Type: Package
Title: Archetypal Analysis
Version: 2.2-0.2
Date: 2025-05-02
Depends: methods, stats, modeltools, nnls (≥ 1.1)
Suggests: MASS, vcd, mlbench, ggplot2, TSP, mvtnorm
Description: The main function archetypes implements a framework for archetypal analysis supporting arbitrary problem solving mechanisms for the different conceptual parts of the algorithm.
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Collate: 'archetypes-barplot.R' 'generics.R' 'archetypes-class.R' 'archetypes-kit-blocks.R' 'archetypes-kit.R' 'archetypes-map.R' 'archetypes-movie.R' 'archetypes-panorama.R' 'pcplot.R' 'archetypes-pcplot.R' 'archetypes-robust.R' 'archetypes-screeplot.R' 'archetypes-step.R' 'archetypes-weighted.R' 'archetypes-xyplot.R' 'memento.R' 'simplex-pot.R' 'skeletonplot.R' 'body.R' 'skel.R' 'toy.R'
Packaged: 2025-05-02 08:43:44 UTC; manuel
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2025-05-02 10:00:06 UTC
RoxygenNote: 7.3.2
LazyData: true
Author: Manuel J. A. Eugster [aut, cre, cph], Friedrich Leisch [aut], Sohan Seth [ctb]
Maintainer: Manuel J. A. Eugster <manuel@mjae.net>

Extract method

Description

An extraction on a stepArchetypes object returns again a stepArchetypes object.

Usage

## S3 method for class 'stepArchetypes'
x[i]

Arguments

x

A stepArchetypes object.

i

The indizes to extract.

Value

A stepArchetypes object containing only the parts defined in i.

Perform archetypal analysis on a data matrix.

Description

Perform archetypal analysis on a data matrix.

Usage

archetypes(data, k, weights = NULL, maxIterations = 100,
  minImprovement = sqrt(.Machine$double.eps), maxKappa = 1000,
  verbose = FALSE, saveHistory = TRUE,
  family = archetypesFamily("original"), ...)

Arguments

data

A numeric n \times m data matrix.

k

The number of archetypes.

weights

Data weights matrix or vector (used as elements of the diagonal weights matrix).

maxIterations

The maximum number of iterations.

minImprovement

The minimal value of improvement between two iterations.

maxKappa

The limit of kappa to report an ill-ness warning.

verbose

Print some details during execution.

saveHistory

Save each execution step in an environment for further analyses.

family

Blocks defining the underlying problem solving mechanisms; see archetypesFamily.

...

Additional arguments for family blocks.

Value

An object of class archetypes, see as.archetypes.

References

Cutler and Breiman. Archetypal Analysis. Technometrics, 36(4), 1994. 338-348.

See Also

Other archetypes: archetypesFamily; as.archetypes; robustArchetypes; weightedArchetypes

Examples

data(toy)
  a <- archetypes(toy, 3)

Archetypes family constructor

Description

This function returns a problem solving block for each of the different conceptual parts of the algorithm.

Usage

archetypesFamily(which = c("original", "weighted", "robust"), ...)

Arguments

which

The kind of archetypes family.

...

Exchange predefined family blocks with self-defined functions.

Value

A list containing a function for each of the different parts.

See Also

Other archetypes: archetypes; as.archetypes; robustArchetypes; weightedArchetypes

Archetypal maps

Description

Two-dimensional projection of the observations based on the alpha coefficients into a space spanned by the (projected) archetypes.

Usage

archmap(object, projection = simplex_projection, projection_args = list(),
  rotate = 0, cex = 1.5, col = 1, pch = 1, xlab = "", ylab = "",
  axes = FALSE, asp = TRUE, ...)

Arguments

object

An archetypes object

projection

Projection function; see archmap_projections

projection_args

Arguments passed to the projection function; see archmap_projections

rotate

Rotation angle to rotate the projection

cex

Character expansion of archetypes

col

Color of observations

pch

Point character of observations

xlab

A label for the x-axis

ylab

A label for the y-axis

axes

Logical value to draw axes or not

asp

The y/x aspect ratio

...

Arguments passed to the underlying plot function

Value

Invisible matrix with the projected archetypes

See Also

Other archmap: archmap_projections, atypes_projection, simplex_projection, tspsimplex_projection

Examples

## Not run: 
  data("skel", package = "archetypes")
  skel2 <- subset(skel, select = -Gender)

  set.seed(1981)
  a <- archetypes(skel2, k = 5)

  ## Simplex projection:
  archmap(a, col = skel$Gender)

  ## Simplex projection with archetypes arranged according to their
  ## distances:
  archmap(a, col = skel$Gender,
          projection = tspsimplex_projection)
  archmap(a, col = skel$Gender,
          projection = tspsimplex_projection,
          projection_args = list(equidist = TRUE))

  ## MDS projection:
  archmap(a, col = skel$Gender,
          projection = atypes_projection)

## End(Not run)

Archetypes object constructor

Description

Archetypes object constructor

Usage

as.archetypes(object, k, alphas, rss, iters = NULL, call = NULL,
  history = NULL, kappas = NULL, betas = NULL, zas = NULL,
  family = NULL, familyArgs = NULL, residuals = NULL, weights = NULL,
  reweights = NULL, scaling = NULL)

Arguments

object

The archetypes; a p \times m matrix, see parameters-methods.

k

The number of archetypes;

alphas

The coefficients; a n \times p matrix, see coef.

rss

The residual sum of squares; see rss.archetypes.

iters

The number of iterations to the convergence.

call

The call of the archetypes function.

history

If saveHistory set then an environment with the archetypes object for each execution step;

kappas

The kappas for each system of linear equations.

betas

The data coefficients; a p \times n matrix.

zas

The temporary archetypes.

family

The archetypes family.

familyArgs

Additional arguments for family blocks.

residuals

The residuals.

weights

The data weights.

reweights

The data reweights.

scaling

The scaling parameters of the data.

Value

A list with an element for each parameter and class attribute archetypes.

See Also

Other archetypes: archetypesFamily; archetypes; robustArchetypes; weightedArchetypes

Barplot of archetypes.

Description

Barplot of archetypes.

Usage

## S3 method for class 'archetypes'
barplot(height, data, which = c("below", "beside"),
  which.beside = c("atypes", "variables"), which.below = c("compressed",
  "default"), percentiles = FALSE, below.compressed.height = 0.1,
  below.compressed.srt = 0, col.atypes = NULL, ...)

Arguments

height

An archetypes object.

data

The original data matrix.

which

below creates a barplot for each archetype, beside creates one barplot with bars side by side.

which.beside

Barplot according to atypes or variables.

which.below

compressed plots the labels only once.

percentiles

Show real values or percentile profiles.

below.compressed.height

Height of additional tail subplot.

below.compressed.srt

Rotations of the x-labels.

col.atypes

Color of archetypes; only used in below.compressed.

...

Passed to the underlying barplot call.

Value

Undefined.

Return best model

Description

Return best model

Usage

## S3 method for class 'stepArchetypes'
bestModel(object, ...)

## S3 method for class 'repArchetypes'
bestModel(object, ...)

Arguments

object

An archetypes object.

...

Ignored

Exploring relationships in body dimensions

Description

Body girth measurements and skeletal diameter measurements, as well as age, weight, height and gender, are given for 507 physically active individuals - 247 men and 260 women.

Usage

body

Format

A data.frame containing 507 observations of 25 variables.

References

Heinz, Peterson, Johnson and Kerk. "Exploring relationships in body dimensions". Journal of Statistics Education, 11(2). http://www.amstat.org/publications/jse/v11n2/datasets.heinz.html

See Also

skel

Return coefficients

Description

Return coefficients

Usage

## S3 method for class 'archetypes'
coef(object, type = c("alphas", "betas"), ...)

Arguments

object

An archetypes object.

type

Return alpha or beta coefficients.

...

Ignored.

Value

Coefficient matrix.

Return fitted data

Description

Returns the approximated data.

Usage

## S3 method for class 'archetypes'
fitted(object, ...)

Arguments

object

An archetypes object.

...

Ignored.

Value

Matrix with approximated data.

Return kappa

Description

Return kappa

Usage

## S3 method for class 'archetypes'
kappa(z, ...)

Arguments

z

An archetypes object.

...

Ignored.

Value

A vector of kappas.

Add lines to an existing parallel coordinates plot.

Description

Add lines to an existing parallel coordinates plot.

Usage

## S3 method for class 'pcplot'
lines(x, data, col = 1, lty = 1, ...)

Arguments

x

A matrix or data frame containing the additional data.

data

The data of the existing parallel coordinates plot.

col

Line colors.

lty

Line types.

...

Passed to underlying matlines.

Value

Undefined.

Archetypes movies.

Description

Archetypes movies.

Shows the intermediate steps of the algorithm;

Archetypes parallel coordinates plot movie.

Usage

movieplot(zs, data, show = c("atypes", "adata", "rwdata"), ssleep = 0,
  bsleep = 0, postfn = function(iter) { }, rwdata.col1 = gray(0.7),
  rwdata.col2 = 2, ...)

movieplot2(zs, data, show = "atypes", ssleep = 0, bsleep = 0,
  zas.col = 2, zas.pch = 13, old.col = rgb(1, 0.5, 0.5), ...)

moviepcplot(zs, data, show = c("atypes", "adata"), ssleep = 0, bsleep = 0,
  ...)

Arguments

zs

An archetypes object.

data

The data matrix.

show

Show archetypes or approximated data.

ssleep

Seconds to sleep before start.

bsleep

Seconds to sleep between each plot.

postfn

Post plot function; is called in each iteration after the plot call.

rwdata.col1

If show = 'rwdata': color of base data set.

rwdata.col2

If show = 'rwdata': color of weighted data set.

...

Passed to underlying plot functions.

zas.col

Color of the intermediate archetypes.

zas.pch

Type of the intermediate archetypes points.

old.col

Color of the archetypes on step further.

Value

Undefined.

Undefined.

Undefined.

Return number of archetypes

Description

Return number of archetypes

Usage

## S3 method for class 'archetypes'
nparameters(object, ...)

## S3 method for class 'stepArchetypes'
nparameters(object, ...)

## S3 method for class 'repArchetypes'
nparameters(object, ...)

Arguments

object

An archetypes object.

...

Ignored.

Value

Number of archetypes.

Panorma plot for archetypes.

Description

Panorma plot for archetypes.

Usage

## S3 method for class 'archetypes'
panorama(object, data, distfn = distEuclidean,
  xlab = "Index", ylab = "Distance", order = TRUE, col = 1, pch = 1,
  cex = 1, atypes.col = (seq(length = nparameters(object)) + 1),
  atypes.pch = rep(19, nparameters(object)), atypes.cex = rep(1,
  nparameters(object)), ylim = NULL, ...)

Arguments

object

An archetypes-related object.

data

A matrix or data frame.

distfn

Distance function.

xlab

Label of xaxis.

ylab

Label of yaxis.

order

Order the distances.

col

Color of distances.

pch

Plot character of distances.

cex

magnification of the distances.

atypes.col

Color of archetype distances.

atypes.pch

Plot character of archetype distances.

atypes.cex

Magnification of the archetype distances.

ylim

The y limits of the plot.

...

Passed to the underlying plot call.

Examples

## Not run: 
  data(toy)
  a <- archetypes(toy, 3)
  panorama(a, toy)

  ## See demo(robust-ozone).
  
## End(Not run)

Return fitted archetypes

Description

Return fitted archetypes

Usage

## S4 method for signature 'archetypes'
parameters(object, ...)

## S4 method for signature 'stepArchetypes'
parameters(object, ...)

## S4 method for signature 'repArchetypes'
parameters(object, ...)

Arguments

object

An archetypes object.

...

Ignored.

Value

Matrix with k archetypes.

Parallel coordinates of data and archetypes.

Description

Parallel coordinates of data and archetypes.

Usage

## S3 method for class 'archetypes'
pcplot(x, data, data.col = gray(0.7), data.lwd = 1,
  atypes.col = 2, atypes.lwd = 2, atypes.lty = 1, chull = NULL,
  chull.col = 1, chull.lwd = 2, chull.lty = 1, ...)

Arguments

x

An archetypes object.

data

A matrix or data frame.

data.col

Color of data lines.

data.lwd

Width of data lines.

atypes.col

Color of archetypes lines.

atypes.lwd

Width of archetypes lines.

atypes.lty

Type of archetypes lines.

chull

An integer vector giving the indices of the points from data lying on the convex hull.

chull.col

Color of convex hull lines.

chull.lwd

Width of convex hull lines.

chull.lty

Type of convex hull lines.

...

Passed to pcplot and lines.pcplot.

Value

Undefined.

Default parallel coordinates plot.

Description

Code copied from function parcoord of package MASS to simply play arround with the visualization of archetypes. At a later date, when it is clear which visualisation is the best, the functionality is probabibly merged with the original function or it is possible with parallel coordinate plots which are available et all.

Usage

## Default S3 method:
pcplot(x, col = gray(0.7), lty = 1, var.label = TRUE,
  rx = NULL, ...)

Arguments

x

A n \times m matrix or data frame who columns represent variables. Missing values are allowed.

col

Line color.

lty

Line type.

var.label

Axes labels.

rx

A 2 \times m matrix with ranges for each dimension.

...

Passed to the underlying matplot function.

Value

Undefined.

Predict method for archetypal analysis fits

Description

This method produces predicted alpha coefficients for new data.

Usage

## S3 method for class 'archetypes'
predict(object, newdata, ...)

Arguments

object

An archetypes object; currently only original-family objects.

newdata

A data frame with data for which to predict the alpha coefficients.

...

Ignored.

Value

The predict alpha coefficients.

Return residuals

Description

Return residuals

Usage

## S3 method for class 'archetypes'
residuals(object, ...)

Arguments

object

An archetypes object.

...

Ignored.

Value

Matrix with residuals.

Robust archetypes

Description

Robust archetypes

Usage

robustArchetypes(data, k, familyBlocks = list(), ...)

Arguments

familyBlocks

Exchange predefined family blocks; see archetypesFamily.

data

A numeric n \times m data matrix.

k

The number of archetypes.

...

Additional arguments for family blocks.

Value

An object of class robustArchetypes and as.archetypes.

See Also

Other archetypes: archetypesFamily; archetypes; as.archetypes; weightedArchetypes

Defined generics

Description

Generics defined by the archetypes package.

Return number of parameters

Return best model

Panorama

Parallel coordinates plot

Usage

rss(object, ...)

nparameters(object, ...)

bestModel(object, ...)

panorama(object, ...)

pcplot(x, ...)

Arguments

object

An object

...

Futher arguments

x

An object.

Return residual sum of squares

Description

Return residual sum of squares

Usage

## S3 method for class 'archetypes'
rss(object, type = c("scaled", "single", "global"), ...)

## S3 method for class 'stepArchetypes'
rss(object, ...)

## S3 method for class 'repArchetypes'
rss(object, ...)

Arguments

object

An archetypes object.

type

Return scaled, single or global RSS.

...

Ignored.

Value

Residual sum of squares.

Screeplot of stepArchetypes.

Description

Screeplot draws the residual sum of square curve based on the best model of each step.

Usage

## S3 method for class 'stepArchetypes'
screeplot(x, type = c("lines", "barplot"), ...)

Arguments

x

A stepArchetypes object.

type

Draw lines or a barplot.

...

Passed to underlying plot functions.

Value

Undefined.

Archetypal map projections

Description

Archetypal map projections

Usage

simplex_projection(x, r = 10)

tspsimplex_projection(x, r = 10, equidist = FALSE, ...)

atypes_projection(x)

Arguments

x

Archetypes matrix

r

Radius of the simplex projection

equidist

Arrange archetypes equidistantly or in relation to their distance

...

Parameters for the solve_TSP function

Value

Matrix with the projected archetypes

See Also

Other archmap: archmap

Simplex visualization

Description

The stochastic nature of the alpha coefficients implies that they exist on a standard (K-1)-simplex with the K archetypes Z as the corners, and the coefficients as the coordinate with respect to these corners. A standard simplex can be projected to two dimensions via a skew orthogonal projection, where all the vertices of the simplex are shown on a circle connected by edges. The individual alpha coefficients can be then projected into this circle.

Usage

simplexplot(object, radius = 10, order = NULL, labels_cex = 1,
  labels = NULL, show_labels = TRUE, points_col = "#00000044",
  points_pch = 19, points_cex = 1, projection = simplex_projection,
  show_points = TRUE, show_circle = TRUE, circle_col = "lightgray",
  show_edges = TRUE, edges_col = "lightgray", show_direction = FALSE,
  direction_length = 1, directions_col = points_col, ...)

Arguments

object

An archetypes object

radius

Radius of the projection

order

Order of the archetypes

labels_cex

Label expansion

labels

Labels

show_labels

Show labels

points_col

Color of the points

points_pch

Plot character of the points

points_cex

Character expansion of the points

projection

Projection function; see archmap_projections

show_points

Show the points

show_circle

Show the circle

circle_col

Color of the circle

show_edges

Show the edges

edges_col

Color of the edges

direction_length

Expansion of the direction pointers

directions_col

Color of the direction pointers

show_direction

Show direction pointers

...

Additional arguments; currently ignored

Value

Invisible list of all computed components needed for the simplex visualization.

References

See Section 6 in "Probabilistic Archetypal Analysis" by Seth and Eugster (2014), http://arxiv.org/abs/1312.7604.

Examples

### This example reproduces parts of the Figure 7 shown in
  ### "Probabilistic Archetypal Analysis" by Seth and Eugster (2014)

  data("toy", package = "archetypes")

  suppressWarnings(RNGversion("3.5.0"))
  set.seed(1234); a3 <- archetypes(toy, k = 3)
  set.seed(1237); a4 <- archetypes(toy, k = 4)
  set.seed(1238); a5 <- archetypes(toy, k = 5)

  simplexplot(a3)
  simplexplot(a3, show_direction = TRUE, show_points = FALSE)
  simplexplot(a4, projection = tspsimplex_projection)
  simplexplot(a5, show_direction = TRUE, show_points = FALSE,
    direction_length = 2, directions_col = "black")

Exploring relationships in body dimensions, skeletal measurements

Description

Skeletal diameter measurements, as well as height and gender, are given for 507 physically active individuals - 247 men and 260 women.

This is a subset of the body data set.

Usage

skel

Format

A data.frame containing 507 observations of 11 variables.

References

Heinz, Peterson, Johnson and Kerk. "Exploring relationships in body dimensions". Journal of Statistics Education, 11(2). http://www.amstat.org/publications/jse/v11n2/datasets.heinz.html

See Also

body

Skeleton plot.

Description

Displays a schematic representation of skeleton data as available in dataset skel.

Displays a generic skeleton with annotations explaining the measurements available in data set skel.

Usage

skeletonplot(x, skel.width = 100, skel.height = 200, ylab = "Height (cm)",
  base.radius = 2, xlab = "", xlim = (nrow(x) * c(0, skel.width)),
  ylim = c(0, skel.height), col = NULL, mtext = TRUE, skel.lwd = 1, ...)

jd()

Arguments

x

Matrix or data.frame of skeleton data.

skel.width

Reference width for instance calculation.

skel.height

Reference height for instance calculation.

base.radius

Base radius for points.

xlab

The x label of the plot.

ylab

The y label of the plot.

xlim

Numeric of length 2 giving the x limits for the plot.

ylim

Numeric of length 2 giving the y limits for the plot.

col

Color of the different parts of the skeleton.

mtext

Label archetypes.

skel.lwd

Line width of skeleton.

...

Passed to underlying canvas plot function.

Value

List of skeleton instances.

Generic skeleton instance.

See Also

skel

Run archetypes algorithm repeatedly

Description

Run archetypes algorithm repeatedly

Usage

stepArchetypes(..., k, nrep = 3, method = archetypes, verbose = TRUE)

Arguments

...

Passed to the specific archetype function.

k

A vector of integers passed in turn to the k argument of archetypes.

nrep

For each value of k run archetypes nrep times.

method

Archetypes function to use, typically archetypes, weightedArchetypes or robustArchetypes,

verbose

Show progress during exection.

Value

A list with k elements and class attribute stepArchetypes. Each element is a list of class repArchetypes with nrep elements; only for internal usage.

See Also

archetypes

Examples

## Not run: 
  data(skel)
  skel2 <- subset(skel, select=-Gender)
  as <- stepArchetypes(skel2, k=1:5, verbose=FALSE)

  ## Residual sum of squares curve:
  screeplot(as)

  ## Select three archetypes and from that the best
  ## recurrence:
  a3 <- bestModel(as[[3]])
  
## End(Not run)

Summary method for stepArchetypes object

Description

Summary method for stepArchetypes object

Usage

## S3 method for class 'stepArchetypes'
summary(object, ...)

Arguments

object

A stepArchetypes object.

...

Ignored.

Value

Undefined.

Toy data set

Description

A simple artificial two-dimensional data set.

Usage

toy

Format

A data.frame containing 250 observations of 2 variables.

Weighted archetypes

Description

Weighted archetypes

Usage

weightedArchetypes(data, k, weights = NULL, familyBlocks = list(), ...)

Arguments

weights

Data weights matrix.

familyBlocks

Exchange predefined family blocks; see archetypesFamily.

data

A numeric n \times m data matrix.

k

The number of archetypes.

...

Additional arguments for family blocks.

Value

An object of class weightedArchetypes and as.archetypes.

See Also

Other archetypes: archetypesFamily; archetypes; as.archetypes; robustArchetypes

Return weights

Description

Return weights

Usage

## S3 method for class 'archetypes'
weights(object, type = c("weights", "reweights"), ...)

Arguments

object

An archetypes object.

type

Return global weights (weighted archetypes) or weights calculated during the iterations (robust archetypes).

...

Ignored.

Value

Vector of weights.

Two-dimensional plot.

Description

Two-dimensional plot.

Usage

xyplot(x, ...)

Arguments

x

An object.

...

Further arguments.

Value

Undefined.

Plot of two-dimensional data and archetypes.

Description

Plot of two-dimensional data and archetypes.

Usage

## S3 method for class 'archetypes'
xyplot(x, y, data.col = 1, data.pch = 19,
  data.bg = NULL, atypes.col = 2, atypes.pch = 19, ahull.show = TRUE,
  ahull.col = atypes.col, chull = NULL, chull.col = gray(0.7),
  chull.pch = 19, adata.show = FALSE, adata.col = 3, adata.pch = 13,
  link.col = data.col, link.lty = 1, ...)

Arguments

x

An archetypes object.

y

A matrix or data frame.

data.col

Color of data points.

data.pch

Type of data points.

data.bg

Background of data points.

atypes.col

Color of archetypes points.

atypes.pch

Type of archetypes points.

ahull.show

Show approximated convex hull.

ahull.col

Color of approximated convex hull line.

chull

An integer vector giving the indices of the points from data lying on the convex hull.

chull.col

Color of convex hull points.

chull.pch

Type of convex hull points.

adata.show

Show approximated data with link to the original data.

adata.col

Color of approximated data points.

adata.pch

Type of approximated data points.

link.col

Color of link between approximated and original data points.

link.lty

Line type of link between approximated and original data points.

...

Passed to the underlying plot functions.

Value

Undefined.

Note

The link between approximated and original data is based on an idea and Matlab source code of Bernard Pailthorpe.

Plot of two-dimensional data and robust archetypes.

Description

Plot of two-dimensional data and robust archetypes.

Usage

## S3 method for class 'robustArchetypes'
xyplot(x, y, ...)

Arguments

x

An archetypes object.

y

A matrix or data frame.

...

Arguments of xyplot.weightedArchetypes and xyplot.robustArchetypes

Plot of two-dimensional data and stepArchetypes.

Description

Plot of two-dimensional data and stepArchetypes.

Usage

## S3 method for class 'stepArchetypes'
xyplot(x, y, data.col = gray(0.7), data.pch = 19,
  atypes.col = (seq_len(length(x) * length(x[[1]])) + 1), atypes.pch = 19,
  ahull.show = TRUE, ahull.col = atypes.col, ...)

Arguments

x

An stepArchetypes object.

y

A matrix or data frame.

data.col

Color of data points.

data.pch

Type of data points.

atypes.col

Color of archetypes points.

atypes.pch

Type of archetypes points.

ahull.show

Show approximated convex hull.

ahull.col

Color of approximated convex hull line.

...

Passed to the underlying plot functions.

Value

Undefined.

Plot of two-dimensional data and weighted archetypes.

Description

Plot of two-dimensional data and weighted archetypes.

Usage

## S3 method for class 'weightedArchetypes'
xyplot(x, y, data.col = 1, data.pch = 21,
  data.bg = gray, link.col = NULL, link.lty = NULL,
  weights.type = "weights", ...)

Arguments

x

An archetypes object.

y

A matrix or data frame.

data.col

Color of data points.

data.pch

Type of data points.

data.bg

Background of data points.

link.col

Color of link between approximated and original data points.

link.lty

Line type of link between approximated and original data points.

weights.type

Weights to display; see weights.archetypes.

...

Arguments of xyplot.archetypes.