R/data_microarray.R

In FPZhang2015/CCR: Fit the correspondence curve regression

    #' @title microarray dataset
    #' @description A dataset containing the scores of two platforms
    #' and 2 labs.
    #' The variables are as follows:
    #'
    #' @format A data frame with 800 rows and 2 variables
    #' \describe{
    #'   \item{y1}{the scores of replicate 1}
    #'   \item{y2}{the scores of replicate 2}
    #'   \item{x1}{the factor variabel of platforms}
    #'   \item{x2}{the factor variabel of labs}
    #' }
    #' @source Irizarry et al. (2005).
    #' @docType data
    #' @keywords data_microarray
    #' @usage data(data_microarray)
    #'
    #' @references
    #' \itemize{
    #' \item Irizarry, R. A., Warren, D., Spencer, F., Kim, I. F., Biswal,
    #' S., Frank, B. C., Gabrielson, E., Garcia, J. G., Geoghegan,
    #' J., Germino, G., et al. (2005).
    #' Multiple-laboratory comparison of microarray platforms.
    #' Nature Methods 2, 345-350.
    #'   }
    #' 
    #' \examples{
    #' \dontrun{
    #' data(data_microarray)
    #' summary(data_microarray)
    #' 
    #' ## with slope without ht
    #' par.ini = c(-1, 1, 0.1, 0.1)    # initial value
    #' fit <- ccrFit(cbind(y1,y2)~x1+x2, data = data_microarray,
    #'               is.slope = TRUE, is.ht = FALSE, par.ini = par.ini,
    #'               method = 'logitlogit')
    #'
    #'## with slope with ht, including iteractions
    #' par.ini = c(-1, 0.1, 0.1, 0, 1,  0.1, 0.1, 0)
    #' fit <- ccrFit(cbind(y1,y2)~x1*x2, data = data_microarray,
    #'               is.slope = TRUE, is.ht = TRUE, par.ini = par.ini,
    #'               method = 'logitlogit')
    #' }}