rng_stream_rztpois

Sample from <code>rstream</code> objects

internal

Simulates events from one dimensional nonhomogeneous Poisson point processes (NHPPPs) as per Trikalinos and Sereda (2024, <doi:10.48550/arXiv.2402.00358> and 2024, <doi:10.1371/journal.pone.0311311>). Functions are based on three algorithms that provably sample from a target NHPPP: the time-transformation of a homogeneous Poisson process (of intensity one) via the inverse of the integrated intensity function (Cinlar E, "Theory of stochastic processes" (1975, ISBN:0486497996)); the generation of a Poisson number of order statistics from a fixed density function; and the thinning of a majorizing NHPPP via an acceptance-rejection scheme (Lewis PAW, Shedler, GS (1979) <doi:10.1002/nav.3800260304>).

Thomas Trikalinos

nhppp

Simulating Nonhomogeneous Poisson Point Processes

Yuliia Sereda

rng_stream_rztpois function

<dl><dt>size</dt>
<dd>Integer, number of samples</dd>
<dt>lambda</dt>
<dd>Positive number, the mean of the original
(untruncated) Poisson distribution</dd>
<dt>rng_stream</dt>
<dd>(<code>rstream</code>) an <code>rstream</code> object or <code>NULL</code></dd></dl>

Arguments

Zero-truncated Poisson random samples from rstream objects — rng_stream_rztpois

<dl>

<dt>size</dt>
<dd>Integer, number of samples</dd>


<dt>lambda</dt>
<dd>Positive number, the mean of the original
(untruncated) Poisson distribution</dd>


<dt>rng_stream</dt>
<dd>(<code>rstream</code>) an <code>rstream</code> object or <code>NULL</code></dd>

</dl>

rng_stream_rztpois: Zero-truncated Poisson random samples from `rstream` objects

Description

Usage

Value

Arguments

Examples