discretize_gamma

The serial interval distribution expresses the probability of the
symptom onset of a secondary infection occurred a given number of days after
the primary infection. The serial interval distribution is commonly
represented by a discretized Gamma distribution in literature, parametrized
by the shape and scale parameters.

Use trend filtering, a type of regularized nonparametric
regression, to estimate the instantaneous reproduction number, also
called Rt. This value roughly says how many new infections will result
from each new infection today. Values larger than 1 indicate that an
epidemic is growing while those less than 1 indicate decline. For more
details about this methodology, see Liu, Cai, Gustafson, and McDonald (2024)
<doi:10.1371/journal.pcbi.1012324>.

Daniel McDonald

rtestim

Estimate the Effective Reproductive Number with Trend Filtering

Daniel J. McDonald

Jiaping Liu

Zhenglun Cai

discretize_gamma function

<dl><dt>x</dt>
<dd>locations (times) where cases are observed. Must be nonnegative.</dd>
<dt>shape, scale</dt>
<dd>shape and scale parameters. Must be positive,
 <code>scale</code> strictly.</dd>
<dt>rate</dt>
<dd>an alternative way to specify the scale.</dd></dl>

Arguments

Compute the discretized density function for gamma distribution — discretize_gamma

<dl>

<dt>x</dt>
<dd>locations (times) where cases are observed. Must be nonnegative.</dd>


<dt>shape, scale</dt>
<dd>shape and scale parameters. Must be positive,
 <code>scale</code> strictly.</dd>


<dt>rate</dt>
<dd>an alternative way to specify the scale.</dd>

</dl>

discretize_gamma: Compute the discretized density function for gamma distribution

Description

Usage

Value

Arguments

Examples