pcoa: Principal Coordinates Analysis
In Andros-Spica/cerUB: Protocols for exploring archaeometric data
Description
Apply Principal Coordinates Analysis to a given distance matrix,
calculate variable covariances, and the percent of variance explained by
2D and 3D projections.
Usage
1
Arguments
distance_matrix
distance or dissimilarity matrix
original_data
data frame containing the original data
variable_tags
Character, two-column data frame containing (1)
the names of variables and (2) their tags.
dimensions
Numeric, number of dimensions of the projection equivalent to
k in cmdscale
Andros-Spica/cerUB documentation built on June 9, 2020, 9:22 p.m.
R Package Documentation
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Description
Apply Principal Coordinates Analysis to a given distance matrix, calculate variable covariances, and the percent of variance explained by 2D and 3D projections.
Usage
1 |
Arguments
distance_matrix |
distance or dissimilarity matrix |
original_data |
data frame containing the original data |
variable_tags |
Character, two-column data frame containing (1) the names of variables and (2) their tags. |
dimensions |
Numeric, number of dimensions of the projection equivalent to
k in |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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