Closed schneiderpy closed 1 year ago
@ropensci-review-bot check srr
:heavy_check_mark: This package complies with > 50% of all standads and may be submitted.
I think we can approve this and proceed with https://github.com/ropensci/software-review/issues/559. @mpadge, I'll reopen that issue and close this one so we can proceed.
Submitting Author Name: Andreas Schneider Submitting Author Github Handle: !--author1-->@schneiderpy<!--end-author1-- Other Package Authors Github handles: (comma separated, delete if none) Repository: https://github.com/schneiderpy/concstats Submission type: Pre-submission Language: en
Scope
Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check an appropriate box below):
Data Lifecycle Packages
[ ] data retrieval
[ ] data extraction
[ ] data munging
[ ] data deposition
[ ] data validation and testing
[ ] workflow automation
[ ] version control
[ ] citation management and bibliometrics
[ ] scientific software wrappers
[ ] field and lab reproducibility tools
[ ] database software bindings
[ ] geospatial data
[ ] text analysis
Statistical Packages
[ ] Bayesian and Monte Carlo Routines
[ ] Dimensionality Reduction, Clustering, and Unsupervised Learning
[ ] Machine Learning
[ ] Regression and Supervised Learning
[x] Exploratory Data Analysis (EDA) and Summary Statistics
[ ] Spatial Analyses
[ ] Time Series Analyses
Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of: Exploring and/or summarizing a given market (or ecosystem) reflected by its given data (e.g. sales) to determine its structure regarding concentration, inequality, market share etc.
If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package? Yes, all EDA and general standards are incorporated into the code via srr-tags.
Who is the target audience and what are scientific applications of this package?
The goal of the concstats package is to offer a set of alternative and/or additional measures for researchers in social sciences and practitioners in institutions concerned with competition on a regular basis to better determine a given market structure and therefore reduce uncertainty with respect to a given market situation.
Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category? Some functions are already implemented in other R packages. The non-exhaustive summary below is by no means a description of each package. The Herfindahl Hirschman Index can be found in the hhi and the divseg packages. While the hhi package has just one function, neither of both packages offer a finite sample correction. However, almost none of these packages offer finite sample correction, with the exception of the ineq package. Other functions are new implementations in R, e.g. Dominance Index, Palma ratio, Stenbacka Index, GRS measure, and the dual of the Herfindahl Hirschman Index.
(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research? Not applicable
Any other questions or issues we should be aware of?: Imports (dependencies) dplyr and readr, which are only used in data.R file