Man pages for Yu-Group/dgpoix
Generate synthetic data that is as fresh as the real thing
| ar1_errors | Generate autoregressive Gaussian errors. |
| block_errors | Generate block-correlated Gaussian errors. |
| correlated_linear_gaussian_dgp | Generate correlated Gaussian covariates and linear response... |
| correlated_logistic_gaussian_dgp | Generate correlated Gaussian covariates and (binary) logistic... |
| correlated_lss_gaussian_dgp | Generate correlated Gaussian covariates and LSS response... |
| dots_to_fun_args | Helper function to process ... args to pass to multiple... |
| generate_coef | Helper function to generate a coefficient vector. |
| generate_errors | Helper function to generate simulated errors. |
| 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... |
| 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. |
| indicator | Helper function to compute indicator function in LSS model. |
| linear_gaussian_dgp | Generate independent Gaussian covariates and linear response... |
| logistic_gaussian_dgp | Generate independent Gaussian covariates and (binary)... |
| lss_gaussian_dgp | Generate independent Gaussian covariates and LSS response... |
| norm_errors | Generate heteroskedastic Gaussian errors based on the norm of... |
| omitted_var_dgp | Generate data from a model with omitted variable bias. |
| pipe | Pipe operator |
| return_DGP_output | Developer function to return consistent outputs in DGP. |
| rwd_dgp | Read in real world data from X and y. |
| shared_dgp_lib_args | Arguments that are shared by multiple 'DGP' library... |
| split_data | Helper function to split data into training and test sets |
| xy_dgp_constructor | General DGP constructor function to generate X and y data. |
