Function Reference

The cccc package provides a comprehensive set of functions organized around the four-stage analytical pipeline. Below, functions are grouped by their primary purpose to help you navigate the workflow more effectively.

📥 Data Import & Preprocessing

Functions for importing, validating, and preparing your corpus data.

Function	Description
`importData()`	Imports and validates corpus data and metadata into a standardized structure for analysis.
`normalization()`	Normalizes the term-document matrix using various schemes (nc, nchi, nM, nmM, nnl).

📊 Exploratory Visualization

Functions for initial exploration and visualization of corpus characteristics.

Function	Description
`rowMassPlot()`	Creates a bar plot of keywords ordered by total frequency and colored by frequency zone.
`colMassPlot()`	Plots the temporal dimensions of a corpus, showing distribution across time periods.

📈 Temporal Modeling & Smoothing

Functions for modeling keyword trajectories and selecting optimal smoothing parameters.

Function	Description
`smoothingSelection()`	Selects optimal smoothing parameters for chronological keyword curves using cross-validation.
`optimalSmoothing()`	Selects the optimal spline degree and penalization strategy for trajectory smoothing.
`plotSuboptimalFits()`	Plots suboptimal smoothed curves for selected keywords to compare different smoothing approaches.

📉 Trajectory Visualization

Functions for visualizing temporal curves and frequency patterns.

Function	Description
`curvePlot()`	Plots temporal curves of keyword frequencies over time periods.
`curveCtuPlot()`	Plots temporal curves for frequency zones with example keywords highlighted.
`facetPlot()`	Creates faceted plots of keyword frequency curves for comparative visualization.

📖 Quick Reference Guide

Typical Workflow

Import your data → importData()
Explore the corpus → rowMassPlot(), colMassPlot()
Normalize frequencies → normalization()
Visualize trajectories → curvePlot(), curveCtuPlot(), facetPlot()
Select smoothing parameters → smoothingSelection(), optimalSmoothing()
Compare fits → plotSuboptimalFits()

Function Categories Summary

Category	Number of Functions	Purpose
Data Import & Preprocessing	2	Prepare and normalize data
Exploratory Visualization	2	Initial corpus exploration
Temporal Modeling	3	Optimize smoothing parameters
Trajectory Visualization	3	Visualize temporal patterns

🔍 Need Help?

Click on any function name to see detailed documentation
Visit the Use Cases page for practical examples
Check out Projects to see cccc in action
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