close

Showing 7 of total 7 results (show query)

vincentarelbundock

modelsummary:Summary Tables and Plots for Statistical Models and Data: Beautiful, Customizable, and Publication-Ready

Create beautiful and customizable tables to summarize several statistical models side-by-side. Draw coefficient plots, multi-level cross-tabs, dataset summaries, balance tables (a.k.a. "Table 1s"), and correlation matrices. This package supports dozens of statistical models, and it can produce tables in HTML, LaTeX, Word, Markdown, PDF, PowerPoint, Excel, RTF, JPG, or PNG. Tables can easily be embedded in 'Rmarkdown' or 'knitr' dynamic documents. Details can be found in Arel-Bundock (2022) <doi:10.18637/jss.v103.i01>.

Maintained by Vincent Arel-Bundock. Last updated 1 months ago.

927 stars 13.39 score 6.2k scripts 2 dependents

michaeltopper1

panelsummary:Create Publication-Ready Regression Tables with Panels

Create an automated regression table that is well-suited for models that are estimated with multiple dependent variables. 'panelsummary' extends 'modelsummary' (Arel-Bundock, V. (2022) <doi:10.18637/jss.v103.i01>) by allowing regression tables to be split into multiple sections with a simple function call. Utilize familiar arguments such as fmt, estimate, statistic, vcov, conf_level, stars, coef_map, coef_omit, coef_rename, gof_map, and gof_omit from 'modelsummary' to clean the table, and additionally, add a row for the mean of the dependent variable without external manipulation.

Maintained by Michael Topper. Last updated 2 years ago.

2 stars 5.39 score 81 scripts

jobnmadu

Dyn4cast:Dynamic Modeling and Machine Learning Environment

Estimates, predict and forecast dynamic models as well as Machine Learning metrics which assists in model selection for further analysis. The package also have capabilities to provide tools and metrics that are useful in machine learning and modeling. For example, there is quick summary, percent sign, Mallow's Cp tools and others. The ecosystem of this package is analysis of economic data for national development. The package is so far stable and has high reliability and efficiency as well as time-saving.

Maintained by Job Nmadu. Last updated 17 days ago.

data-scienceequal-lenght-forecastforecastingknotsmachine-learningnigeriapredictionregression-modelsspline-modelsstatisticstime-series

4 stars 5.03 score 38 scripts

rrprf

tablesgg:Presentation-Quality Tables, Displayed Using 'ggplot2'

Presentation-quality tables are displayed as plots on an R graphics device. Although there are other packages that format tables for display, this package is unique in combining two features: (a) It is aware of the logical structure of the table being presented, and makes use of that for automatic layout and styling of the table. This avoids the need for most manual adjustments to achieve an attractive result. (b) It displays tables using 'ggplot2' graphics. Therefore a table can be presented anywhere a graph could be, with no more effort. External software such as LaTeX or HTML or their viewers is not required. The package provides a full set of tools to control the style and appearance of tables, including titles, footnotes and reference marks, horizontal and vertical rules, and spacing of rows and columns. Methods are included to display matrices; data frames; tables created by R's ftable(), table(), and xtabs() functions; and tables created by the 'tables' and 'xtable' packages. Methods can be added to display other table-like objects. A vignette is included that illustrates usage and options available in the package.

Maintained by Richard Raubertas. Last updated 4 years ago.

3.70 score 5 scripts

cran

MRCV:Methods for Analyzing Multiple Response Categorical Variables (MRCVs)

Provides functions for analyzing the association between one single response categorical variable (SRCV) and one multiple response categorical variable (MRCV), or between two or three MRCVs. A modified Pearson chi-square statistic can be used to test for marginal independence for the one or two MRCV case, or a more general loglinear modeling approach can be used to examine various other structures of association for the two or three MRCV case. Bootstrap- and asymptotic-based standardized residuals and model-predicted odds ratios are available, in addition to other descriptive information. Statisical methods implemented are described in Bilder et al. (2000) <doi:10.1080/03610910008813665>, Bilder and Loughin (2004) <doi:10.1111/j.0006-341X.2004.00147.x>, Bilder and Loughin (2007) <doi:10.1080/03610920600974419>, and Koziol and Bilder (2014) <https://journal.r-project.org/articles/RJ-2014-014/>.

Maintained by Chris Bilder. Last updated 5 months ago.

2.48 score

cran

IGoRRR:A Shiny Interface for Simple Data Management

Launches a shiny application generating code to view tables in several ways, import/export tables, modify tables, make some basic graphics. 'IGoR' is a graphic user interface designed to help beginners using simple functions around table management and exploration. Inspired by 'Rcmdr', 'IGoR' is a code generator that, with simple inputs under a Shiny application, provides R code mainly built around the 'tidyverse' or some packages in the direct line of the Mosaic project: the 'rio' and 'ggformula' packages. The generated code doesn't depend on IGoR and can be manually modified by the user or copied elsewhere.

Maintained by Jean-Luc Lipatz. Last updated 2 years ago.

1.00 score

wilsonrp

T2Qv:Control Qualitative Variables

Covers k-table control analysis using multivariate control charts for qualitative variables using fundamentals of multiple correspondence analysis and multiple factor analysis. The graphs can be shown in a flat or interactive way, in the same way all the outputs can be shown in an interactive shiny panel.

Maintained by Wilson Rojas-Preciado. Last updated 1 years ago.

1.00 score

: