R: Some 'MASS' Enhancements

# Some 'MASS' Enhancements

## Documentation for package ‘MASSExtra’ version 1.2.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

.normalise | Normalise a vector
add_term | Stepwise model construction and inspection
as_complex | Coerce to complex
as_complex-method | Coerce to complex
avoid | Avoid overlaps
avoid-method | Avoid overlaps
bc | Box-Cox transform
bc_inv | Box-Cox transform inverse
Boston | Boston
box_cox | Box-cox constructor function
box_cox-method | Box-cox constructor function
Cars93 | Cars93
cm2in | Unit change functions
default_test | Guess the default test
default_test.default | Guess the default test
default_test.glm | Guess the default test
default_test.glmerMod | Guess the default test
default_test.lm | Guess the default test
default_test.lmerMod | Guess the default test
default_test.multinom | Guess the default test
default_test.negbin | Guess the default test
default_test.polr | Guess the default test
drop_term | Stepwise model construction and inspection
eigen2 | Generalized eigenvalue problem
GIC | Intermediate Information Criterion
givens_orth | Givens orthogonalisation
gs_orth | Gram-Schmidt orthogonalization
gs_orth_modified | Gram-Schmidt orthogonalization
hr_levels | #' @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.default | #' @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.kde_2d | #' @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)
in2cm | Unit change functions
in2mm | Unit change functions
in2usr | Conversion functions for plotting
in2usr-method | Conversion functions for plotting
kde_1d | One-dimensional Kernel Density Estimate
kde_2d | A Two-dimensional Kernel Density Estimate
lambda | Find the box-cox transform exponent estimate
lambda.box_cox | Find the box-cox transform exponent estimate
lambda.default | Find the box-cox transform exponent estimate
lambda.formula | Find the box-cox transform exponent estimate
lambda.lm | Find the box-cox transform exponent estimate
makepredictcall.normalise | Method function for safe prediction
mean_c | Mean and variance for a circular sample
mm2in | Unit change functions
plot.box_cox | Box-cox constructor function
plot.drop_term | drop_term plot method
plot.kde_1d | One-dimensional Kernel Density Estimate
plot.kde_2d | A Two-dimensional Kernel Density Estimate
print.box_cox | Box-cox constructor function
print.kde_1d | One-dimensional Kernel Density Estimate
print.kde_2d | A Two-dimensional Kernel Density Estimate
print.lambda | Print method for Box-Cox objects
quine | quine
step_AIC | Stepwise model construction and inspection
step_BIC | Stepwise model construction and inspection
step_down | Naive backeward elimination
step_GIC | Stepwise model construction and inspection
unitChange | Unit change functions
usr2in | Conversion functions for plotting
usr2in-method | Conversion functions for plotting
var_c | Mean and variance for a circular sample
vcovx | Extended variance matrix
vcovx.default | Extended variance matrix
vcovx.negbin | Extended variance matrix
which_tri | Which in lower/upper triangle
whiteside | whiteside
xy-class | An S4 class to represent alternavive complex, matrix or list input forms.
zq | Standardisation functions for models
zr | Standardisation functions for models
zs | Standardisation functions for models
zu | Standardisation functions for models