Function reference • dgpoix

All functions

ar1_errors(): Generate autoregressive Gaussian errors.

block_errors(): Generate block-correlated Gaussian errors.

correlated_linear_gaussian_dgp(): Generate correlated Gaussian covariates and linear response data.

correlated_logistic_gaussian_dgp(): Generate correlated Gaussian covariates and (binary) logistic response data.

correlated_lss_gaussian_dgp(): Generate correlated Gaussian covariates and LSS response data.

generate_X_gaussian(): Generate a normal random matrix of covariates/features.

generate_X_rwd(): Generate a design matrix X by sampling from a real-world data matrix.

generate_coef(): Helper function to generate a coefficient vector.

generate_errors(): Helper function to generate simulated errors.

generate_y_linear(): Simulate linear response data.

generate_y_logistic(): Simulate (binary) logistic response data.

generate_y_lss(): Generate locally spiky smooth (LSS) response data.

linear_gaussian_dgp(): Generate independent Gaussian covariates and linear response data.

logistic_gaussian_dgp(): Generate independent Gaussian covariates and (binary) logistic response data.

lss_gaussian_dgp(): Generate independent Gaussian covariates and LSS response data.

norm_errors(): Generate heteroskedastic Gaussian errors based on the norm of X.

omitted_var_dgp(): Generate data from a model with omitted variable bias.

return_DGP_output(): Developer function to return consistent outputs in DGP.

rwd_dgp(): Read in real world data from X and y.

xy_dgp_constructor(): General DGP constructor function to generate X and y data.