Sentence examples for contagion models from inspiring English sources
The obtained form differs from that arising under the proneness and contagion models.
Most attempts seem to have been concentrated on distinguishing between the proneness and contagion models generating the negative binomial distribution.
However, the first systematic study on how one can discriminate between the proneness and contagion models of the negative binomial distribution appears to be that by Cane ([1974]).
This implies that the availability of information on the times of the occurrence of accidents is not sufficient to guide one's choice between the proneness and contagion models.
This extension has already been addressed for contagion models with heterogenous agents and homophily providing fruitful results (e.g., Jackson and López-Pintado 2013).
Our results concur with evidence from other interbank markets and other financial networks regarding the flaws of traditional direct financial contagion models based on homogeneous and non-hierarchical networks.
This framework is the classical contagion model (Greenwood and Yule [1920]; Xekalaki [1983a]).
We describe the default model in "Default contagion model" section and the market model in "The market model" section.
Xekalaki ([1983a]), extended the assumptions of the classical contagion model developed by Greenwood and Yule ([1920]) by considering a population of individuals exposed to varying accident risk.
The predictive model created by Papachristos combines demographic data with what is called a 'social contagion' model in which it is assumed that individuals who are socially connected a victim of gun violence will themselves run a higher risk of becoming victims of gun violence.
When Papachristos combines this social contagion model with the traditional demographic approach, the predictive strength of this method rises above 70percentt; in other words, seven out of ten of the individuals who were later subjects of gun violence could be identified before the actual gun violence event took place.
