| 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:
lengthA numeric vector giving the convex hull maximum
dimension length.
cutoffA numeric value giving the cutoff value for samples
selection.
excludeAn integer vector giving the subscript of the
observations to be removed.
marginA 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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