.io/r/base/table.html) does not allow a
     `data` argument to provide an environment in which the table
     variables are to be found. In the examples in @ref(sec:table) I used
     `attach(mydata)` for this purpose, but
@@ -1017,6 +1019,6 @@ Hartigan, J. A., & Kleiner, B. (1984). A mosaic of television ratings.
     [`table()`](https://rdrr.io/r/base/table.html) expression in a
     temporary environment of the data.
 
-[^4]: This relies on the fact that that indexing an array drops
-    dimensions of length 1 by default, using the argument `drop=TRUE`;
-    the result is coerced to the lowest possible dimension.
+4.  This relies on the fact that that indexing an array drops dimensions
+    of length 1 by default, using the argument `drop=TRUE`; the result
+    is coerced to the lowest possible dimension.