41  Statistical Topics

ImportantDisclaimer

These packages (Note 1) are a one-person project undergoing rapid evolution. Backward compatibility (per Hadley Wickham) is provided as a courtesy rather than a guarantee.

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• not be used as the basis for research grant applications or referenced in final research progress reports,
• not be cited as an actively maintained tool in a peer-reviewed manuscript,
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These statements are advisory in nature and do not modify or restrict the rights granted under the GNU General Public License https://www.r-project.org/Licenses/.

Table 41.1 summarizes the S3 generic functions, or the “pseudo” S3 methods, for the statistical functionalities implemented in these packages (Note 1) and/or covered in this Quarto book (Note 2), and where to find them.

Table 41.1: Index of Statistical Topics

Topic	S3 Generic Function, or (Pseudo) S3 Method	Where to Find
A
aggregate to (grouped) hyper data frame	aggregate2hyper() (Table 12.1)	from data.frame (Section 12.1), from groupedData (Section 14.1)
aggregation	aggregate()	of hyperframe (Section 16.3)
G
group-generic, Math	Math() (Table 24.2, Table 24.3)	of numeric marks in ppp (Section 24.3.1), psp (Section 26.1.1) and tess (Section 29.1.1)
group-generic, Summary	Summary() (Table 24.4, Table 24.5)	of numeric marks in ppp (Section 24.3.2), psp (Section 26.1.2) and tess (Section 29.1.2)
grouped hyper data frame, to create	as.groupedHyperframe() (Table 16.3)	from hyperframe (Section 16.4)
L
length	length()	of hyperframe (Section 16.2)
Q
quantile of numeric marks	quantile() (Table 24.6)	of ppp (Section 24.4)
S
superimpose	superimpose()	of hyperframe (Section 16.5)

Table 41.2 keeps track of the number of S3 generic functions, S3 methods and all other non-S3 functions in these package.

Listing 41.1: Table: Number of functions in these package

c('groupedHyperframe', 'groupedHyperframe.random', 'hyper.gam', 'maxEff') |>
  lapply(FUN = \(pkg) {
    ns = pkg |> getNamespace()
    nm = ns |> 
      as.list.environment() |>
      names()
    id_generic = nm |>
      vapply(FUN = sloop::is_s3_generic, env = ns, FUN.VALUE = NA)
    id_method = nm |>
      vapply(FUN = sloop::is_s3_method, env = ns, FUN.VALUE = NA)
    return(list(
      'Package' = sprintf(fmt = '**`%s`** (v%s)', pkg, packageVersion(pkg)),
      '`S3` Generic Function' = sum(id_generic),
      '`S3` Method' = sum(id_method),
      'non-`S3` Function' = sum(!id_generic & !id_method)
    ))
  }) |>
  c(list(f = c)) |>
  do.call(what = Map, args = _) |>
  as.data.frame.list(check.names = FALSE) |>
  within.data.frame(expr = {
    Total = `\`S3\` Generic Function` + `\`S3\` Method` + `non-\`S3\` Function`
  }) |>
  knitr::kable(
    caption = 'Number of `S3` generic functions, `S3` methods and non-`S3` functions in *these package*'
  )

Table 41.2: Number of S3 generic functions, S3 methods and non-S3 functions in these package

Package	S3 Generic Function	S3 Method	non-S3 Function	Total
groupedHyperframe (v0.4.0)	3	25	18	46
groupedHyperframe.random (v0.2.4)	0	0	3	3
hyper.gam (v0.2.4)	2	7	7	16
maxEff (v0.2.4)	1	14	6	21