R: Babson Analytics and Quantitative Methods Tools

# Babson Analytics and Quantitative Methods Tools

## Documentation for package ‘BAQM’ version 0.1.4

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

lm_plot.4way | Create a Four-Panel Regression Assumptions Plot
lm_plot.ac | Plot Residuals vs. Observation Order (Autocorrelation Check)
lm_plot.df | Augment Model Data for Diagnostic Plots
lm_plot.fit | Plot Observed vs. Fitted Values to Check Linearity
lm_plot.infl | Plot Leverage vs. Fitted Values to Visualize Inflential Observations
lm_plot.lev | Plot Standard Residuals vs. Leverage with Cook's Distance Contours
lm_plot.parms | Set or Retrieve Default Plot Parameters for Model Diagnostic Plots
lm_plot.qq | Q-Q Plot of Residuals to Assess Normality
lm_plot.var | Plot Residuals vs. Fitted Values to Assess Homoskedasticity
outlier | Identify Outliers Using Boxplot Heuristic
print.sumry.lm | Print a 'sumry' Summarization for Linear Model Objects
print.sumry.regsubsets | Print Method for Best Subset Selection ('regsubsets') Objects
print.table.sumry.lm | Print a Table from Linear Model Summary
sumry | Summary Descriptive Statistics for BAQM
sumry.default | Summary Descriptive Statistics for List or Data Frame
sumry.lm | Method 'sumry' to Summarize Linear Model ('lm') Objects
sumry.regsubsets | Summary for Subset Selection ('regsubsets') Objects