generatePPConst

Generates one realization of a Poisson process (PP) with a piecewise constant intensity function.

Stochastic block model used for dynamic graphs represented by Poisson processes.
To model recurrent interaction events in continuous time, an extension of the stochastic block model is proposed where every individual belongs to a latent group and interactions between two individuals follow a conditional inhomogeneous Poisson process with intensity driven by the individuals’ latent groups. The model is shown to be identifiable and its estimation is based on a semiparametric variational expectation-maximization algorithm. Two versions of the method are developed, using either a nonparametric histogram approach (with an adaptive choice of the partition size) or kernel intensity estimators. The number of latent groups can be selected by an integrated classification likelihood criterion.
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Daphnc3<a9> Giorgi

ppsbm

Clustering in Longitudinal Networks

Daphné Giorgi

Catherine Matias

Tabea Rebafka

Fanny Villers

generatePPConst function

<dl><dt>intens</dt>
<dd>Vector with the constant values of the intensity, defined on a regular partition of the time interval [0,Time].</dd>
<dt>Time</dt>
<dd>Positive real number. [0,Time] is the total time interval of observation.</dd></dl>

Arguments

Poisson process with piecewise constant intensity — generatePPConst

<dl>

<dt>intens</dt>
<dd>Vector with the constant values of the intensity, defined on a regular partition of the time interval [0,Time].</dd>


<dt>Time</dt>
<dd>Positive real number. [0,Time] is the total time interval of observation.</dd>

</dl>

generatePPConst: Poisson process with piecewise constant intensity

Description

Usage

Arguments

Examples