Package index • ipd

All functions

A(): Calculation of the matrix A based on single dataset

Sigma_cal(): Variance-covariance matrix of the estimation equation

augment(<ipd>): Augment data from an ipd fit

calc_lhat_glm(): Estimate PPI++ Power Tuning Parameter

chen_ols(): Chen & Chen OLS

compute_cdf(): Empirical CDF of the Data

compute_cdf_diff(): Empirical CDF Difference

est_ini(): Initial estimation

glance(<ipd>): Glance at an ipd fit

ipd-class: ipd: S4 class for inference on predicted data results

ipd(): Inference on Predicted Data (ipd)

link_Hessian(): Hessians of the link function

link_grad(): Gradient 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

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

show(<ipd>): Show an ipd object

sim_data_y(): Simulate the data for testing the functions

simdat(): Data generation function for various underlying models

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