R/audps.R

In myaseen208/agricolae: Statistical Procedures for Agricultural Research

#' @name    audps
#' @aliases audps
#' @title The Area Under the Disease Progress Stairs
#' @description
#' A better estimate of disease progress is the area under the disease progress
#' stairs (AUDPS). The AUDPS approach improves the estimation of disease
#' progress by giving a weight closer to optimal to the first and last
#' observations.
#' 
#' AUDPS. For the illustration one considers three evaluations (14, 21 and 28
#' days) and percentage of damage in the plant 40, 80 and 90 (interval between
#' dates of evaluation 7 days).  AUDPS = 1470.  The evaluations can be at
#' different interval.  AUDPS= sum( rectangle area by interval in times
#' evaluation ) see example.
#' 
#' @param evaluation Table of data of the evaluations: Data frame
#' @param dates Vector of dates corresponding to each evaluation
#' @param type relative, absolute
#' 
#' @return \strong{Vector} with relative or absolute audps.
#' 
#' 
#' @author
#' \enumerate{
#'          \item Felipe de Mendiburu (\email{fmendiburu@@lamolina.edu.pe})
#'          \item Muhammad Yaseen (\email{myaseen208@@gmail.com})
#'          }
#'          
#' @references Ivan Simko, and Hans-Peter Piepho, (2012). The area under the
#' disease progress stairs: Calculation, advantage, and application.
#' Phytopathology 102:381- 389.
#' 
#' @keywords manip
#' 
#' @export
#' 
#' @examples
#' 
#' library(agricolae)
#' dates<-c(14,21,28) # days
#' # example 1: evaluation - vector
#' evaluation<-c(40,80,90)
#' audps(evaluation,dates)
#' audps(evaluation,dates,"relative")
#' x<-seq(10.5,31.5,7)
#' y<-c(40,80,90,90)
#' plot(x,y,"s",ylim=c(0,100),xlim=c(10,32),axes=FALSE,col="red" ,ylab="",xlab="")
#' title(cex.main=0.8,main="Absolute or Relative AUDPS\nTotal area=(31.5-10.5)*100=2100",
#' ylab="evaluation",xlab="dates" )
#' points(x,y,type="h")
#' z<-c(14,21,28)
#' points(z,y[-3],col="blue",lty=2,pch=19)
#' points(z,y[-3],col="blue",lty=2,pch=19)
#' axis(1,x,pos=0)
#' axis(2,c(0,40,80,90,100),las=2)
#' text(dates,evaluation+5,dates,col="blue")
#' text(14,20,"A = (17.5-10.5)*40",cex=0.8)
#' text(21,40,"B = (24.5-17.5)*80",cex=0.8)
#' text(28,60,"C = (31.5-24.5)*90",cex=0.8)
#' text(14,95,"audps = A+B+C = 1470")
#' text(14,90,"relative = audps/area = 0.7")
#' # It calculates audpc absolute
#' absolute<-audps(evaluation,dates,type="absolute")
#' print(absolute)
#' rm(evaluation, dates, absolute)
#'
audps <- 
  function(evaluation, dates, type = "absolute"){
    UseMethod("audps")
  }

#' @export
#' @rdname audps


audps.default <- 
function(evaluation, dates, type = "absolute") {
if(!(is.matrix(evaluation) | is.data.frame(evaluation))){
evaluation <- rbind(evaluation)
}
n<-length(dates)
k<-ncol(evaluation)
if (n!=k) {
cat("Error:\nThe number of dates of evaluation \nmust agree with the number of evaluations\n")
return()
}
d1<-(dates[2]-dates[1])/2
d2<-(dates[n]-dates[n-1])/2
d<-d1+d2+dates[n]-dates[1]
audps<-0
for (i in 1:(n-1)) {
audps <- audps + evaluation[,i]*(dates[i+1]-dates[i])
}
audps <- audps + evaluation[,n]*(dates[n]-dates[n-1])
if (type =="relative" ) audps <- audps/(d*100)
if (type =="absolute" | type =="relative" ) {
return(audps)
}
else cat("Error: type is 'absolute' or 'relative'\n\n")
}