Man pages for ipd
Inference on Predicted Data
| A | Calculation of the matrix A based on single dataset |
| augment.ipd | Augment data from an ipd fit |
| calc_lhat_glm | Estimate PPI++ Power Tuning Parameter |
| chen_logistic | Chen & Chen Logistic |
| chen_ols | Chen & Chen OLS |
| chen_poisson | Chen & Chen Poisson |
| compute_cdf | Empirical CDF of the Data |
| compute_cdf_diff | Empirical CDF Difference |
| dot-build_design | Build design matrices and outcome vectors |
| dot-drop_unused_levels | Drop unused factor levels and report which were removed |
| dot-parse_inputs | Validate and split input data |
| dot-warn_differing_levels | Warn on differing factor levels between labeled and unlabeled... |
| est_ini | Initial estimation |
| glance.ipd | Glance at an ipd fit |
| ipd | Inference on Predicted Data (ipd) |
| ipd-class | ipd: S4 class for inference on predicted data results |
| ipd-package | ipd: Inference on Predicted Data |
| link_grad | Gradient of the link function |
| link_Hessian | Hessians of the link function |
| log1pexp | Log1p Exponential |
| logistic_get_stats | Logistic Regression Gradient and Hessian |
| mean_psi | Sample expectation of psi |
| mean_psi_pop | Sample expectation of PSPA psi |
| ols | Ordinary Least Squares |
| ols_get_stats | OLS Gradient and Hessian |
| optim_est | One-step update for obtaining estimator |
| optim_weights | One-step update for obtaining the weight vector |
| pdc_logistic | PDC Logistic |
| pdc_ols | PDC OLS |
| pdc_poisson | PDC Poisson |
| postpi_analytic_ols | PostPI OLS (Analytic Correction) |
| postpi_boot_logistic | PostPI Logistic Regression (Bootstrap Correction) |
| postpi_boot_ols | PostPI OLS (Bootstrap Correction) |
| ppi_a_ols | PPI "All" OLS |
| ppi_logistic | PPI Logistic Regression |
| ppi_mean | PPI Mean Estimation |
| ppi_ols | PPI OLS |
| ppi_plusplus_logistic | PPI++ Logistic Regression |
| ppi_plusplus_logistic_est | PPI++ Logistic Regression (Point Estimate) |
| ppi_plusplus_mean | PPI++ Mean Estimation |
| ppi_plusplus_mean_est | PPI++ Mean Estimation (Point Estimate) |
| ppi_plusplus_ols | PPI++ OLS |
| ppi_plusplus_ols_est | PPI++ OLS (Point Estimate) |
| ppi_plusplus_quantile | PPI++ Quantile Estimation |
| ppi_plusplus_quantile_est | PPI++ Quantile Estimation (Point Estimate) |
| ppi_quantile | PPI Quantile Estimation |
| print.ipd | Print ipd fit |
| print.summary.ipd | Print summary.ipd |
| psi | Estimating equation |
| pspa_logistic | PSPA Logistic Regression |
| pspa_mean | PSPA Mean Estimation |
| pspa_ols | PSPA OLS Estimation |
| pspa_poisson | PSPA Poisson Regression |
| pspa_quantile | PSPA Quantile Estimation |
| pspa_y | PSPA M-Estimation for ML-predicted labels |
| rectified_cdf | Rectified CDF |
| rectified_p_value | Rectified P-Value |
| reexports | tidy re-exported from generics packages |
| show-ipd-method | Show an ipd object |
| Sigma_cal | Variance-covariance matrix of the estimation equation |
| simdat | Data generation function for various underlying models |
| sim_data_y | Simulate the data for testing the functions |
| summary.ipd | Summarize ipd fit |
| tidy.ipd | Tidy an ipd fit |
| wls | Weighted Least Squares |
| zconfint_generic | Normal Confidence Intervals |
| zstat_generic | Compute Z-Statistic and P-Value |
