z_scale

Compute rank normalization for a numeric array. First replace each
value by its rank. Average rank for ties are used to conserve the
number of unique values of discrete quantities. Second, normalize
ranks via the inverse normal transformation.

internal

Provides useful tools for both users and developers of packages
for fitting Bayesian models or working with output from Bayesian models.
The primary goals of the package are to:
(a) Efficiently convert between many different useful formats of
draws (samples) from posterior or prior distributions.
(b) Provide consistent methods for operations commonly performed on draws,
for example, subsetting, binding, or mutating draws.
(c) Provide various summaries of draws in convenient formats.
(d) Provide lightweight implementations of state of the art posterior
inference diagnostics. References: Vehtari et al. (2021)
<doi:10.1214/20-BA1221>.

PaulChristian Buerkner

posterior

Tools for Working with Posterior Distributions

Paul-Christian Bürkner

Jonah Gabry

Matthew Kay

Aki Vehtari

Måns Magnusson

Rok Češnovar

Ben Lambert

Ozan Adıgüzel

Jacob Socolar

Noa Kallioinen

z_scale function

<dl><dt>x</dt>
<dd>(numeric) A scalar, vector, matrix, or array of values.</dd>
<dt>c</dt>
<dd>(numeric) Fractional offset used in the back-transformation of ranks.
Defaults to <code>3/8</code>.</dd></dl>

Arguments

Rank normalization — z_scale

<dl>

<dt>x</dt>
<dd>(numeric) A scalar, vector, matrix, or array of values.</dd>


<dt>c</dt>
<dd>(numeric) Fractional offset used in the back-transformation of ranks.
Defaults to <code>3/8</code>.</dd>

</dl>

Rank normalization

z_scale: Rank normalization

Description

Usage

Value

Arguments