Tidy Finance Helper Functions

Helper functions for empirical research in financial economics, addressing a variety of topics covered in Scheuch, Voigt, and Weiss (2023) . The package is designed to provide shortcuts for issues extensively discussed in the book, facilitating easier application of its concepts. For more information and resources related to the book, visit < https://www.tidy-finance.org/r/index.html>.

Working with Sets the Tidy Way

Implements a class and methods to work with sets, doing intersection, union, complementary sets, power sets, cartesian product and other set operations in a "tidy" way. These set operations are available for both classical sets and fuzzy sets. Import sets from several formats or from other several data structures.

Tidy Standardized Mean Differences

Tidy standardized mean differences ('SMDs'). 'tidysmd' uses the 'smd' package to calculate standardized mean differences for variables in a data frame, returning the results in a tidy format.

Tidy Bayesian Vector Autoregression

Functions to prepare tidy objects from estimated models via 'BVAR' (see Kuschnig & Vashold, 2019 ) and visualisation thereof. Bridges the gap between estimating models with 'BVAR' and plotting the results in a more sophisticated way with 'ggplot2' as well as passing them on in a tidy format.

A Tidy Solution for Epidemiological Data

Offers a tidy solution for epidemiological data. It houses a range of functions for epidemiologists and public health data wizards for data management and cleaning.

A Tidy Wrapper Around 'gtrendsR'

Access Google Trends information. This package provides a tidy wrapper to the 'gtrendsR' package. Use four spaces when indenting paragraphs within the Description.

Tidy Characterizations of Model Performance

Tidy tools for quantifying how well model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).

Tidy Data Validation Reports

Tools for creating data validation pipelines and tidy reports. This package offers a framework for exploring and validating data frame like objects using 'dplyr' grammar of data manipulation.

Heatmaps from Tidy Data

The goal of 'tidyheatmaps' is to simplify the generation of publication-ready heatmaps from tidy data. By offering an interface to the powerful 'pheatmap' package, it allows for the effortless creation of intricate heatmaps with minimal code.

Smooth and Tidy Spatial Features

Tools for smoothing and tidying spatial features (i.e. lines and polygons) to make them more aesthetically pleasing. Smooth curves, fill holes, and remove small fragments from lines and polygons.