Title: Variable Descriptions
Version: 1.1-2
Date: 2025-05-09
Description: Abstract descriptions of (yet) unobserved variables.
URL: http://ctm.R-forge.R-project.org
Imports: stats
License: GPL-2
NeedsCompilation: no
Packaged: 2025-05-09 12:24:07 UTC; hothorn
Author: Torsten Hothorn ORCID iD [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
Repository: CRAN
Date/Publication: 2025-05-09 15:00:02 UTC

General Information on the variables Package

Description

The variables package offers a small collection of objects describing conceptual variables and corresponding methods, for example for generating a grid of values for a (yet) unmeasured variable.

The package was written to support the basefun and mlt packages and will be of limited use outside these packages.

Author(s)

This package is authored by Torsten Hothorn <Torsten.Hothorn@R-project.org>.

References

Torsten Hothorn (2018), Most Likely Transformations: The mlt Package, Journal of Statistical Software, forthcoming. URL: https://cran.r-project.org/package=mlt.docreg

Accessor Functions

Description

Access properties of variable objects

Usage

## S3 method for class 'var'
variable.names(object, ...)
desc(object)
unit(object)
support(object)
bounds(object)
is.bounded(object)

Arguments

object

a variable object

...

additional arguments, currently not used

Details

These generics have corresponding methods for factor_var, ordered_var and numeric_var objects as well as for vars collections of those.

Check Observations Against Formal Description

Description

Check if observations correspond to their formal descriptions

Usage

check(object, data)

Arguments

object

an object of class var or vars

data

a data.frame

Details

The function returns true of data matches the description in object.

Unordered Categorical Variable

Description

Formal description of an unordered categorical variable

Usage

factor_var(name, desc = NULL, levels, ...)

Arguments

name

character, the name of the variable

desc

character, a description of what is measured

levels

character, the levels of the factor

...

ignored

Details

A conceptual description of a (yet) unobserved unordered categorical variable.

Value

An object of class factor\_var inheriting from var with corresponding methods.

Examples


  factor_var("eye", "eye color", c("blue", "brown", "green", "grey", "mixed"))

Generate Grids of Observations

Description

Make a grid of values

Usage

mkgrid(object, ...)
## S3 method for class 'continuous_var'
mkgrid(object, n = 2, add = TRUE, ...)

Arguments

object

an object of class var or vars

n

number of grid points for a continous variable

add

logical, adds the add argument (in numeric_var) to support if TRUE

...

additional arguments

Details

The function returns a names list of values for each variable.

Numeric Variable

Description

Formal description of numeric variable

Usage

numeric_var(name, desc = NULL, unit = NULL, support = c(0, 1), add = c(0, 0), 
            bounds = NULL, ...)

Arguments

name

character, the name of the variable

desc

character, a description of what is measured

unit

character, the measurement unit

support

the support of the measurements, see below

add

add these values to the support before generating a grid via mkgrid

bounds

an interval defining the bounds of a real sample space

...

ignored

Details

A numeric variable can be discrete (support is then the set of all possible values, either integer or double; integers of length 2 are interpreted as all integers inbetween) or continuous (support is a double of length 2 giving the support of the data).

If a continuous variable is bounded, bounds defines the corresponding interval.

Value

An object of class numeric\_var inheriting from var with corresponding methods.

Examples


  numeric_var("age", "age of patient", "years", support = 25:75)

  numeric_var("time", "survival time", "days", support = 0:365)

  numeric_var("time", "survival time", "days", support = c(0.0, 365), 
              bounds = c(0, Inf))

Ordered Categorical Variable

Description

Formal description of an ordered categorical variable

Usage

ordered_var(name, desc = NULL, levels, sparse = FALSE, ...)

Arguments

name

character, the name of the variable

desc

character, a description of what is measured

levels

character, the ordered levels of the factor

sparse

logical, set-up a sparse model matrix

...

ignored

Details

A conceptual description of a (yet) unobserved ordered categorical variable.

Value

An object of class ordered\_var inheriting from var with corresponding methods.

Examples


  ordered_var("temp", "temperature", c("cold", "lukewarm", "warm", "hot"))

Multiple Abstract Descriptions

Description

Concatenate or generate multiple variable descriptions

Usage

## S3 method for class 'var'
c(...)
as.vars(object)

Arguments

object

an object

...

a list of variable objects

Details

c() can be used to concatenate multiple variable objects; the corresponding generics also work for the resulting object. as.vars() tries to infer a formal description from data.

Examples


   f <- factor_var("x", levels = LETTERS[1:3])
   n <- numeric_var("y")

   fn <- c(f, n)
   variable.names(fn)
   support(fn)
   is.bounded(fn)
   mkgrid(fn, n = 9)

   as.vars(iris)