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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.

Functions (27)

Boston

Boston

Cars93

Cars93

GIC

Intermediate Information Criterion

Box-Cox transform

bc_inv

Box-Cox transform inverse

box_cox

Box-cox constructor function

default_test

Guess the default test

dot-normalise

Normalise a vector

eigen2

Generalized eigenvalue problem

givens_orth

Givens orthogonalisation

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)

kde_1d

One-dimensional Kernel Density Estimate

kde_2d

A Two-dimensional Kernel Density Estimate

lambda

Find the box-cox transform exponent estimate

makepredictcall.normalise

Method function for safe prediction

mean_c

Mean and variance for a circular sample

plot.drop_term

drop_term plot method