Given the growing number of available tools for modeling dynamic networks, the choice of a suitable model becomes central. The goal of this survey is to provide an overview of tie‐oriented dynamic network models. The survey is focused on introducing binary network models with their corresponding assumptions, advantages, and shortfalls. The models are divided according to generating processes, operating in discrete and continuous time. First, we introduce the temporal exponential random graph model (TERGM) and the separable TERGM (STERGM), both being time‐discrete models. These models are then contrasted with continuous process models, focusing on the relational event model (REM). We additionally show how the REM can handle time‐clustered ob...
We propose a family of statistical models for social network evolution over time, which represents a...
This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such ...
We propose a family of statistical models for social network evolution over time, which represents a...
Given the growing number of available tools for modeling dynamic networks, the choice of a suitable ...
Given the growing number of available tools for modeling dynamic networks, the choice of a suitable ...
Given the growing number of available tools for modeling dynamic networks, the choice of a suitable ...
Given the growing number of available tools for modeling dynamic networks, the choice of a suitable ...
Models of dynamic networks - networks that evolve over time - have manifold applications. We develop...
Models of dynamic networks - networks that evolve over time - have manifold applications. We develop...
Models of dynamic networks - networks that evolve over time - have manifold applications. We develop...
Models of dynamic networks — networks that evolve over time — have manifold applications. We develop...
Networks encode relational structures between entities that do not generally abide by the conditiona...
<div><p>There has been a great deal of interest recently in the modeling and simulation of dynamic n...
Autoregressive and moving average models for temporally dynamic networks treat time as a series of d...
The Exponential-family Random Graph Model (ERGM) is a powerful statistical model to represent the co...
We propose a family of statistical models for social network evolution over time, which represents a...
This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such ...
We propose a family of statistical models for social network evolution over time, which represents a...
Given the growing number of available tools for modeling dynamic networks, the choice of a suitable ...
Given the growing number of available tools for modeling dynamic networks, the choice of a suitable ...
Given the growing number of available tools for modeling dynamic networks, the choice of a suitable ...
Given the growing number of available tools for modeling dynamic networks, the choice of a suitable ...
Models of dynamic networks - networks that evolve over time - have manifold applications. We develop...
Models of dynamic networks - networks that evolve over time - have manifold applications. We develop...
Models of dynamic networks - networks that evolve over time - have manifold applications. We develop...
Models of dynamic networks — networks that evolve over time — have manifold applications. We develop...
Networks encode relational structures between entities that do not generally abide by the conditiona...
<div><p>There has been a great deal of interest recently in the modeling and simulation of dynamic n...
Autoregressive and moving average models for temporally dynamic networks treat time as a series of d...
The Exponential-family Random Graph Model (ERGM) is a powerful statistical model to represent the co...
We propose a family of statistical models for social network evolution over time, which represents a...
This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such ...
We propose a family of statistical models for social network evolution over time, which represents a...