Package: MASSExtra 1.2.2

MASSExtra: Some 'MASS' Enhancements

Some enhancements, extensions and additions to the facilities of the recommended 'MASS' package that are useful mainly for teaching purposes, with more convenient default settings and user interfaces. Key functions from 'MASS' are imported and re-exported to avoid masking conflicts. In addition we provide some additional functions mainly used to illustrate coding paradigms and techniques, such as Gramm-Schmidt orthogonalisation and generalised eigenvalue problems.

Authors:Bill Venables

MASSExtra_1.2.2.tar.gz
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MASSExtra_1.2.2.tgz(r-4.4-any)MASSExtra_1.2.2.tgz(r-4.3-any)
MASSExtra_1.2.2.tar.gz(r-4.5-noble)MASSExtra_1.2.2.tar.gz(r-4.4-noble)
MASSExtra_1.2.2.tgz(r-4.4-emscripten)MASSExtra_1.2.2.tgz(r-4.3-emscripten)
MASSExtra.pdf |MASSExtra.html
MASSExtra/json (API)

# Install 'MASSExtra' in R:
install.packages('MASSExtra', repos = c('https://billvenables.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.

68 exports 0.00 score 2 dependencies 6 scripts 829 downloads

Last updated 2 years agofrom:d2200ff46e. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-winNOTESep 13 2024
R-4.5-linuxNOTESep 13 2024
R-4.4-winNOTESep 13 2024
R-4.4-macNOTESep 13 2024
R-4.3-winOKSep 13 2024
R-4.3-macOKSep 13 2024

Exports:.normaliseadd_termaddtermas_complexavoidbcbc_invbox_coxboxcoxbscm2indefault_testdrop_termdroptermeigen2fractionsGICginvgivens_orthglm.convertglm.nbglmmPQLgs_orthgs_orth_modifiedhr_levelsin2cmin2mmin2usrisoMDSkde_1dkde_2dkde2dlambdaldalm.glslogtranslqsmean_cmm2inmvrnormnegative.binomialnsNullpolrqdarlmrnegbinsammonstdresstep_AICstep_BICstep_downstep_GICstepAICstudrestheta.mdtheta.mltheta.mmucvusr2invar_cvcovxwhich_triwidth.SJzqzrzszu

Dependencies:demoKdeMASS

Rationale for MASSExtra

Rendered fromrationale.Rmdusingknitr::rmarkdownon Sep 13 2024.

Last update: 2023-02-16
Started: 2020-12-11

Readme and manuals

Help Manual

Help pageTopics
Normalise a vector.normalise
Coerce to complexas_complex as_complex,missing,numeric-method as_complex,numeric,missing-method as_complex,numeric,numeric-method as_complex,xy,missing-method
Avoid overlapsavoid avoid,numeric-method avoid,xy-method
Box-Cox transformbc
Box-Cox transform inversebc_inv
BostonBoston
Box-cox constructor functionbox_cox box_cox,formula-method box_cox,lm-method plot.box_cox print.box_cox
Cars93Cars93
Guess the default testdefault_test default_test.default default_test.glm default_test.glmerMod default_test.lm default_test.lmerMod default_test.multinom default_test.negbin default_test.polr
Generalized eigenvalue problemeigen2
Intermediate Information CriterionGIC
Givens orthogonalisationgivens_orth
Gram-Schmidt orthogonalizationgs_orth gs_orth_modified
#' @rdname kde_1d #' @export kernelBiweight <- function(x, mean = 0, sd = 1) h <- sqrt(7)*sd ifelse((z <- abs(x-mean)) < h, 15/16*(1 - (z/h)^2)^2/h, 0)hr_levels hr_levels.default hr_levels.kde_2d
One-dimensional Kernel Density Estimatekde_1d plot.kde_1d print.kde_1d
A Two-dimensional Kernel Density Estimatekde_2d plot.kde_2d print.kde_2d
Find the box-cox transform exponent estimatelambda lambda.box_cox lambda.default lambda.formula lambda.lm
Method function for safe predictionmakepredictcall.normalise
Mean and variance for a circular samplemean_c var_c
drop_term plot methodplot.drop_term
Print method for Box-Cox objectsprint.lambda
quinequine
Stepwise model construction and inspectionadd_term drop_term step_AIC step_BIC step_GIC
Naive backeward eliminationstep_down
Unit change functionscm2in in2cm in2mm mm2in unitChange
Conversion functions for plottingin2usr in2usr,numeric-method in2usr,xy-method usr2in usr2in,numeric-method usr2in,xy-method
Extended variance matrixvcovx vcovx.default vcovx.negbin
Which in lower/upper trianglewhich_tri
whitesidewhiteside
An S4 class to represent alternavive complex, matrix or list input forms.xy-class
Standardisation functions for modelszq zr zs zu