Synthetic Data Generation with Copulas, Evaluation and Multi-Format I/O

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Documentation for package ‘SynthesizerPlus’ version 0.2.9

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

Help Pages

association_matrix	Mixed-type association matrix
augment_data	Augment a small training set with synthetic data
augment_data.data.frame	Augment a small training set with synthetic data
augment_data.default	Augment a small training set with synthetic data
augment_data.matrix	Augment a small training set with synthetic data
augment_data.ts	Augment a small training set with synthetic data
autoplot.sp_comparison	Plot a comparison of real and synthetic data
calibrate_closeness	Calibrate the closeness of synthetic to real data
census_sim	Simulated census-like microdata
ci_overlap	Confidence-interval overlap of regression coefficients
compare_synthetic	Compare synthetic data with the real data
copula_correlation	Inspect a fitted synthesizer
dcr	Distance to closest record (disclosure risk)
disclosure_risk	Disclosure risk of synthetic microdata
discriminator_auc	Discriminator AUC
fit_synthesizer	Fit a synthetic-data model
fit_synthesizer.data.frame	Fit a synthetic-data model
fit_synthesizer.default	Fit a synthetic-data model
fit_synthesizer.matrix	Fit a synthetic-data model
fit_synthesizer.ts	Fit a synthesizer to a (multivariate) time series
generate	Generate synthetic data from a fitted model
generate.sp_synthesizer	Generate synthetic data from a fitted model
generate.sp_ts_synthesizer	Generate synthetic data from a fitted model
generate_to_file	Generate a large synthetic data set directly to disk
make_corr	Build a correlation matrix with a given structure
marginal_metrics	Compare marginal distributions of real and synthetic data
margin_categorical	Marginal quantile functions for r_mvdist()
margin_empirical	Marginal quantile functions for r_mvdist()
match_types	Coerce the columns of a data frame to the classes of a template
mvdist	Multivariate random number generators
perturbation	Perturbations of the synthetic data distribution
plot.sp_comparison	Plot a comparison of real and synthetic data
plot_acf	Plot real and synthetic time series
plot_association	Plot association matrices of real and synthetic data
plot_categorical	Plot marginal distributions of real and synthetic data
plot_dcr	Plot distances to the closest record
plot_marginals	Plot marginal distributions of real and synthetic data
plot_pairs	Scatter-plot matrix of real and/or synthetic data
plot_qq	Quantile-quantile plots of synthetic against real data
plot_ts	Plot real and synthetic time series
pmse	Propensity-score utility (pMSE)
read_data	Read a data set from a file
r_copula	Sample from a copula
r_dirichlet	Multivariate random number generators
r_mvdist	Generate data from a copula with arbitrary marginal distributions
r_mvlnorm	Multivariate random number generators
r_mvmixture	Multivariate random number generators
r_mvnorm	Multivariate random number generators
r_mvskewnorm	Multivariate random number generators
r_mvt	Multivariate random number generators
simulate.sp_synthesizer	Simulate several synthetic data sets
simulate.sp_ts_synthesizer	Simulate several synthetic data sets
summary.sp_synthesizer	Inspect a fitted synthesizer
supported_formats	Supported file formats
synthesize	Fit a synthesizer and generate synthetic data in one step
ts_windows	Build a lagged-feature table from one or more time series
write_data	Write a data set to a file