Readable Regular Expressions (regexr)
An R framework for constructing human readable regular expressions. It aims to provide tools that enable the user to write regular expressions in a way that is similar to the ways R code is written. The tools allow the user to (1) write in smaller, modular, named, regular expression chunks, (2) write top to bottom, rather than a single string (3) comment individual chunks, (4) indent expressions to represent regular expression groups, and (5) test the validity of the concatenated expression and the modular chunks.

Session Reconstruction and Analysis (reconstructr)
Functions to aid in reconstructing sessions and efficiently calculating an array of metrics from the resulting data, including bounce rate, time-on-page, and session length. Although primarily designed for web data and analytics, its approach is plausibly applicable to other domains.

Visualization and Analysis Tools for Neural Networks (NeuralNetTools)
Visualization and analysis tools to aid in the interpretation of neural network models. Functions are available for plotting, quantifying variable importance, conducting a sensitivity analysis, and obtaining a simple list of model weights.

Implement Feature Hashing on Model Matrix (FeatureHashing)
Feature hashing, also called as the hashing trick, is a method to transform features to vector. Without looking the indices up in an associative array, it applies a hash function to the features and uses their hash values as indices directly. This package implements the method of feature hashing proposed in Weinberger et. al. (2009) with Murmurhash3 and provides a formula interface in R. See the README.md for more information.

Interface to Dygraphs Interactive Time Series Charting Library (dygraphs)
An R interface to the dygraphs JavaScript charting library (a copy of which is included in the package). Provides rich facilities for charting time-series data in R, including highly configurable series- and axis-display and interactive features like zoom/pan and series/point highlighting.

Collection of methods to detect dichotomous differential item functioning (DIF) in psychometrics (difR)
The difR package contains several traditional methods to detect DIF in dichotomously scored items. Both uniform and non-uniform DIF effects can be detected, with methods relying upon item response models or not. Some methods deal with more than one focal group.

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