make_cumulative_Lambda_matrix

Helper function for the vectorized versions of sampling functions.
Takes the usual ways that <code>lambda_mat</code> and <code>Lambda_mat</code> are specified
and returns <code>Lambda_mat</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

make_cumulative_Lambda_matrix function

<dl><dt>Lambda_mat</dt>
<dd>a matrix of cumulative intensities or missing</dd>
<dt>lambda_mat</dt>
<dd>a matrix of intensities or missing</dd>
<dt>interval_duration</dt>
<dd>a vector with the same number of elements as the rows of <code>Lambda_mat</code></dd></dl>

Arguments

Helper function for the vectorized versions of sampling functions.
Takes the usual ways that lambda_mat and Lambda_mat are specified
and returns Lambda_mat. — make_cumulative_Lambda_matrix

<dl>

<dt>Lambda_mat</dt>
<dd>a matrix of cumulative intensities or missing</dd>


<dt>lambda_mat</dt>
<dd>a matrix of intensities or missing</dd>


<dt>interval_duration</dt>
<dd>a vector with the same number of elements as the rows of <code>Lambda_mat</code></dd>

</dl>

Helper function for the vectorized versions of sampling functions.
Takes the usual ways that <code>lambda_mat</code> and <code>Lambda_mat</code> are specified
and returns <code>Lambda_mat</code>.

make_cumulative_Lambda_matrix: Helper function for the vectorized versions of sampling functions. Takes the usual ways that `lambda_mat` and `Lambda_mat` are specified and returns `Lambda_mat`.

Description

Usage

Value

Arguments