Retrieve the observations used to construct a distribution-like object. This is
useful for obtaining the data used to construct an empirical distribution, but
it is also useful for, say, retrieving the sample that was used by a fitted
object, like an maximum likelihood estimate.

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

obs function

<dl><dt>x</dt>
<dd>the object to retrieve the observations from</dd></dl>

Arguments

Retrieve the observations used to construct a distribution-like object. This is
useful for obtaining the data used to construct an empirical distribution, but
it is also useful for, say, retrieving the sample that was used by a fitted
object, like an maximum likelihood estimate. — obs

<dl>

<dt>x</dt>
<dd>the object to retrieve the observations from</dd>

</dl>

Retrieve the observations used to construct a distribution-like object. This is
useful for obtaining the data used to construct an empirical distribution, but
it is also useful for, say, retrieving the sample that was used by a fitted
object, like an maximum likelihood estimate.

obs: Retrieve the observations used to construct a distribution-like object. This is useful for obtaining the data used to construct an empirical distribution, but it is also useful for, say, retrieving the sample that was used by a fitted object, like an maximum likelihood estimate.

Description

Usage

Value

Arguments

Examples