seriate_refine | R Documentation |
Refine CA-based Seriation
seriate_refine(object, ...)
## S4 method for signature 'AveragePermutationOrder'
seriate_refine(object, cutoff, margin = 1, axes = 1, n = 30, ...)
## S4 method for signature 'BootstrapCA'
seriate_refine(object, cutoff, margin = 1, axes = 1, ...)
## S4 method for signature 'RefinePermutationOrder'
hist(x, ...)
object |
A |
... |
Further arguments to be passed to internal methods. |
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 |
x |
A |
seriate_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."
seriate_refine()
returns a RefinePermutationOrder
object.
hist()
is called it for its side-effects: it results in a histogram
being displayed (invisibly returns x
).
hist(RefinePermutationOrder)
: Compute and plot a histogram of convex hull
maximum dimension length.
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")}.
Other seriation methods:
permute()
,
seriate_average()
,
seriate_rank()
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