Package: AHM 1.0.1

AHM: Additive Heredity Model: Method for the Mixture-of-Mixtures Experiments

An implementation of the additive heredity model for the mixture-of-mixtures experiments of Shen et al. (2019) in Technometrics <doi:10.1080/00401706.2019.1630010>. The additive heredity model considers an additive structure to inherently connect the major components with the minor components. The additive heredity model has a meaningful interpretation for the estimated model because of the hierarchical and heredity principles applied and the nonnegative garrote technique used for variable selection.

Authors:Sumin Shen [aut, cre], Lulu Kang [aut], Xinwei Deng [aut]

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AHM.pdf |AHM.html
AHM/json (API)

# Install 'AHM' in R:
install.packages('AHM', repos = c('https://vtshen.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

9 exports 0.36 score 117 dependencies 1 mentions 2 scripts 322 downloads

Last updated 5 years agofrom:e312b3caec. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 17 2024
R-4.5-winNOTESep 17 2024
R-4.5-linuxNOTESep 17 2024
R-4.4-winNOTESep 17 2024
R-4.4-macNOTESep 17 2024
R-4.3-winNOTESep 17 2024
R-4.3-macNOTESep 17 2024

Exports:ahmcheck_col_correlationcompute_aicccv.ahmenlistexpand_interactionsfind_condition_nummapping_functionmymaximin

Dependencies:askpassbase64encbrewbriobslibcachemcallrclicliprclustercodetoolscommonmarkcpp11crayoncredentialscurldaewrdescdevtoolsdiffobjdigestdownlitdplyrellipsisevaluatefansifastmapfontawesomeforeachfsgenericsgertghgitcredsglmnetgluehighrhtmltoolshtmlwidgetshttpuvhttr2iniiteratorsjquerylibjsonliteknitrlaterlatticelifecyclemagrittrmaptreeMatrixmemoisemimeminiUImixexpmvtnormopensslpillarpkgbuildpkgconfigpkgdownpkgloadplgppraiseprettyunitsprocessxprofvispromisespspurrrquadprogR6raggrappdirsrcmdcheckRcppRcppEigenrematch2remotesrlangrmarkdownroxygen2rpartrprojrootrstudioapirversionssasssessioninfoshapeshinysourcetoolsstringistringrsurvivalsyssystemfontstestthattextshapingtgptibbletidyrtidyselecttinytexurlcheckerusethisutf8vctrswaldowhiskerwithrxfunxml2xopenxtableyamlzip

Introduction to the AHM Package

Rendered fromIntroduction_to_the_AHM_package.Rmdusingknitr::rmarkdownon Sep 17 2024.

Last update: 2019-07-28
Started: 2019-07-28

Readme and manuals

Help Manual

Help pageTopics
This is one of the main functions. The function ahm computes the proposed additive heredity model.ahm
Check column correlationscheck_col_correlation
Photoresist-coating experiment datacoating
Coefficient method for the fitted ahm objectcoef.ahm
Coefficient method for the fitted cv.ahm objectcoef.cv.ahm
compute AICccompute_aicc
This is one of the main functions. It perform the cross validation on ahm models to select the optimal setting of hyper parameter hcv.ahm
Design points for the simplex centroid design with 3 componentsdesign_simplex_centroid_design_3_major_component
Create a listenlist
Expand the interaction terms for each subset group, say x11, x12, or c1, c2, c3expand_interactions
Compute the conditional number of design matrixfind_condition_num
Mapping_function is a function to add the functional coefficients of major components in front of minor components termsmapping_function
The mymaximin function generates the matrix of maximin design points. It uses the simplex centroid design as the base design, then in a stochastics way sample the candidate design points generated by the function partition.mymaximin
Predict method for the fitted ahm objectpredict.ahm
Predict method for the fitted cv.ahm objectpredict.cv.ahm
The candidate search points in the nonlinear optimization for the optimal value in the Pringles experimentpringles_candidates2search
Pringles experiment data set with the percent of Fat as the responsepringles_fat
Pringles experiment data set with the Hardness as the responsepringles_hardness
Summary method for the fitted ahm objectsummary.ahm