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IR90s
|
International relations in the 90s |
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Xbeta()
|
Linear combinations of submatrices of an array |
|
YX_bin
|
binary relational data and covariates |
|
YX_bin_long
|
binary relational data and covariates |
|
YX_cbin
|
Censored binary nomination data and covariates |
|
YX_frn
|
Fixed rank nomination data and covariates |
|
YX_nrm
|
normal relational data and covariates |
|
YX_ord
|
ordinal relational data and covariates |
|
YX_rrl
|
row-specific ordinal relational data and covariates |
|
addhealthc3
|
AddHealth community 3 data |
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addhealthc9
|
AddHealth community 9 data |
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addlines()
|
Add lines |
|
ame()
|
AME model fitting routine |
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ame_rep()
|
AME model fitting routine for replicated relational data |
|
amen-package
|
Additive and Multiplicative Effects Models for Networks and Relational Data |
|
circplot()
|
Circular network plot |
|
coldwar
|
Cold War data |
|
comtrade
|
Comtrade data |
|
design_array()
|
Computes the design socioarray of covariate values |
|
dutchcollege
|
Dutch college data |
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el2sm()
|
Edgelist to sociomatrix |
|
gofstats()
|
Goodness of fit statistics |
|
lazegalaw
|
Lazega's law firm data |
|
ldZgbme()
|
log density for GBME models |
|
llsrmRho()
|
SRM log likelihood evaluated on a grid of rho-values |
|
mhalf()
|
Symmetric square root of a matrix |
|
netplot()
|
Network plotting |
|
plot(<ame>)
|
Plot results of an AME object |
|
precomputeX()
|
Precomputation of design matrix quantities. |
|
rSab_fc()
|
Gibbs update for additive effects covariance |
|
rSuv_fc()
|
Gibbs update for multiplicative effects covariance |
|
rUV_fc()
|
Gibbs sampling of U and V |
|
rUV_rep_fc()
|
Gibbs sampling of U and V |
|
rUV_sym_fc()
|
Gibbs sampling of U and V |
|
rZ_bin_fc()
|
Simulate Z based on a probit model |
|
rZ_cbin_fc()
|
Simulate Z given fixed rank nomination data |
|
rZ_frn_fc()
|
Simulate Z given fixed rank nomination data |
|
rZ_nrm_fc()
|
Simulate missing values in a normal AME model |
|
rZ_ord_fc()
|
Simulate Z given the partial ranks |
|
rZ_rrl_fc()
|
Simulate Z given relative rank nomination data |
|
rZ_tob_fc()
|
Simulate Z based on a tobit model |
|
raSab_bin_fc()
|
Simulate a and Sab from full conditional distributions under bin likelihood |
|
raSab_cbin_fc()
|
Simulate a and Sab from full conditional distributions under the cbin
likelihood |
|
raSab_frn_fc()
|
Simulate a and Sab from full conditional distributions under frn likelihood |
|
rbeta_ab_fc()
|
Conditional simulation of additive effects and regression coefficients |
|
rbeta_ab_rep_fc()
|
Gibbs sampling of additive row and column effects and regression coefficient
with independent replicate relational data |
|
rmvnorm()
|
Simulation from a multivariate normal distribution |
|
rrho_fc()
|
Griddy Gibbs update for dyadic correlation |
|
rrho_mh()
|
Metropolis update for dyadic correlation |
|
rrho_mh_rep()
|
Metropolis update for dyadic correlation with independent replicate data |
|
rs2_fc()
|
Gibbs update for dyadic variance |
|
rs2_rep_fc()
|
Gibbs update for dyadic variance with independent replicate relational data |
|
rwish()
|
Simulation from a Wishart distribution |
|
sampsonmonks
|
Sampson's monastery data |
|
sheep
|
Sheep dominance data |
|
simY_bin()
|
Simulate a network, i.e. a binary relational matrix |
|
simY_frn()
|
Simulate an relational matrix based on a fixed rank nomination scheme |
|
simY_nrm()
|
Simulate a normal relational matrix |
|
simY_ord()
|
Simulate an ordinal relational matrix |
|
simY_rrl()
|
Simulate an relational matrix based on a relative rank nomination scheme |
|
simY_tob()
|
Simulate a tobit relational matrix |
|
simZ()
|
Simulate Z given its expectation and covariance |
|
sm2el()
|
Sociomatrix to edgelist |
|
summary(<ame>)
|
Summary of an AME object |
|
xnet()
|
Network embedding |
|
zscores()
|
rank-based z-scores |