Additive and Multiplicative Effects Models for Networks and Relational Data
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AME model fitting routine
AME model fitting routine for replicated relational data
Additive and Multiplicative Effects Models for Networks and Relational...
Circular network plot
Computes the design socioarray of covariate values
Edgelist to sociomatrix
Goodness of fit statistics
log density for GBME models
SRM log likelihood evaluated on a grid of rho-values
Symmetric square root of a matrix
Network plotting
Plot results of an AME object
Precomputation of design matrix quantities.
Simulate a and Sab from full conditional distributions under bin likel...
Simulate a and Sab from full conditional distributions under the cbin ...
Simulate a and Sab from full conditional distributions under frn likel...
Conditional simulation of additive effects and regression coefficients
Gibbs sampling of additive row and column effects and regression coeff...
Simulation from a multivariate normal distribution
Griddy Gibbs update for dyadic correlation
Metropolis update for dyadic correlation
Metropolis update for dyadic correlation with independent replicate da...
Gibbs update for dyadic variance
Gibbs update for dyadic variance with independent replicate relational...
Gibbs update for additive effects covariance
Gibbs update for multiplicative effects covariance
Gibbs sampling of U and V
Gibbs sampling of U and V
Gibbs sampling of U and V
Simulation from a Wishart distribution
Simulate Z based on a probit model
Simulate Z given fixed rank nomination data
Simulate Z given fixed rank nomination data
Simulate missing values in a normal AME model
Simulate Z given the partial ranks
Simulate Z given relative rank nomination data
Simulate Z based on a tobit model
Simulate a network, i.e. a binary relational matrix
Simulate an relational matrix based on a fixed rank nomination scheme
Simulate a normal relational matrix
Simulate an ordinal relational matrix
Simulate an relational matrix based on a relative rank nomination sche...
Simulate a tobit relational matrix
Simulate Z given its expectation and covariance
Sociomatrix to edgelist
Summary of an AME object
Linear combinations of submatrices of an array
Network embedding
rank-based z-scores
Analysis of dyadic network and relational data using additive and multiplicative effects (AME) models. The basic model includes regression terms, the covariance structure of the social relations model (Warner, Kenny and Stoto (1979) <DOI:10.1037/0022-3514.37.10.1742>, Wong (1982) <DOI:10.2307/2287296>), and multiplicative factor models (Hoff(2009) <DOI:10.1007/s10588-008-9040-4>). Several different link functions accommodate different relational data structures, including binary/network data, normal relational data, zero-inflated positive outcomes using a tobit model, ordinal relational data and data from fixed-rank nomination schemes. Several of these link functions are discussed in Hoff, Fosdick, Volfovsky and Stovel (2013) <DOI:10.1017/nws.2013.17>. Development of this software was supported in part by NIH grant R01HD067509.