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amen (version 1.1)

Additive and Multiplicative Effects Models for Networks and Relational Data

Description

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), Wong (1982)), and multiplicative factor models (Hoff(2009)). Four different link functions accommodate different relational data structures, including binary/network data (bin), normal relational data (nrm), ordinal relational data (ord) and data from fixed-rank nomination schemes (frn). Several of these link functions are discussed in Hoff, Fosdick, Volfovsky and Stovel (2013). Development of this software was supported in part by NIH grant R01HD067509.

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Version

Install

install.packages('amen')

Monthly Downloads

348

Version

1.1

License

GPL-3

Maintainer

Peter D Hoff

Last Published

June 26th, 2015

Functions in amen (1.1)

dutchcollege

Dutch college data
mhalf

Symmetric square root of a matrix
YX_ord

ordinal relational data and covariates
lazegalaw

Lazega's law firm data
rUV_sym_fc

Gibbs sampling of U and V
rbeta_ab_rep_fc

Gibbs sampling of additive row and column effects and regression coefficient
rs2_fc

Gibbs update for dyadic variance
simZ

Simulate Z given its expectation and covariance
rrho_mh

Metropolis update for dyadic correlation
IR90s

International relations in the 90s
rs2_rep_fc

Gibbs update for dyadic variance with independent replicate relational data
sampsonmonks

Sampson's monastery data
rZ_frn_fc

Simulate Z given fixed rank nomination data
rZ_nrm_fc

Simulate missing values in a normal AME model
zscores

rank-based z-scores
netplot

Network plotting
summary.ame

Summary of an AME object
rbeta_ab_fc

Gibbs sampling of additive row and column effects and regression coefficient
xnet

Network embedding
raSab_cbin_fc

Simulate a and Sab from full conditional distributions under the cbin
sheep

Sheep dominance data
YX_nrm

normal relational data and covariates
ame_rep

AME model fitting routine for replicated relational data
plot.ame

Plot results of an AME object
YX_cbin

Censored binary nomination data and covariates
raSab_bin_fc

Simulate a and Sab from full conditional distributions under bin likelihood
design_array

Computes the design socioarray of covariate values
circplot

Circular network plot
rZ_rrl_fc

Simulate Z given relative rank nomination data
rwish

Simulation from a Wishart distribution
YX_frn

Fixed rank nomination data and covariates
comtrade

Comtrade data
YX_rrl

row-specific ordinal relational data and covariates
simY_frn

Simulate an relational matrix based on a fixed rank nomination scheme
rUV_fc

Gibbs sampling of U and V
simY_bin

Simulate a network, i.e. a binary relational matrix
addhealthc3

AddHealth community 3 data
rUV_rep_fc

Gibbs sampling of U and V
sm2el

Sociomatrix to edgelist
Xbeta

Linear combinations of submatrices of an array
YX_bin

binary relational data and covariates
rZ_bin_fc

Simulate Z based on a probit model
simY_ord

Simulate an ordinal relational matrix
simY_rrl

Simulate an relational matrix based on a relative rank nomination scheme
rmvnorm

Simulation from a multivariate normal distribution
gofstats

Goodness of fit statistics
el2sm

Edgelist to sociomatrix
coldwar

Cold War data
rZ_ord_fc

Simulate Z given the partial ranks
ame

AME model fitting routine
amen-package

Additive and Multiplicative Effects Models for Networks and Relational Data
raSab_frn_fc

Simulate a and Sab from full conditional distributions under frn likelihood
rrho_mh_rep

Metropolis update for dyadic correlation with independent replicate data
addhealthc9

AddHealth community 9 data
rZ_cbin_fc

Simulate Z given fixed rank nomination data
YX_bin_long

binary relational data and covariates
addlines

Add lines
simY_nrm

Simulate a normal relational matrix