single_block

Estimates a Dynamic Factor Model (DFM) when only one block is present, using Principal Component Analysis (PCA).

internal

Provides a comprehensive framework in R for modeling and forecasting economic scenarios based on multi-level dynamic factor model. The package enables users to: (i) extract global and group-specific factors using a flexible multi-level factor structure; (ii) compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings; (iii) obtain estimates of the parameters of the factor-augmented quantile regressions together with their standard deviations; (iv) recover full predictive conditional densities from estimated quantiles; (v) obtain risk measures based on extreme quantiles of the conditional densities; (vi) estimate the conditional density and the corresponding extreme quantiles when the factors are stressed.

Gian Pietro Bellocca

FARS

Factor-Augmented Regression Scenarios

Ignacio Garrón

Vladimir Rodríguez-Caballero

Esther Ruiz

single_block function

<dl><dt>data</dt>
<dd>A numeric matrix or data frame containing the time series data (T × N).</dd>
<dt>r</dt>
<dd>Integer. Number of factors to extract.</dd></dl>

Arguments

Multi-Level Dynamic Factor Model  - Single Block (DFM) — single_block

<dl>

<dt>data</dt>
<dd>A numeric matrix or data frame containing the time series data (T × N).</dd>


<dt>r</dt>
<dd>Integer. Number of factors to extract.</dd>

</dl>

single_block: Multi-Level Dynamic Factor Model - Single Block (DFM)

Description

Usage

Value

Arguments