Package index
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A() - Calculation of the matrix A based on single dataset
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Sigma_cal() - Variance-covariance matrix of the estimation equation
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augment(<ipd>) - Augment Data from an IPD Fit
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calc_lhat_glm() - Estimate PPI++ Power Tuning Parameter
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compute_cdf() - Empirical CDF of the Data
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compute_cdf_diff() - Empirical CDF Difference
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est_ini() - Initial estimation
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glance(<ipd>) - Glance at an IPD Fit
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ipd() - Inference on Predicted Data (ipd)
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link_Hessian() - Hessians of the link function
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link_grad() - Gradient of the link function
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log1pexp() - Log1p Exponential
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logistic_get_stats() - Logistic Regression Gradient and Hessian
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mean_psi() - Sample expectation of psi
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mean_psi_pop() - Sample expectation of PSPA psi
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ols() - Ordinary Least Squares
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ols_get_stats() - OLS Gradient and Hessian
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optim_est() - One-step update for obtaining estimator
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optim_weights() - One-step update for obtaining the weight vector
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postpi_analytic_ols() - PostPI OLS (Analytic Correction)
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postpi_boot_logistic() - PostPI Logistic Regression (Bootstrap Correction)
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postpi_boot_ols() - PostPI OLS (Bootstrap Correction)
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ppi_logistic() - PPI Logistic Regression
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ppi_mean() - PPI Mean Estimation
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ppi_ols() - PPI OLS
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ppi_plusplus_logistic() - PPI++ Logistic Regression
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ppi_plusplus_logistic_est() - PPI++ Logistic Regression (Point Estimate)
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ppi_plusplus_mean() - PPI++ Mean Estimation
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ppi_plusplus_mean_est() - PPI++ Mean Estimation (Point Estimate)
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ppi_plusplus_ols() - PPI++ OLS
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ppi_plusplus_ols_est() - PPI++ OLS (Point Estimate)
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ppi_plusplus_quantile() - PPI++ Quantile Estimation
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ppi_plusplus_quantile_est() - PPI++ Quantile Estimation (Point Estimate)
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ppi_quantile() - PPI Quantile Estimation
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print(<ipd>) - Print IPD Fit
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print(<summary.ipd>) - Print Summary of IPD Fit
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psi() - Estimating equation
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pspa_logistic() - PSPA Logistic Regression
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pspa_mean() - PSPA Mean Estimation
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pspa_ols() - PSPA OLS Estimation
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pspa_poisson() - PSPA Poisson Regression
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pspa_quantile() - PSPA Quantile Estimation
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pspa_y() - PSPA M-Estimation for ML-predicted labels
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rectified_cdf() - Rectified CDF
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rectified_p_value() - Rectified P-Value
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sim_data_y() - Simulate the data for testing the functions
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simdat() - Data generation function for various underlying models
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summary(<ipd>) - Summarize IPD Fit
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tidy(<ipd>) - Tidy an IPD Fit
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wls() - Weighted Least Squares
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zconfint_generic() - Normal Confidence Intervals
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zstat_generic() - Compute Z-Statistic and P-Value