mat_diff_columns

Return matrix with column-wise differencing.
No checks for arguments is done.

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

mat_diff_columns function

<dl><dt>X</dt>
<dd>(matrix)</dd></dl>

Arguments

Return matrix with column-wise differencing.
No checks for arguments is done. — mat_diff_columns

<dl>

<dt>X</dt>
<dd>(matrix)</dd>

</dl>

mat_diff_columns: Return matrix with column-wise differencing. No checks for arguments is done.

Description

Usage

Value

Arguments