Package index • smartcor

Core Functions

Compute correlations with automatic method selection.

smart_cor(): Choose and Compute a Correlation
smart_cor_df(): Correlation Matrix as Plain Data Frames
smart_cormat(): Build a Mixed-Type Correlation Matrix

Method Comparison

Compare all applicable methods for a variable pair.

compare_methods(): Run Every Applicable Method on One Pair

Diagnostics

Check outliers, normality, latent normality, and linearity for method selection.

detect_outliers() print(<smartcor_outliers>): Flag Outliers with the Outer-Fence Rule
test_bivariate_normality(): Test Bivariate Normality for a Pair of Variables
test_linearity(): Test Linearity Using Ordered Regression Residuals

Helpers

Inspect variable types and available methods.

detect_type(): Detect the Statistical Type of a Variable
available_methods(): Which Methods Apply to a Pair of Variable Types

Tidy Output

Convert results to tidy data frames.

tidy(<smartcor>): Tidy a smartcor Object
tidy(<smartcormat>): Tidy a smartcormat Object
tidy(<smartcor_comparison>): Tidy a smartcor Comparison

Plotting (Base R)

Visualise correlation matrices with base graphics.

plot(<smartcormat>) plot_cor_heatmap(): Plot a Correlation Heatmap

Plotting (ggplot2)

Publication-quality visualisations with ggplot2.

ggcor_heatmap() ggcor_method_heatmap(): ggplot2 Heatmaps for Smart Correlation Matrices

Print Methods

print(<smartcor>): Print a smartcor Object
print(<smartcormat>): Print a smartcormat Object
print(<smartcor_comparison>): Print a Method Comparison
print(<smartcor_normtest>): Print a Normality Test
print(<smartcor_lintest>): Print a Linearity Test