A Biparametric Approach to Network Autocorrelation

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Abstract
In anthropology, “Galton's Problem” is generally taken to refer to the interdependence of cases in a cross-cultural sample due to various processes of cultural diffusion. Previous attempts to deal with this problem have usually assumed that these types of interdependencies can be characterized adequately in terms of spatial proximity and/or common linguistic history. In regression analysis using such interdependent data, autocorrelation among the error terms can be incorporated into the model by means of a network relational or connectivity matrix, W. The biparametric model is a straightforward generalization that specifies two autocorrelation parameters associated with two network relational matrices. Simultaneous autocorrelation effects for language similarity and geographical distance matrices are empirically demonstrated using cross-cultural data on the sexual division of labor. An alternative to the maximum likelihood approach to estimation of both autocorrelation parameters is suggested and employed.

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