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• W2018120626 abstract "Researchers in social networks are becoming increasingly interested in how networks evolve over time. There are theories that bear on the evolution of networks, but virtually no statistical methodology which supports the comparative evaluation of these theories. In this paper, we present explicit probability models for networks that change over time, covering a range of simple but significant qualitative behavior. Maximum likelihood estimates of model parameters which describe the rate of change of the network are derived, and some of their sampling properties are elucidated. To calculate these estimates the researcher must have measurements upon the trajectory of a network — these are the values of the network at successive time points. We also describe goodness-of-fit tests for assessing model adequacy, and use Newcomb's dataset to illustrate the methodology." @default.
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• W2018120626 date "1995-01-01" @default.
• W2018120626 modified "2023-10-12" @default.
• W2018120626 title "Models for evolving fixed node networks: Model fitting and model testing" @default.
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• W2018120626 doi "https://doi.org/10.1016/0378-8733(94)00249-a" @default.
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