A forest plot that allows for
multiple confidence intervals per row,
custom fonts for each text element,
custom confidence intervals,
text mixed with expressions, and more.
The aim is to extend the use of forest plots beyond meta-analyses.
This is a more general version of the original 'rmeta' package's forestplot()
function and relies heavily on the 'grid' package.
testthat, abind, knitr, rmarkdown, rmeta

A forest plot that allows for
multiple confidence intervals per row,
custom fonts for each text element,
custom confidence intervals,
text mixed with expressions, and more.
The aim is to extend the use of forest plots beyond meta-analyses.
This is a more general version of the original 'rmeta' package's forestplot
function and relies heavily on the 'grid' package.

testthat, abind, knitr, rmarkdown, rmeta, dplyr, tidyr, rlang

dplyr, knitr, purrr, rmarkdown, rmeta, testthat, tibble,
tidyr, tidyselect, rlang

person(given="Alimu",
family = "Dayimu",
email = "ad938@cam.ac.uk",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-9998-7463"))
Create forest plot based on the layout of the data. Confidence interval in multiple columns by groups can be done easily. Editing plot, inserting/adding text, applying theme to the plot and much more.

rmarkdown, knitr, vdiffr, testthat (>= 3.0.0)

rmarkdown, knitr, vdiffr, testthat (>= 3.0.0), covr

Ecosystem and Canopy Structural Complexity Metrics from LiDAR
c(person("Jeff", "Atkins", email = "jwatkins6@vcu.edu",
role = c("aut", "cre")),
person("Gil", "Bohrer", role = "aut"),
person("Robert", "Fahey", role = "aut"),
person("Brady", "Hardiman", role = "aut"),
person("Chrisopher", "Gough", role = "aut"),
person("Timothy", "Morin", role = "aut"),
person("Atticus", "Stovall", role = "aut"),
person("Naupaka", "Zimmerman", role = "aut"))
Jeff Atkins [aut, cre],
Gil Bohrer [aut],
Robert Fahey [aut],
Brady Hardiman [aut],
Chrisopher Gough [aut],
Timothy Morin [aut],
Atticus Stovall [aut],
Naupaka Zimmerman [aut]
Provides a toolkit for calculating forest and canopy structural complexity metrics from
terrestrial LiDAR (light detection and ranging). References:  Atkins et al. In Review; Hardiman et al. 2013 <doi:10.3390/f4030537>;
Parker et al. 2004 <doi:10.1111/j.0021-8901.2004.00925.x>.