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:
MASSExtra_1.2.2.tar.gz
MASSExtra_1.2.2.zip(r-4.5)MASSExtra_1.2.2.zip(r-4.4)MASSExtra_1.2.2.zip(r-4.3)
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:d2200ff46e. Checks:OK: 3 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 12 2024 |
| R-4.5-win | NOTE | Nov 12 2024 |
| R-4.5-linux | NOTE | Nov 12 2024 |
| R-4.4-win | NOTE | Nov 12 2024 |
| R-4.4-mac | NOTE | Nov 12 2024 |
| R-4.3-win | OK | Nov 12 2024 |
| R-4.3-mac | OK | Nov 12 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
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Normalise a vector | .normalise |
| Coerce to complex | as_complex as_complex,missing,numeric-method as_complex,numeric,missing-method as_complex,numeric,numeric-method as_complex,xy,missing-method |
| Avoid overlaps | avoid avoid,numeric-method avoid,xy-method |
| Box-Cox transform | bc |
| Box-Cox transform inverse | bc_inv |
| Boston | Boston |
| Box-cox constructor function | box_cox box_cox,formula-method box_cox,lm-method plot.box_cox print.box_cox |
| Cars93 | Cars93 |
| Guess the default test | default_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 problem | eigen2 |
| Intermediate Information Criterion | GIC |
| Givens orthogonalisation | givens_orth |
| Gram-Schmidt orthogonalization | gs_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 Estimate | kde_1d plot.kde_1d print.kde_1d |
| A Two-dimensional Kernel Density Estimate | kde_2d plot.kde_2d print.kde_2d |
| Find the box-cox transform exponent estimate | lambda lambda.box_cox lambda.default lambda.formula lambda.lm |
| Method function for safe prediction | makepredictcall.normalise |
| Mean and variance for a circular sample | mean_c var_c |
| drop_term plot method | plot.drop_term |
| Print method for Box-Cox objects | print.lambda |
| quine | quine |
| Stepwise model construction and inspection | add_term drop_term step_AIC step_BIC step_GIC |
| Naive backeward elimination | step_down |
| Unit change functions | cm2in in2cm in2mm mm2in unitChange |
| Conversion functions for plotting | in2usr in2usr,numeric-method in2usr,xy-method usr2in usr2in,numeric-method usr2in,xy-method |
| Extended variance matrix | vcovx vcovx.default vcovx.negbin |
| Which in lower/upper triangle | which_tri |
| whiteside | whiteside |
| An S4 class to represent alternavive complex, matrix or list input forms. | xy-class |
| Standardisation functions for models | zq zr zs zu |
