Tidy Tools for Visualizing Mixture Models

The main function, plot_mm(), is used for (gg)plotting output from mixture models, including both densities and overlaying mixture weight component curves from the fit models in line with the tidy principles. The package includes several additional functions for added plot customization. Supported model objects include: 'mixtools', 'EMCluster', and 'flexmix', with more from each in active dev. Supported mixture model specifications include mixtures of univariate Gaussians, multivariate Gaussians, Gammas, logistic regressions, linear regressions, and Poisson regressions.

Tidy Manipulation of Fourier Transformed Data

The 'fftab' package stores Fourier coefficients in a tibble and allows their manipulation in various ways. Functions are available for converting between complex, rectangular ('re', 'im'), and polar ('mod', 'arg') representations, as well as for extracting components as vectors or matrices. Inputs can include vectors, time series, and arrays of arbitrary dimensions, which are restored to their original form when inverting the transform. Since 'fftab' stores Fourier frequencies as columns in the tibble, many standard operations on spectral data can be easily performed using tidy packages like 'dplyr'.

Weighted Tidy Log Odds Ratio

How can we measure how the usage or frequency of some feature, such as words, differs across some group or set, such as documents? One option is to use the log odds ratio, but the log odds ratio alone does not account for sampling variability; we haven't counted every feature the same number of times so how do we know which differences are meaningful? Enter the weighted log odds, which 'tidylo' provides an implementation for, using tidy data principles. In particular, here we use the method outlined in Monroe, Colaresi, and Quinn (2008) to weight the log odds ratio by a prior. By default, the prior is estimated from the data itself, an empirical Bayes approach, but an uninformative prior is also available.

A Service for Tidy Transcriptomics Software Suite

It provides generic methods that are used by more than one package, avoiding conflicts. This package will be imported by 'tidySingleCellExperiment' and 'tidyseurat'.

Tidy Up Date/Time Ranges

Collapse, partition, combine, fill gaps in and expand date/time ranges.

Generate Tidy Charts Inspired by 'IBCS'

There is a wide range of R packages created for data visualization, but still, there was no simple and easily accessible way to create clean and transparent charts - up to now. The 'tidycharts' package enables the user to generate charts compliant with International Business Communication Standards ('IBCS'). It means unified bar widths, colors, chart sizes, etc. Creating homogeneous reports has never been that easy! Additionally, users can apply semantic notation to indicate different data scenarios (plan, budget, forecast). What's more, it is possible to customize the charts by creating a personal color pallet with the possibility of switching to default options after the experiments. We wanted the package to be helpful in writing reports, so we also made joining charts in a one, clear image possible. All charts are generated in SVG format and can be shown in the 'RStudio' viewer pane or exported to HTML output of 'knitr'/'markdown'.

A Tidy Format Datasets of Dengue by Country

Provides a weekly, monthly, yearly summary of dengue cases by state/ province/ country.

A Tidy Interface for Simulating Multivariate Data

Provides pipe-friendly (%>%) wrapper functions for MASS::mvrnorm() to create simulated multivariate data sets with groups of variables with different degrees of variance, covariance, and effect size.

A Tidy Interface to the 'Walk Score' API

Easily collect walk scores, bike scores, and transit scores (where available) from the 'Walk Score' API < https://www.walkscore.com/professional/api.php>, a proprietary API that assigns locations a walkability score between 0 and 100.

Tidy Multiverse Analysis Made Simple

Extends 'multiverse' package (Sarma A., Kale A., Moon M., Taback N., Chevalier F., Hullman J., Kay M., 2021) , which allows users perform to create explorable multiverse analysis in R. This extension provides an additional level of abstraction to the 'multiverse' package with the aim of creating user friendly syntax to researchers, educators, and students in statistics. The 'mverse' syntax is designed to allow piping and takes hints from the 'tidyverse' grammar. The package allows users to define and inspect multiverse analysis using familiar syntax in R.