R: Linear Regression and Logistic Regression with Missing Covariates

# Linear Regression and Logistic Regression with Missing Covariates

## Documentation for package ‘misaem’ version 1.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

combinations | combinations
imputeEllP | Function for imputing single point for linear regression model
initialize_df | Initialize Missing Data in Data Frame
likelihood_saem | likelihood_saem
log_reg | log_reg
louis_lr_saem | louis_lr_saem
miss.glm | Statistical Inference for Logistic Regression Models with Missing Values
miss.glm.control | Auxiliary for Controlling Fitting
miss.glm.fit | Fitting Logistic Regression Models with Missing Values
miss.glm.model.select | miss.glm.model.select
miss.lm | Statistical Inference for Linear Regression Models with Missing Values
miss.lm.control | Auxiliary for Controlling Fitting
miss.lm.fit | Fitting Linear Regression Model with Missing Values
miss.lm.model.select | miss.lm.model.select
predict.miss.glm | Prediction on test with missing values for the logistic regression model.
predict.miss.lm | Prediction on test with missing values for the linear regression model.
print.miss.glm | Print miss.glm
print.miss.lm | Print miss.lm
print.summary.miss.glm | Print Summary of miss.glm
print.summary.miss.lm | Print Summary of miss.lm
summary.miss.glm | Summarizing Fits for miss.glm
summary.miss.lm | Summarizing Fits for miss.lm