ExpFamilyPCA.jl vs JASP
ExpFamilyPCA.jl
sisl.github.io
JASP
jasp-stats.orgSide by side
| Figure | ExpFamilyPCA.jl | JASP |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Statistical Analysis Software | 7.4 (#75) | 8.7 (#8) |
| Data import formats | Julia AbstractMatrix data | .csv, .tsv, .txt, .sav, .zsav, .por, .sas7bda, .sas7bcatt, .xpt, .ods, .xls, .xlsx, .dta, .rdata, .rds, .mwx, .mpx |
| Free plan | Yes | Yes |
| License | The GitHub repository identifies the project as MIT licensed. | JASP is released under the GNU Affero GPL v3 license, which the download page says guarantees it will always be free. |
| Purpose | ExpFamilyPCA.jl is a Julia package for exponential family principal component analysis, a generalization of PCA for non-Gaussian data. | JASP is a cross-platform statistical software program with a graphical interface for conducting statistical analyses without programming. |
| Scripting support | Yes | Yes |
Plans
In their own words
ExpFamilyPCA.jl
ExpFamilyPCA.jl has no write-up on Specifiction yet; its figures are above.
JASP
JASP is free desktop statistical software for Linux, macOS, and Windows, designed to run analyses through a graphical interface without programming. It offers standard procedures in both frequentist and Bayesian forms, with modules for descriptives, t-tests, ANOVA, regression, meta-analysis, machine learning, structural equation modeling, survival, and time series. The spreadsheet-style interface uses drag-and-drop controls, and results update as analysis options change. JASP produces APA-formatted output, including tables that can be copied into a word processor, and lets users annotate results. It is integrated with the Open Science Framework and can run without an internet connection. Import formats include CSV, TSV, text, SPSS, SAS, Excel, Stata, and R files, among others. JASP requires a 64-bit operating system, about 4 GB of free disk space, and at least 4 GB of RAM; 8 GB is recommended, with 16 GB or more suggested for large datasets. Android, iOS, and iPadOS devices are not supported. The software uses the GNU Affero GPL v3 license, and its download page says it will remain free.