Lambda_exp_form

Definite integral of <code>l = exp(intercept + slope*t)</code> starting at
<code>t0</code> -- only for <code>l+</code>.

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

Lambda_exp_form function

<dl><dt>t</dt>
<dd>(double) the time point</dd>
<dt>intercept</dt>
<dd>(double) the intercept</dd>
<dt>slope</dt>
<dd>(double) the slope</dd>
<dt>t0</dt>
<dd>(double) the starting time</dd></dl>

Arguments

Definite integral of l = exp(intercept + slope*t) at time t
with L(t0) = 0 — Lambda_exp_form

<dl>

<dt>t</dt>
<dd>(double) the time point</dd>


<dt>intercept</dt>
<dd>(double) the intercept</dd>


<dt>slope</dt>
<dd>(double) the slope</dd>


<dt>t0</dt>
<dd>(double) the starting time</dd>

</dl>

Lambda_exp_form: Definite integral of `l = exp(intercept + slope*t)` at time `t` with `L(t0) = 0`

Description

Usage

Arguments