Reference

All functions
REndo REndo-package	Fitting Linear Models with Endogenous Regressors using Latent Instrumental Variables
confint(<rendo.boots>)	Confidence Intervals for Bootstrapped Model Parameters
copulaCorrection()	Fitting Linear Models Endogenous Regressors using Gaussian Copula
dataCopCont	Simulated Dataset with One Endogenous Continuous Regressor
dataCopCont2	Simulated Dataset with Two Endogenous Continuous Regressor
dataCopDis	Simulated Dataset with One Endogenous Discrete Regressor
dataCopDis2	Simulated Dataset with Two Endogenous Discrete Regressors
dataCopDisCont	Simulated Dataset with Two Endogenous Regressors
dataHetIV	Simulated Dataset with One Endogenous Continuous Regressor
dataHigherMoments	Simulated Dataset with One Endogenous Regressor
dataLatentIV	Simulated Dataset with One Endogenous Continuous Regressor
dataMultilevelIV	Multilevel Simulated Dataset - Three Levels
hetErrorsIV()	Fitting Linear Models with Endogenous Regressors using Heteroskedastic Covariance Restrictions
higherMomentsIV()	Fitting Linear Models with Endogenous Regressors using Lewbel's Higher Moments Approach
latentIV()	Fitting Linear Models with one Endogenous Regressor using Latent Instrumental Variables
multilevelIV()	Fitting Multilevel GMM Estimation with Endogenous Regressors
predict(<rendo.copula.correction>)	Predict method for Models using the Gaussian Copula Approach
predict(<rendo.ivreg>)	Predict method for fitted Regression Models with Internal Instrumental Variables
predict(<rendo.latent.IV>)	Predict method for Models using the Latent Instrumental Variables approach
predict(<rendo.multilevel>)	Predict method for Multilevel GMM Estimations
summary(<rendo.copula.correction>)	Summarizing Bootstrapped copulaCorrection Model Fits
summary(<rendo.latent.IV>)	Summarizing latentIV Model Fits
summary(<rendo.multilevel>)	Summarizing Multilevel GMM Estimation with Endogenous Regressors Model Fits
vcov(<rendo.boots>)	Calculate Variance-Covariance Matrix for Models Fitted with Bootstrapped Parameters