compilr: Indices from a (dataset of) Multilevel Composition(s)

In florale/multilevelcoda: Estimate Bayesian Multilevel Models for Compositional Data

Indices from a (dataset of) Multilevel Composition(s)

Description

Compute sets of compositions and log ratio transformation for multilevel compositional data

Usage

compilr(...)

Arguments

...	arguments passed to complr.

Value

A complr object with at least 12 elements.

comp	A vector of class acomp representing one closed composition or a matrix of class acomp representing multiple closed compositions each in one row.
between_comp	A vector of class acomp representing one closed between-person composition or a matrix of class acomp representing multiple closed between-person compositions each in one row.
within_comp	A vector of class acomp representing one closed within-person composition or a matrix of class acomp representing multiple closed within-person compositions each in one row.
logratio	Log ratio transform of composition.
between_logratio	Log ratio transform of between-person composition.
within_logratio	Log ratio transform of within-person composition.
data	The user's dataset or imputed dataset if the input data contains zeros.
transform	Type of transform applied on compositional data.
parts	Names of compositional variables.
idvar	Name of the variable containing IDs.
shape	The shape of the input dataset.
total	Total amount to which the compositions is closed.

florale/multilevelcoda documentation built on April 16, 2024, 1:21 a.m.