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Managing Larger Data on a GitHub Repository
Because larger (> 50 MB) data files cannot easily be committed to git, a different approach is required to manage data associated with an analysis in a GitHub repository. This package provides a simple work-around by allowing larger (up to 2 GB) data files to piggyback on a repository as assets attached to individual GitHub releases. These files are not handled by git in any way, but instead are uploaded, downloaded, or edited directly by calls through the GitHub API. These data files can be versioned manually by creating different releases. This approach works equally well with public or private repositories. Data can be uploaded and downloaded programmatically from scripts. No authentication is required to download data from public repositories.
Interface with Google BigQuery with Shiny Compatibility
Interface with 'Google BigQuery', see < https://cloud.google.com/bigquery/> for more information. This package uses 'googleAuthR' so is compatible with similar packages, including 'Google Cloud Storage' (< https://cloud.google.com/storage/>) for result extracts.
Functions and Utilities for Jordan
Provides core functions and utilities for packages and other code developed by Jordan Mark Barbone.
A Simulation Tool to Determine the Required Sample Size for Repertory Grid Studies
Simulation tool to facilitate determination of required sample size to achieve category saturation for studies using multiple repertory grids in conjunction with content analysis.
Automatic Database Normalisation for Data Frames
Automatic normalisation of a data frame to third normal form, with the intention of easing the process of data cleaning. (Usage to design your actual database for you is not advised.) Originally inspired by the 'AutoNormalize' library for 'Python' by 'Alteryx' (< https://github.com/alteryx/autonormalize>), with various changes and improvements. Automatic discovery of functional or approximate dependencies, normalisation based on those, and plotting of the resulting "database" via 'Graphviz', with options to exclude some attributes at discovery time, or remove discovered dependencies at normalisation time.
Functions to Streamline Statistical Analysis and Reporting
Built upon popular R packages such as 'ggstatsplot' and 'ARTool', this collection offers a wide array of tools for simplifying reproducible analyses, generating high-quality visualizations, and producing 'APA'-compliant outputs. The primary goal of this package is to significantly reduce repetitive coding efforts, allowing you to focus on interpreting results. Whether you're dealing with ANOVA assumptions, reporting effect sizes, or creating publication-ready visualizations, this package makes these tasks easier.
Calibration of Scatterplot and Biplot Axes
Package for drawing calibrated scales with tick marks on (non-orthogonal) variable vectors in scatterplots and biplots. Also provides some functions for biplot creation and for multivariate analysis such as principal coordinate analysis.
Interface to 'LANDFIRE Product Service' API
Provides access to a suite of geospatial data layers for wildfire management, fuel modeling, ecology, natural resource management, climate, conservation, etc., via the 'LANDFIRE' (< https://www.landfire.gov/>) Product Service ('LFPS') API.
Google Search Console R Client
Provides an interface with the Google Search Console, formally called Google Webmaster Tools.
Fit, Simulate and Diagnose Exponential-Family Models for Networks
An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet suite of packages for network analysis. See Hunter, Handcock, Butts, Goodreau, and Morris (2008)