beta_ols

Computes OLS coefficients using <code>.lm.fit</code> for computational efficiency.
If <code>Y</code> is a matrix, applies OLS column-wise.

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

beta_ols function

<dl><dt>X</dt>
<dd>A numeric matrix of regressors (T × k).</dd>
<dt>Y</dt>
<dd>A numeric matrix or vector of responses (T × N or T × 1).</dd></dl>

Arguments

Efficient OLS Estimation — beta_ols

<dl>

<dt>X</dt>
<dd>A numeric matrix of regressors (T × k).</dd>


<dt>Y</dt>
<dd>A numeric matrix or vector of responses (T × N or T × 1).</dd>

</dl>

beta_ols: Efficient OLS Estimation

Description

Usage

Value

Arguments