compute_initial_factors

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

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

compute_initial_factors function

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

Arguments

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

<dl>

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


<dt>num_vars</dt>
<dd>Integer vector. Number of variables in each block.</dd>


<dt>num_obs</dt>
<dd>Integer. Number of time observations (T).</dd>


<dt>num_blocks</dt>
<dd>Integer. Number of blocks.</dd>


<dt>ranges</dt>
<dd>A list of vectors with the column indices for each block.</dd>


<dt>r_list</dt>
<dd>A named list specifying the number of factors to extract for each node (from <code>build_factor_structure</code>).</dd>


<dt>method</dt>
<dd>Integer. Method for factor extraction: <code>0</code> = Canonical Correlation Analysis (CCA), <code>1</code> = Principal Component Analysis (PCA).</dd>

</dl>

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

Description

Usage

Value

Arguments