procmod_frame: The procmod_frame data structure.
In ProcMod: Informative Procrustean Matrix Correlation

Description Usage Arguments Value Author(s) Examples

A procmod_frame can be considered as the analog of a data.frame for vector data. In a procmod_frame each element, equivalent to a column in a data.frame is a numeric matrix or a distance matrix object (dist). Every element must describe the same number of individuals. Therefore every numeric matrix must have the same number of row (nrow) and every distance matrix must have the same size (attr(d,"Size")). A procmod_frame can simultaneously contain both types of data, numeric and distance matrix.

procmod_frame(
  ...,
  row_names = NULL,
  check_rows = TRUE,
  reorder_rows = TRUE,
  contrasts_arg = NULL
)

`...`	a set of objects to aggregate into a `procmod_frame`. These objects can be numeric matrices, or dist objects. Every objects must have the same number of row.
`row_names`	a character vector containing names associated to each row.
`check_rows`	a logical value. When set to `TRUE`, its default value, the number of row of every elements of the `procmod_frame` are tested for equality. Otherwise no check is done.
`reorder_rows`	a logical value. When set to `TRUE`, its default value, every elements of the `procmod_frame` are reordered according to the `row_names` order. Otherwise nothing is done.
`contrasts_arg`	A list, whose entries are values (numeric matrices or character strings naming functions) to be used as replacement values for the contrasts replacement function and whose names are the names of columns of data containing factors.

a procmod_frame instance.

Eric Coissac

Christelle Gonindard-Melodelima

library(vegan)
data(bacteria)
data(eukaryotes)
data(soil)

dataset <- procmod_frame(euk = vegdist(decostand(eukaryotes,
                                                 method = "hellinger"),
                                       method = "euclidean"),
                         bac = vegdist(decostand(bacteria,
                                                 method = "hellinger"),
                                       method = "euclidean"),
                         soil = scale(soil,
                                      center = TRUE,
                                      scale  = TRUE))
length(dataset)
nrow(dataset)
ncol(dataset)
dataset$euk