compute_initial_factors: Compute Initial Factors for Multi-Level Dynamic Factor Model

In FARS: Factor-Augmented Regression Scenarios

Compute Initial Factors for Multi-Level Dynamic Factor Model

Description

Computes the initial set of global, middle-layer, and local factors using either PCA or CCA.

Usage

compute_initial_factors(
  data,
  num_vars,
  num_obs,
  num_blocks,
  ranges,
  r_list,
  method
)

Arguments

data	A numeric matrix or data frame containing the time series data (T × N).
num_vars	Integer vector. Number of variables in each block.
num_obs	Integer. Number of time observations (T).
num_blocks	Integer. Number of blocks.
ranges	A list of vectors with the column indices for each block.
r_list	A named list specifying the number of factors to extract for each node (from build_factor_structure).
method	Integer. Method for factor extraction: 0 = Canonical Correlation Analysis (CCA), 1 = Principal Component Analysis (PCA).

Value

A list with two elements:

initial_factors

Matrix of all initial factors (T × total number of factors).

factor_list

Named list of factors for each node in the hierarchy.

FARS documentation built on Feb. 17, 2026, 5:06 p.m.