27  hyper_gam from gam

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.

Until further notice, these packages should

  • not be used as a basis for research grant applications,
  • not be cited as an actively maintained tool in a peer-reviewed manuscript,
  • not be used to support or fulfill requirements for pursuing an academic degree.

In addition, work primarily based on these packages (Note 1) should not be presented at academic conferences or similar scholarly venues.

Furthermore, a person’s ability to use these packages (Note 1) does not necessarily imply an understanding of their underlying mechanisms. Accordingly, demonstration of their use alone should not be considered sufficient evidence of expertise, nor should it be credited as a basis for academic promotion or advancement.

These statements do not apply to the contributors (Tip 1) to these packages (Note 1) with respect to their specific contributions.

These statements do not apply when the maintainer of these packages (Note 1), Tingting Zhan, is credited as the first author, the lead author, and/or the corresponding author in a peer-reviewed manuscript, or as the Principal Investigator or Co-Principal Investigator in a research grant application and/or a final research progress report.

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/.

Note

The examples in Chapter 27 require

library(hyper.gam)

The function hyper.gam::hyper_gam() (v0.2.4, GPL-2) 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, GPL (>= 2)) with an additional attribute,

Table 27.1 summarizes the S3 methods for the class 'hyper_gam' in package hyper.gam (v0.2.4, GPL-2),

Table 27.1: S3 methods hyper.gam::*.hyper_gam (v0.2.4)
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.

Visualizations of the integrand surface (Chapter 5, Equation 5.3) in the function integrandSurface() and the S3 methods persp.hyper_gam() and contour.hyper_gam() are inspired by function vis.gam() (Wood 2017, v1.9.4, GPL (>= 2)). 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.

The function hyper.gam::predict.hyper_gam() is a convenient wrapper and slight modification of the S3 method predict.gam() (Wood 2017, v1.9.4, GPL (>= 2)). The use of S3 generic function predict(), which is typically for predicted values, could be confusing, but we choose to follow the practice and nomenclature of the function predict.gam() (v1.9.4, GPL (>= 2)).

27.4 Update

The S3 method update.hyper_gam() …

🚧 Rest of this section is under construction. Expected delivery by 2025-12-31.