refine | R Documentation |
Refine CA-based Seriation
refine(object, ...)
## S4 method for signature 'AveragePermutationOrder'
refine(object, cutoff, margin = 1, axes = 1, n = 30, ...)
## S4 method for signature 'BootstrapCA'
refine(object, cutoff, margin = 1, axes = 1, ...)
object |
A |
... |
Currently not used. |
cutoff |
A function that takes a numeric vector as argument and returns a single numeric value (see below). |
margin |
A length-one |
axes |
An |
n |
A non-negative |
refine()
allows to identify samples that are subject to sampling error or
samples that have underlying structural relationships and might be
influencing the ordering along the CA space.
This relies on a partial bootstrap approach to CA-based seriation where each
sample is replicated n
times. The maximum dimension length of the convex
hull around the sample point cloud allows to remove samples for a given
cutoff
value.
According to Peebles and Schachner (2012), "[this] point removal procedure [results in] a reduced dataset where the position of individuals within the CA are highly stable and which produces an ordering consistent with the assumptions of frequency seriation."
See vignette("seriation")
.
A list
with the following elements:
length
A numeric
vector giving the convex hull maximum
dimension length.
cutoff
A numeric
value giving the cutoff value for samples
selection.
exclude
An integer
vector giving the subscript of the
observations to be removed.
margin
A numeric
value specifying the dimension along which
the refinement procedure has been applied: 1
indicates rows,
2
indicates columns.
N. Frerebeau
Peeples, M. A., & Schachner, G. (2012). Refining correspondence analysis-based ceramic seriation of regional data sets. Journal of Archaeological Science, 39(8), 2818-2827. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jas.2012.04.040")}.
dimensio::bootstrap()
Other seriation methods:
as_seriation()
,
assess()
,
order()
,
permute()
,
seriate_average()
,
seriate_rank()
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