c(
person("Yuhui", "Yao", role = c("aut", "cre"), email = "yyao17@cba.ua.edu"),
person("Subha", "Chakraborti", role = c("ctb"), email = "schakrab@cba.ua.edu"),
person("Tyler", "Thomas", role = c("ctb"), email = "tjthomas7@crimson.ua.edu"),
person("Jason", "Parton", role = c("ctb"), email = "jmparton@cba.ua.edu"),
person("Xin", "Yang", role = c("ctb"), email = "xyang15@cba.ua.edu")
)
The purpose of 'PH1XBAR' is to build a Phase I Shewhart control chart for the basic Shewhart, the variance components and the ARMA models in R for subgrouped and individual data. More details can be found: Yao and Chakraborti (2020) <doi: 10.1002/qre.2793>, and Yao and Chakraborti (2021) <doi: 10.1080/08982112.2021.1878220>.
Yuhui Yao [aut, cre],
Subha Chakraborti [ctb],
Tyler Thomas [ctb],
Jason Parton [ctb],
Xin Yang [ctb]

c(
person("Yuhui", "Yao", role = c("aut", "cre"), email = "yyao17@cba.ua.edu"),
person("Subha", "Chakraborti", role = c("ctb"), email = "schakrab@cba.ua.edu"),
person("Tyler", "Thomas", role = c("ctb"), email = "tjthomas7@crimson.ua.edu")
)
The purpose of 'PH1XBAR' is to build a Phase I Shewhart X-Bar control chart with variance components model in R. More details can be found: Yao and Chakraborti (2020) <doi: 10.1002/qre.2793>, and Yao and Chakraborti (2021) <doi: 10.1080/08982112.2021.1878220>.
Yuhui Yao [aut, cre],
Subha Chakraborti [ctb],
Tyler Thomas [ctb]

Provides functions to estimate the size-controlled phenotypic integration index, a novel method by Torices & Méndez (2014) to solve problems due to individual size when estimating integration (namely, larger individuals have larger components, which will drive a correlation between components only due to resource availability that might overestimate the observed measures of integration). In addition, the package also provides the classical estimation by Wagner (1984) and a bootstrapping method to test the significance of both integration indices.

Provides functions to estimate the size-controlled phenotypic integration index, a novel method by Torices & Méndez (2014) to solve problems due to individual size when estimating integration (namely, larger individuals have larger components, which will drive a correlation between components only due to resource availability that might obscure the observed measures of integration). In addition, the package also provides the classical estimation by Wagner (1984), a bootstrapping method to calculate confidence intervals and a significance test for both integration indices.