mldfm: Estimate Multilevel Dynamic Factor Model

In FARS: Factor-Augmented Regression Scenarios

Estimate Multilevel Dynamic Factor Model

Description

Estimates a multilevel dynamic factor model from time series data. Supports both single-block and hierarchical multi-block structures with customizable factor extraction settings.

Usage

mldfm(
  data,
  blocks = 1,
  block_ind = NULL,
  global = 1,
  local = NULL,
  middle_layer = NULL,
  method = 0,
  tol = 1e-06,
  max_iter = 1000,
  verbose = TRUE
)

Arguments

data	A numeric matrix or data frame containing the time series data. Rows represent time points; columns represent observed variables.
blocks	Integer. Number of blocks into which the data is divided.
block_ind	Integer vector. End column indices for each block. Must be of length blocks and in increasing order.
global	Integer. Number of global factors extracted from the entire dataset.
local	Integer vector of length blocks. Specifies the number of local factors for each block.
middle_layer	Named list. Each name is a string specifying a group of blocks (e.g., "1-3" or "2-3"), and each value is the number of factors to extract.
method	Integer. Method used to initialize the factors: 0 for Canonical Correlation Analysis (CCA), 1 for Principal Component Analysis (PCA).
tol	Numeric. The tolerance level for the residual sum of squares (RSS) minimization process. Used as a convergence criterion.
max_iter	Integer. The maximum number of iterations allowed for the RSS minimization process.
verbose	Logical. If TRUE (default), print a summary of the mldfm.

Value

An object of class mldfm, which is a list containing the following components:

Factors

Matrix of estimated factors.

Lambda

Matrix of factor loadings.

Residuals

Matrix of residuals.

Iterations

Number of iterations before convergence.

Factors_list

List of estimated factors for each node.

Examples

data <- matrix(rnorm(1000), nrow = 100, ncol = 519)
block_ind <- c(63, 311, 519)  # Defines 3 blocks
local <- c(1, 1, 1)           # One local factor per block
middle_layer <- list("1-3" = 1)
result <- mldfm(data, blocks = 3, block_ind = block_ind, global = 1, 
local = local, middle_layer = middle_layer)
summary(result)

FARS documentation built on Aug. 8, 2025, 7:33 p.m.