library(hyper.gam)
# Loading required package: groupedHyperframe
# Registered S3 method overwritten by 'pROC':
# method from
# plot.roc spatstat.explore27 hyper_gam from gam
The examples in Chapter 27 require (see the explanation of the function name conflict in Section 7.4)
search path & loadedNamespaces on author’s computer
search()
# [1] ".GlobalEnv" "package:hyper.gam" "package:groupedHyperframe" "package:stats" "package:graphics" "package:grDevices" "package:utils"
# [8] "package:datasets" "package:methods" "Autoloads" "package:base"
loadedNamespaces() |> sort.int()
# [1] "abind" "base" "caret" "class" "cli" "cluster" "codetools" "compiler" "data.table"
# [10] "datasets" "deldir" "digest" "doParallel" "dplyr" "evaluate" "farver" "fastmap" "fastmatrix"
# [19] "foreach" "future" "future.apply" "generics" "geomtextpath" "GET" "ggplot2" "globals" "glue"
# [28] "goftest" "gower" "graphics" "grDevices" "grid" "gridExtra" "groupedHyperframe" "gtable" "hardhat"
# [37] "htmltools" "htmlwidgets" "httr" "hyper.gam" "ipred" "iterators" "jsonlite" "knitr" "lattice"
# [46] "lava" "lazyeval" "lifecycle" "listenv" "lubridate" "magrittr" "MASS" "Matrix" "matrixStats"
# [55] "methods" "mgcv" "ModelMetrics" "nlme" "nnet" "otel" "parallel" "parallelly" "patchwork"
# [64] "pillar" "pkgconfig" "plotly" "plyr" "polyclip" "pracma" "pROC" "prodlim" "purrr"
# [73] "R6" "RColorBrewer" "Rcpp" "recipes" "reshape2" "rlang" "rmarkdown" "rpart" "rstudioapi"
# [82] "S7" "scales" "SpatialPack" "spatstat.data" "spatstat.explore" "spatstat.geom" "spatstat.random" "spatstat.sparse" "spatstat.univar"
# [91] "spatstat.utils" "splines" "stats" "stats4" "stringi" "stringr" "survival" "systemfonts" "tensor"
# [100] "textshaping" "tibble" "tidyr" "tidyselect" "timechange" "timeDate" "tools" "utils" "vctrs"
# [109] "viridisLite" "withr" "xfun" "yaml"Function hyper.gam::hyper_gam() (v0.2.1.20151215) creates an R object of the S3 class 'hyper_gam', which inherits from the S3 class 'gam' (Chapter 22) from package mgcv (Wood 2017, v1.9.4) with an additional attribute,
attr(.,'xname'), asymbolof the hypercolumn name.
Table 27.1 summarizes the S3 methods for the class 'hyper_gam' in package hyper.gam (v0.2.1.20151215),
S3 methods hyper.gam::*.hyper_gam (v0.2.1.20151215)
| visible | generic | isS4 | |
|---|---|---|---|
contour.hyper_gam |
TRUE | graphics::contour |
FALSE |
cor_xy.hyper_gam |
TRUE | hyper.gam::cor_xy |
FALSE |
persp.hyper_gam |
TRUE | graphics::persp |
FALSE |
predict.hyper_gam |
TRUE | stats::predict |
FALSE |
sign_adjust.hyper_gam |
TRUE | hyper.gam::sign_adjust |
FALSE |
update.hyper_gam |
TRUE | stats::update |
FALSE |
27.1 Sign Adjustment
The S3 generic functions hyper.gam::sign_adjust() and hyper.gam::cor_xy() ..
🚧 Rest of this section is under construction. Expected delivery by 2025-12-31.
27.2 Visualization
The S3 methods contour.hyper_gam() and persp.hyper_gam() .. Listing 5.5 ..
🚧 Rest of this section is under construction. Expected delivery by 2025-12-31.
Visualization of the integrand surface (Chapter 5, Equation 5.3) in functions integrandSurface(), persp.hyper_gam() and contour.hyper_gam() is inspired by function mgcv::vis.gam(). Visualization of the integrand paths, as well as their projections on the \((p,q)\)- and \((p,s)\)-plane, is an original idea and design by Tingting Zhan.
27.3 Prediction
The S3 method hyper.gam::predict.hyper_gam() calculates the quantile index predictors of the training and/or test data set, based on the training model m1a (Chapter 5, Listing 5.6). The returned value is a numeric vector.
Function hyper.gam::predict.hyper_gam() is a convenient wrapper and slight modification of the S3 method mgcv::predict.gam(). The use of S3 generic stats::predict(), which is typically for predicted values, could be confusing, but we choose to follow the practice and nomenclature of function mgcv::predict.gam().
27.4 Update
The S3 method update.hyper_gam() …
🚧 Rest of this section is under construction. Expected delivery by 2025-12-31.