ena.svd: ENA SVD

In rENA: Epistemic Network Analysis

ENA SVD

Description

Computes a dimensional reduction of points in an ENA set using Singular Value Decomposition (SVD).

Usage

ena.svd(enaset, params)

Arguments

enaset	An ENAset object containing the points to be reduced.
params	A list of parameters. Use params$as_object = TRUE to return an ENARotationSet object, or FALSE (default) to return a list.

Details

This function computes the SVD of the points in the ENA set and returns either an ENARotationSet object or a list with the rotation matrix, codes, node positions, and eigenvalues, depending on params$as_object.

Value

An ENARotationSet object or a list containing:

rotation	The rotation matrix from SVD
codes	The code names used for the matrix
node.positions	(Currently NULL) Node positions
eigenvalues	The eigenvalues (squared singular values) from SVD

Examples

data(RS.data)
codes <- c("Data", "Technical.Constraints", "Performance.Parameters",
           "Client.and.Consultant.Requests", "Design.Reasoning",
           "Collaboration")
units <- c("Condition", "UserName")
horizon <- c("Condition", "GroupName")
enaset <- RS.data |>
  accumulate(units, codes, horizon) |>
  model()
# SVD as list:
svd_result <- ena.svd(enaset, list(as_object = FALSE))
# SVD as ENARotationSet object:
svd_obj <- ena.svd(enaset, list(as_object = TRUE))

rENA documentation built on Nov. 5, 2025, 5:50 p.m.