marginal

Generic method for obtaining the marginal distribution of a distribution
object <code>x</code> over components <code>indices</code>.

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

marginal function

<dl><dt>x</dt>
<dd>The distribution object.</dd>
<dt>indices</dt>
<dd>The indices of the marginal distribution to obtain.</dd></dl>

Arguments

Generic method for obtaining the marginal distribution of a distribution
object x over components indices. — marginal

<dl>

<dt>x</dt>
<dd>The distribution object.</dd>


<dt>indices</dt>
<dd>The indices of the marginal distribution to obtain.</dd>

</dl>

marginal: Generic method for obtaining the marginal distribution of a distribution object `x` over components `indices`.

Description

Usage

Value

Arguments

Examples