Shiny apps for automated data analysis, annotated outputs and human-readable interpretation in natural language. Designed especially for learners and applied researchers. Currently available methods: EDA, EDA with Python, Correlation Analysis, Principal Components Analysis, Confirmatory Factor Analysis.
Version: |
1.1.0 |
Imports: |
shiny, rmarkdown, data.table, readr, shinydisconnect, knitr, kableExtra, car, DDoutlier, energy, corrplot, ggplot2, gridExtra, reshape2 |
Suggests: |
MASS, boot, nortest, lmtest, DescTools, psych, Hmisc, PerformanceAnalytics, reticulate, fastDummies, semTools, semPlot, FactoMineR, FactoInvestigate, factoextra, rrcov, methods, parallel, graphics, imputeMissings, onewaytests |
Published: |
2021-11-17 |
Author: |
Denise Welsch
[aut, cre],
Berit Hunsdieck [ctb],
Omar Alhelal [ctb] |
Maintainer: |
Denise Welsch <denise.welsch at reyar.de> |
License: |
AGPL |
URL: |
https://statsomat.com |
NeedsCompilation: |
no |
SystemRequirements: |
For all functions resp. apps: pandoc, LaTeX. For
the edapy() function resp. Statsomat/EDAPY app: Python (>=3). |
CRAN checks: |
Statsomat results |