mean.mixture

The mean of a mixture is the weighted sum of the component means:
\(E[X] = \sum_k w_k \mu_k\).

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

mean.mixture function

<dl><dt>x</dt>
<dd>A <code>mixture</code> object.</dd>
<dt>...</dt>
<dd>Additional arguments (not used).</dd></dl>

Arguments

Mean of a mixture distribution. — mean.mixture

<dl>

<dt>x</dt>
<dd>A <code>mixture</code> object.</dd>


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

</dl>

mean.mixture: Mean of a mixture distribution.

Description

Usage

Value

Arguments

Examples