title: R-Package or Code for logitudinal ERGM (LERGM) with continuous time treatment
body: <p>I am working on a comparison of analysis methods for longitudinal network data. I want to compare an ERGM-based method to Stochastic Actor Oriented Models (SAOM). The key difference I am interesed in is how the results differ using a tie-centered approach versus an actor-centered apporoach.
  So far I have used the TERGM model, which is provided in an R-Package. But TERGM treats data discrete meaning the dataset a t-1 is simply used as an additional tie-kovariate at time t, whereas SAOM simulates microsteps to model time continuously.
  In a book chapter (for citation see bottom) I read about LERGM (as it is reffered to not by the authors but by other authors who mention the approach), that is also an ERGM-family method, meaning it is tie-centered but it treats time continuously like SAOM.</p>
  <p><strong>Did anybody ever work with continuous-time LERGM and could give me a hint if there is some R-package or code available I could apply to may data?
  Any hint is appreciated!</strong></p>
  <p><em>Snijders, Tom A.B. und Johan Koskinen (2013). „Longitudinal Models“. In: Exponential random graph models for social networks: Theory, methods, and applications. Eds.: Dean Lusher, Johan Koskinen und Garry Robins. Cambridge: CambridgeUniversity Press. Chapter 11, pp. 130–140.</em></p>