Longitudinal Additive and Multiplicative Effects Models for Networks

Documentation for package ‘lame’ version 1.3.4

Help Pages

-- A --

absdiff	ERGM-style covariate helpers for ame() / lame()
ab_plot	Visualize sender and receiver random effects
ab_plot.ame_als	Additive-effects plot for an ame_als fit
addhealthc3	AddHealth community 3 data
addhealthc9	AddHealth community 9 data
als_dynamic_beta	Penalised ALS time-varying coefficient estimate
als_start_vals	Convert an ALS fit to MCMC starting values
ame	AME model fitting routine
ame_als	Fast (MCMC-free) AME estimation for a cross-sectional network
ame_als_bootstrap	Bootstrap uncertainty for the fast AME estimator
ame_als_refit	Refit a fast AME model with a warm start
ame_memory_settings	Display memory usage information for AME models
ame_memory_usage	Calculate memory usage of AME model components
ame_options	AME model fitting options
ame_parallel	Run AME model with multiple parallel chains
array_to_list	Convert array to list.
as_draws	Generic dispatcher for posterior::as_draws on lame fits
as_draws.ame	Convert an AME / LAME fit to a posterior draws object
as_draws.ame_als	Convert an AME / LAME fit to a posterior draws object
as_draws.lame	Convert an AME / LAME fit to a posterior draws object
as_lame_y	Convert a graph object to a lame-ready adjacency matrix
autoplot.ame	Ribbon plot of time-varying coefficients (or coefplot for static fits)
autoplot.ame_als	autoplot method for ALS fits
autoplot.lame	Ribbon plot of time-varying coefficients (or coefplot for static fits)
autoplot.lame_als	autoplot method for ALS fits

-- B --

boot_ame	Bootstrap uncertainty for the fast AME estimator
boot_ame-no-fitted	fitted/residuals are not defined for a bootstrap object

-- C --

check_format	Validate input data format for lame function
coef.als_dynamic_beta	Extract beta path from a penalised-ALS object
coef.ame	Extract model coefficients from AME model
coef.ame_als	Extract coefficients from a fast AME fit
coef.boot_ame	Point estimates from a fast AME bootstrap
coef.lame	Extract model coefficients from AME model
coldwar	Cold War data
combine_ame_chains	Combine multiple AME chains
compact_ame	Optimize AME model output for memory efficiency
compute_mcmc_diagnostics	Compute MCMC convergence diagnostics for multiple chains
compute_XtX_Xty_bip_cpp	Compute X'X and X'y for bipartite covariate regression
comtrade	Comtrade data
confint.ame	Bayesian credible intervals for AME model parameters
confint.ame_als	Confidence intervals for a fast AME fit
confint.boot_ame	Confidence intervals from a fast AME bootstrap
confint.lame	Bayesian credible intervals for AME model parameters

-- D --

design_array_listwisedel	Computes the design socioarray of covariate values
detect_change_point	Detect potential change points in a dynamic_beta posterior path
dutchcollege	Dutch college data
dynamic_beta_prior_summary	Summarise the implied prior on a time-varying coefficient path

-- E --

el2sm	Edgelist to sociomatrix
evaluate_heldout	Held-out predictive evaluation for an ame / lame fit

-- F --

fitted.ame	Extract fitted values from AME model
fitted.ame_als	Extract fitted values from a fast AME fit
fitted.boot_ame	fitted/residuals are not defined for a bootstrap object
fitted.lame	Extract fitted values from LAME model
forecast_pit	Probability-integral-transform calibration check for h-step forecasts
formula.ame	formula() is not defined for an ame() / lame() fit
formula.lame	formula() is not defined for an ame() / lame() fit

-- G --

get_design_rep	Create design array for replicate data
get_EZ_dynamic_beta_cpp	Compute EZ when beta is time-varying
get_fit_object	Get fitted object from MCMC results
get_start_vals	Get fitted object from MCMC results
glance	S3 generic for 'glance'
glance.ame	Glance method for fitted 'ame' / 'lame' objects
glance.ame_als	Glance method for fitted 'ame_als' / 'lame_als' objects
glance.lame	Glance method for fitted 'ame' / 'lame' objects
glance.lame_als	Glance method for fitted 'ame_als' / 'lame_als' objects
gof	Compute GOF statistics from saved posterior samples
gof_plot	Visualize goodness-of-fit statistics for AME and LAME models
gof_plot.ame_als	Goodness-of-fit check for an ame_als fit
gof_stats	Goodness of fit statistics
gof_stats_bipartite	Goodness of fit statistics for bipartite networks
gof_stats_unipartite	Goodness of fit statistics for unipartite networks
gof_temporal	Posterior-predictive temporal-trend test

-- I --

init_dynamic_ab_cpp	Initialize dynamic additive effects with AR(1) structure
init_dynamic_positions	Initialize dynamic latent positions with AR(1) structure
IR90s	International relations in the 90s

-- L --

lame	AME model fitting routine for longitudinal relational data
lame_als	Fast (MCMC-free) AME estimation for a longitudinal network
lame_multi	Multi-panel lame() with shared coefficients
lame_parallel	Run LAME (longitudinal AME) with multiple parallel chains
lame_resume	Resume a 'lame()' MCMC run from a checkpoint
lame_snap_als	Fast approximate dynamic snap-shift AME estimator
latent_positions	Extract latent positions as a tidy data frame
latent_positions.ame	Extract latent positions as a tidy data frame
latent_positions.ame_als	Extract latent positions as a tidy data frame
latent_positions.lame	Extract latent positions as a tidy data frame
lazegalaw	Lazega's law firm data
lfo	Exact rolling-origin leave-future-out cross-validation
list_to_array	Convert list to array
logLik.ame	Log-likelihood is not directly exposed for ame() / lame() fits
logLik.ame_als	Log-likelihood is not defined for a fast AME fit
logLik.lame	Log-likelihood is not directly exposed for ame() / lame() fits
loo	Generic dispatcher for loo / waic on ame / lame fits
loo.ame	Approximate leave-one-out cross-validation for AME / LAME fits
loo.ame_als	Approximate leave-one-out cross-validation for AME / LAME fits
loo.lame	Approximate leave-one-out cross-validation for AME / LAME fits

-- M --

mhalf

Symmetric square root of a matrix

-- N --

nobs.ame	Number of observed dyads in an AME / LAME fit
nobs.ame_als	Number of observed dyads in an ame_als fit
nobs.lame	Number of observed dyads in an AME / LAME fit
nodefactor	ERGM-style covariate helpers for ame() / lame()
nodematch	ERGM-style covariate helpers for ame() / lame()

-- P --

per_actor_slopes	Post-MCMC per-actor time-varying slopes
plot.ame	Simple diagnostic plot for AME model fit
plot.ame_als	Plot the convergence of a fast AME fit
plot.lame	Plot diagnostics for a LAME model fit
posterior_options	Options for saving posterior samples during MCMC
posterior_quantiles	Extract posterior quantiles for model components
predict.ame	Predict method for AME models
predict.ame_als	Predictions from a fast AME fit
predict.lame	Predict method for LAME models
prediction_draws_long	Long-format draws of the linear predictor for marginaleffects-style use
print.als_dynamic_beta	Print method for penalised ALS time-varying beta
print.ame	Print method for AME model objects
print.ame.sim	Print methods for AME and LAME simulation objects
print.ame_als	Print an ame_als object
print.boot_ame	Print bootstrap results for a fast AME fit
print.gof_temporal	Print method for gof_temporal output
print.lame	Print method for LAME objects
print.lame.sim	Print methods for AME and LAME simulation objects
print.lame_multi	Print method for lame_multi
print.lfo_lame	Print method for lfo() results
print.per_actor_slopes	Print method for per_actor_slopes
print.summary.ame	Print method for summary.ame objects
print.summary.ame_als	Print a fast AME summary
print.summary.boot_ame	Summarize bootstrap results for a fast AME fit
print.summary.lame	Print method for summary.lame objects
prior_summary	Print the priors used by an AME / LAME / ame_als fit
prior_summary.ame	Print the priors used by an AME / LAME / ame_als fit
prior_summary.ame_als	Print the priors used by an AME / LAME / ame_als fit
prior_summary.default	Print the priors used by an AME / LAME / ame_als fit
prior_summary.lame	Print the priors used by an AME / LAME / ame_als fit
procrustes_align	Procrustes alignment of latent positions across time

-- R --

rbeta_ab_bip_gibbs_cpp	Full bipartite Gibbs update for beta, a, b
read_log_lik	Read the per-iteration log-lik matrix back from on-disk chunks
reconstruct_EZ	Reconstruct EZ and UVPM matrices from AME model output
reconstruct_UVPM	Reconstruct EZ and UVPM matrices from AME model output
residuals.ame	Extract residuals from AME model
residuals.ame_als	Residuals from a fast AME fit
residuals.boot_ame	fitted/residuals are not defined for a bootstrap object
residuals.lame	Extract residuals from LAME model
rhat_dynamic_beta	Multivariate split-R-hat for dynamic_beta coefficient paths
rmvnorm	Simulation from a multivariate normal distribution
rSab_fc	Gibbs update for additive effects covariance
rUV_dynamic_bip_fc_cpp	Bipartite dynamic UV Gibbs update
rUV_dynamic_fc	Gibbs sampling of dynamic U and V with AR(1) evolution
rUV_dynamic_fc_cpp	Update dynamic latent positions using AR(1) process
rUV_dynamic_snap_fc	Gibbs sampling of dynamic U and V with snap-shift dynamics
rUV_dynamic_snap_fc_cpp	Update dynamic latent positions with snap-shift model selection
rUV_dynamic_t_fc	Gibbs sampling of dynamic U and V with heavy-tailed (Student-t) innovations
rUV_dynamic_t_fc_cpp	Update dynamic latent positions with heavy-tailed (Student-t) AR(1) innovations
rUV_sym_fc	Gibbs sampling of U and V
rZ_bin_bip_batch_cpp	Batch binary Z sampling across all time periods (bipartite, rho=0)
rZ_nrm_batch_cpp	Batch normal Z sampling across all time periods
rZ_nrm_fc	Simulate missing values in a normal AME model
rZ_pois_fc	Gibbs update for latent variable in a Poisson AME model

-- S --

sampler_describe	Describe the estimator behind a fitted object
sampler_describe.ame	Describe the estimator behind a fitted object
sampler_describe.ame_als	Describe the estimator behind a fitted object
sampler_describe.boot_ame	Describe the estimator behind a fitted object
sampler_describe.lame	Describe the estimator behind a fitted object
sample_beta_dynamic_cpp	Sample the dynamic-block beta path via FFBS
sample_beta_static_cpp	Sample the static-block beta conditional on the dynamic path
sample_dynamic_ab_cpp	Sample dynamic additive effects with AR(1) evolution
sample_rho_ab_cpp	Sample AR(1) parameter for dynamic additive effects
sample_rho_beta_cpp	Sample the AR(1) rho for each dynamic block
sample_rho_uv	Sample AR(1) parameter for dynamic latent factors
sample_sigma_ab_cpp	Sample innovation variance for dynamic additive effects
sample_sigma_beta_cpp	Sample the AR(1) innovation sigma for each dynamic block
sample_sigma_uv	Sample innovation variance for dynamic latent factors
sampsonmonks	Sampson's monastery data
sheep	Sheep dominance data
simulate.ame	Simulate networks from a fitted AME model
simulate.ame_als	Simulate networks from a fitted ame_als model
simulate.lame	Simulate longitudinal networks from a fitted LAME model
simulate_posterior	Simulate posterior distributions from fitted AME model
simY_pois	Simulate a Poisson relational matrix
snap_category_summary	Summarize snap indices by actor category
snap_index_draws	Extract posterior draws of snap indices
snap_index_summary	Summarize posterior snap indices
snap_rank_summary	Summarize posterior rank uncertainty for snap years
summary.ame	Summary of an AME object
summary.ame.sim	Summary method for AME simulations
summary.ame_als	Summarize an ame_als object
summary.boot_ame	Summarize bootstrap results for a fast AME fit
summary.lame	Summary of a LAME object
summary.lame.sim	Summary method for LAME simulations

-- T --

tidy	S3 generic for 'tidy'
tidy.ame	Tidy method for fitted 'ame' / 'lame' objects
tidy.ame_als	Tidy method for fitted 'ame_als' / 'lame_als' objects
tidy.boot_ame	Tidy method for a standalone bootstrap object ('boot_ame')
tidy.lame	Tidy method for fitted 'ame' / 'lame' objects
tidy.lame_als	Tidy method for fitted 'ame_als' / 'lame_als' objects
trace_plot	MCMC trace plots and density plots for AME/LAME model parameters

-- U --

update.ame	Update an AME / LAME fit
update.ame_als	Update an 'ame_als' / 'lame_als' fit
update.lame	Update an AME / LAME fit
update.lame_als	Update an 'ame_als' / 'lame_als' fit
uv_plot	Visualize multiplicative effects (latent factors) from AME models

-- V --

vcov.ame	Posterior covariance of AME model coefficients
vcov.ame_als	Sandwich covariance for the regression coefficients of a fast AME fit
vcov.boot_ame	Bootstrap covariance of the regression coefficients
vcov.lame	Posterior covariance of AME model coefficients
vignette_data	TIES sanctions data for vignettes

-- W --

waic	Generic dispatcher for loo / waic on ame / lame fits
waic.ame	WAIC for AME / LAME fits
waic.ame_als	WAIC for AME / LAME fits
waic.lame	WAIC for AME / LAME fits

-- X --

Xbeta	Linear combinations of submatrices of an array
Xbeta_bip_cpp	Compute Xbeta product for bipartite networks
Xcol	Column covariates
Xdyad	Dyadic covariates
Xrow	Row covariates

-- Y --

Y	Relational matrix
YX_bin	binary relational data and covariates
YX_bin_list	Synthetic longitudinal binary relational data, list-form (latent-scale)
YX_bin_long	synthetic longitudinal binary relational data (latent-scale)
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