#' @name ge_var
#' @aliases ge_var
#' @title Genotype by Environment Interaction Variances
#' @description Calcuates Genotype by Environment Interaction Variances
#'
#' @param .data data.frame
#' @param .y Response Variable
#' @param .gen Genotypes Factor
#' @param .env Environment Factor
#'
#' @return Genotype by Environment Interaction Variances
#'
#' @author
#' \enumerate{
#' \item Muhammad Yaseen (\email{myaseen208@@gmail.com})
#' }
#'
#' @references
#' Crossa, J., Perez-Elizalde, S., Jarquin, D., Cotes, J.M., Viele, K., Liu, G., and Cornelius, P.L. (2011)
#' Bayesian Estimation of the Additive Main Effects and Multiplicative Interaction Model
#' \emph{Crop Science}, \strong{51}, 1458–1469.
#' (\href{https://dl.sciencesocieties.org/publications/cs/abstracts/51/4/1458?access=0&view=pdf}{doi: 10.2135/cropsci2010.06.0343})
#'
#' @import rlang
#' @import tidyr
#' @importFrom dplyr select group_by count
#' @importFrom magrittr %>%
#' @importFrom stats var
#'
#' @export
#'
#' @examples
#'
#' data(Maiz)
#' ge_var(
#' .data = Maiz
#' , .y = y
#' , .gen = entry
#' , .env = site
#' )
#'
#'
if(getRversion() >= "2.15.1"){
utils::globalVariables(
c(
"Gen"
, "Env"
, "Y"
, "GEVar"
, "."
)
)
}
ge_var <- function(.data, .y, .gen, .env) {
UseMethod("ge_var")
}
#' @export
#' @rdname ge_var
ge_var.default <-
function(.data, .y, .gen, .env){
.y <- deparse(substitute(.y))
.gen <- deparse(substitute(.gen))
.env <- deparse(substitute(.env))
df1 <- tibble::as_tibble(data.frame(
Env = factor(.data[[.env]])
, Gen = factor(.data[[.gen]])
, Y = .data[[.y]]
))
ge_variances <-
df1 %>%
dplyr::group_by(Gen, Env) %>%
dplyr::summarise(GEVar = var(Y)) %>%
tidyr::spread(key = Env, value = GEVar) %>%
# magrittr::set_rownames(.$Gen) %>%
dplyr::ungroup() %>%
dplyr::select(- Gen) %>%
as.matrix()
return(list(
ge_variances = ge_variances
))
}
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