R: Network Scale-Up Models for Aggregated Relational Data

# Network Scale-Up Models for Aggregated Relational Data

## Documentation for package ‘networkscaleup’ version 0.2-1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

networkscaleup-package | The 'networkscaleup' package.
construct_pearson | Compute Pearson Residuals for ARD matrix and fitted model
construct_rqr | Compute Randomized Quantile Residuals for ARD Models
correlatedStan | Fit ARD using the uncorrelated or correlated model in Stan This function fits the ARD using either the uncorrelated or correlated model in Laga et al. (2021) in Stan. The population size estimates and degrees are scaled using a post-hoc procedure.
cov_plots | Covariance plots
dispersion_metric | Dispersion Metric for Fitted ARD Model
example_data | Simulated ARD data set with z and x.
fit_mle | Fit basic Poisson and Negative Binomial models using glmmTMB
get_surrogate | Compute Surrogate Residuals for ARD Models
hang_rootogram_ard | Hanging Rootogram for Fitted ARD Model
killworth | Fit Killworth models to ARD. This function estimates the degrees and population sizes using the plug-in MLE and MLE estimator.
log_mix_uniform | log computed uniform quantile
make_ard | Generate simulated ARD
make_ard_tidy | Construct tibble from ARD matrix
networkscaleup | The 'networkscaleup' package.
overdispersed | Fit Overdispersed model to ARD (Gibbs-Metropolis)
overdispersedStan | Fit ARD using the Overdispersed model in Stan
plot_fitted | Plot residuals against fitted values
residual_correlation | Construction Residual (row/column) correlation matrix
residual_heatmap | Construct heatmap of residuals
rqr_nbinom_logs | compute numerically stable negative binomial rqr
rqr_pois_logs | compute numerically stable Poisson rqr
scaling | Scale raw log degree and log prevalence estimates
tw_group_corr_test | Tracy-Widom test for residual group correlation