vcov.normal

Retrieve the variance-covariance matrix (or scalar)
of a <code>normal</code> object.

Provides an algebra over probability distributions enabling
composition, sampling, and automatic simplification to closed forms.
Supports normal, exponential, gamma, Weibull, chi-squared, uniform,
beta, log-normal, Poisson, multivariate normal, empirical, and mixture
distributions with algebraic operators (addition, subtraction,
multiplication, division, power, exp, log, min, max) that automatically
simplify when mathematical identities apply. Includes closed-form MVN
conditioning (Schur complement), affine transformations, mixture
marginals/conditionals (Bayes rule), and limiting distribution builders
(CLT, LLN, delta method). Uses S3 classes for distributions and R6
for support objects.

Alexander Towell

algebraic.dist

Algebra over Probability Distributions

vcov.normal function

<dl><dt>object</dt>
<dd>The <code>normal</code> object to retrieve the variance-covariance matrix from</dd>
<dt>...</dt>
<dd>Additional arguments to pass (not used)</dd></dl>

Arguments

Retrieve the variance-covariance matrix (or scalar)
of a normal object. — vcov.normal

<dl>

<dt>object</dt>
<dd>The <code>normal</code> object to retrieve the variance-covariance matrix from</dd>


<dt>...</dt>
<dd>Additional arguments to pass (not used)</dd>

</dl>

vcov.normal: Retrieve the variance-covariance matrix (or scalar) of a `normal` object.

Description

Usage

Value

Arguments

Examples