Package: ggtrendline 1.0.3

ggtrendline: Add Trendline and Confidence Interval to 'ggplot'

Add trendline and confidence interval of linear or nonlinear regression model and show equation to 'ggplot' as simple as possible. For a general overview of the methods used in this package, see Ritz and Streibig (2008) <doi:10.1007/978-0-387-09616-2> and Greenwell and Schubert Kabban (2014) <doi:10.32614/RJ-2014-009>.

Authors:Weiping Mei [aut, cre, cph], Guangchuang Yu [aut], Brandon M. Greenwell [aut], Jiangshan Lai [ctb], Zhendu Mao [ctb], Yu Umezawa [ctb], Jun Zeng [ctb], Jun Wang [ctb]

ggtrendline_1.0.3.tar.gz
ggtrendline_1.0.3.zip(r-4.5)ggtrendline_1.0.3.zip(r-4.4)ggtrendline_1.0.3.zip(r-4.3)
ggtrendline_1.0.3.tgz(r-4.4-any)ggtrendline_1.0.3.tgz(r-4.3-any)
ggtrendline_1.0.3.tar.gz(r-4.5-noble)ggtrendline_1.0.3.tar.gz(r-4.4-noble)
ggtrendline_1.0.3.tgz(r-4.4-emscripten)ggtrendline_1.0.3.tgz(r-4.3-emscripten)
ggtrendline.pdf |ggtrendline.html✨
ggtrendline/json (API)

# Install 'ggtrendline' in R:

install.packages('ggtrendline', repos = c('https://phdmeiwp.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/phdmeiwp/ggtrendline/issues

On CRAN:

4.46 score 25 stars 23 scripts 303 downloads 9 exports 28 dependencies

Last updated 3 years agofrom:95ad61ac29. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 29 2024
R-4.5-win	OK	Oct 29 2024
R-4.5-linux	OK	Oct 29 2024
R-4.4-win	OK	Oct 29 2024
R-4.4-mac	OK	Oct 29 2024
R-4.3-win	OK	Oct 29 2024
R-4.3-mac	OK	Oct 29 2024

Exports:ggtrendline predFit SSexp2P SSexp3P SSpower2P SSpower3P stat_eq stat_rrp trendline_sum

Dependencies:cli colorspace fansi farver ggplot2 glue gtable isoband labeling lattice lifecycle magrittr MASS Matrix mgcv munsell nlme pillar pkgconfig R6 RColorBrewer rlang scales tibble utf8 vctrs viridisLite withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Add Trendline and Confidence Interval to 'ggplot'	ggtrendline
Predictions from a Fitted Model	predFit predFit.default predFit.nls
Self-Starting Nls 'exp2P' Regression Model	SSexp2P
Self-Starting Nls 'exp3P' Regression Model	SSexp3P
Self-Starting Nls 'power2P' Regression Model	SSpower2P
Self-Starting Nls 'power3P' Regression Model	SSpower3P
Add Equation to 'ggplot'	stat_eq
Add R square and P-value to 'ggplot'	stat_rrp
Summarized Results of Each Regression Model	trendline_sum