knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
This package is intended to provide some basic abstractions and default implementations of basic computational infrastructure for multivariate component-based modeling such as principal components analysis.
The main idea is to model multivariate decompositions as involving projections from an input data space to a lower dimensional component space. This idea is encapsulated by the projector
class and the project
function. Support for two-way mapping (row projection and column projection) is provided by the derived class bi-projector
. Generic functions for common operations are included:
project
for mapping from input space into (usually) reduced-dimensional output spacepartial_project
for mapping a subset of input space into output spaceproject_vars
for mapping new variables ("supplementary variables") to output spacereconstruct
for reconstructing input data from its low-dimensional representationresiduals
for extracting residuals of a fit with n
components.You can install the development version from GitHub with:
# install.packages("devtools") devtools::install_github("bbuchsbaum/multivarious")
This is a basic example which shows you how to solve a common problem:
library(multivarious) ## basic example code
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