R/SSnegExp.R

In statforbiology: Tools for Data Analyses in Biology

#Negative exponential Function #################################################
negExp.fun <- function(predictor, a, c) {
                      x <- predictor
                      a * (1 - exp (- c * x))
}

negExp.Init <- function(mCall, LHS, data, ...) {
          xy <- sortedXyData(mCall[["predictor"]], LHS, data)
          x <-  xy[, "x"]; y <- xy[, "y"]
          plateau <- max(y) * 1.05        
          ## Linear regression on pseudo y values
          pseudoY <- log( 1 - (y / plateau ) )
          coefs <- coef( lm(pseudoY ~ x - 1) )
          a <- plateau
          c <- - coefs[1]
          value <- c(a, c)
          names(value) <- mCall[c("a", "c")]
          value
}

NLS.negExp <- selfStart(negExp.fun, negExp.Init, parameters=c("a", "c"))

DRC.negExp <-
function(fixed = c(NA, NA), names = c("a", "c"))
{
    ## Checking arguments
    numParm <- 2
    if (!is.character(names) | !(length(names) == numParm)) {stop("Not correct 'names' argument")}
    if (!(length(fixed) == numParm)) {stop("Not correct 'fixed' argument")}

    ## Fixing parameters (using argument 'fixed')
    notFixed <- is.na(fixed)
    parmVec <- rep(0, numParm)
    parmVec[!notFixed] <- fixed[!notFixed]

    ## Defining the non-linear function
    fct <- function(x, parm)
    {
        parmMat <- matrix(parmVec, nrow(parm), numParm, byrow = TRUE)
        parmMat[, notFixed] <- parm

        a <- parmMat[, 1]; c <- parmMat[, 2]
        a * (1 - exp (- c * x))
    }

    ## Defining self starter function
    ssfct <- function(dataf)
    {
        x <- dataf[, 1]
        y <- dataf[, 2]

        plateau <- max(y) * 1.05

        ## Linear regression on pseudo y values
        pseudoY <- log( 1 - (y / plateau ) )
        coefs <- coef( lm(pseudoY ~ x - 1) )
        a <- plateau
        c <- - coefs[1]

        return(c(a, c)[notFixed])
    }

    ## Defining names
    pnames <- names[notFixed]

    ## Defining derivatives
    deriv1 <- function(x, parms){
      
      parmMat <- matrix(parmVec, nrow(parms), 
                        numParm, byrow = TRUE)
      parmMat[, notFixed] <- parms
      
      # Approximation by using finite differences
      a <- as.numeric(parmMat[,1])
      b <- as.numeric(parmMat[,2])
      
      d1.1 <- negExp.fun(x, a, b)
      d1.2 <- negExp.fun(x, (a + 10e-7), b)
      d1 <- (d1.2 - d1.1)/10e-7
      
      d2.1 <- negExp.fun(x, a, b)
      d2.2 <- negExp.fun(x, a, (b + 10e-7) )
      d2 <- (d2.2 - d2.1)/10e-7
      
      
      cbind(d1, d2)[notFixed]
    }
    
    ## Defining the first derivative (in x=dose)
    derivx <- function(x, parm)
    {
      # print("qui")
      parmMat <- matrix(parmVec, nrow(parm), numParm, byrow = TRUE)
      parmMat[, notFixed] <- parm
      
      a <- as.numeric(parmMat[,1])
      b <- as.numeric(parmMat[,2])
      
      d1.1 <- negExp.fun(x, a, b)
      d1.2 <- negExp.fun((x + 10e-7), a, b)
      d1 <- (d1.2 - d1.1)/10e-7
      d1
    }

    ## Defining the ED function

    ## Defining the inverse function

    ## Defining descriptive text
    text <- "Negative exponential function"

    ## Returning the function with self starter and names
    returnList <- list(fct = fct, ssfct = ssfct, names = pnames,
                       text = text, noParm = sum(is.na(fixed)),
                       deriv1 = deriv1, derivx = derivx)

    class(returnList) <- "drcMean"
    invisible(returnList)
}

# Negative exponential cumulative distribution #############
negExpDist.fun <- function(predictor, c) {
    x <- predictor
    1 - exp (- c * x)
}

negExpDist.Init <- function(mCall, LHS, data, ...) {
    xy <- sortedXyData(mCall[["predictor"]], LHS, data)
    x <-  xy[, "x"]; y <- xy[, "y"]
    ## Linear regression on pseudo y values
    pseudoY <- log( 1 - y )
    coefs <- coef( lm(pseudoY ~ x - 1) )
    c <- - coefs[1]
    value <- c(c)
    names(value) <- mCall[c("c")]
    value
}

NLS.negExpDist <- selfStart(negExpDist.fun, negExpDist.Init, 
                            parameters=c("c"))

DRC.negExpDist <-
    function(fixed = NA, names = c("c"))
    {
        ## Checking arguments
        numParm <- 1
        if (!is.character(names) | !(length(names) == numParm)) {stop("Not correct 'names' argument")}
        if (!(length(fixed) == numParm)) {stop("Not correct 'fixed' argument")}
        
        ## Fixing parameters (using argument 'fixed')
        notFixed <- is.na(fixed)
        parmVec <- rep(0, numParm)
        parmVec[!notFixed] <- fixed[!notFixed]
        
        ## Defining the non-linear function
        fct <- function(x, parm)
        {
            parmMat <- matrix(parmVec, nrow(parm), numParm, byrow = TRUE)
            parmMat[, notFixed] <- parm
            
            c <- parmMat[, 1]
            1 - exp (- c * x)
        }
        
        ## Defining self starter function
        ssfct <- function(dataf)
        {
            x <- dataf[, 1]
            y <- dataf[, 2]
            
            ## Linear regression on pseudo y values
            pseudoY <- log( 1 - y )
            coefs <- coef( lm(pseudoY ~ x - 1) )
            c <- - coefs[1]
            
            return(c(c)[notFixed])
        }
        
        ## Defining names
        pnames <- names[notFixed]
        
        ## Defining derivatives
        deriv1 <- function(x, parms){
          parmMat <- matrix(parmVec, nrow(parms), 
                            numParm, byrow = TRUE)
          parmMat[, notFixed] <- parms
          
          # Approximation by using finite differences
          a <- as.numeric(parmMat[,1])
          
          d1.1 <- negExpDist.fun(x, a)
          d1.2 <- negExpDist.fun(x, (a + 10e-7))
          d1 <- (d1.2 - d1.1)/10e-7
          d1
          # cbind(d1)[notFixed]
        }
        
        ## Defining the first derivative (in x=dose)
        derivx <- function(x, parm)
        {
          parmMat <- matrix(parmVec, nrow(parm), numParm, byrow = TRUE)
          parmMat[, notFixed] <- parm
          
          a <- as.numeric(parmMat[,1])
          
          d1.1 <- negExpDist.fun(x, a)
          d1.2 <- negExpDist.fun((x + 10e-7), a)
          d1 <- (d1.2 - d1.1)/10e-7
          d1
        }
        
        ## Defining the ED function
        
        ## Defining the inverse function
        
        ## Defining descriptive text
        text <- "Negative exponential cumulative distribution function"
        
        ## Returning the function with self starter and names
        returnList <- list(fct = fct, ssfct = ssfct, names = pnames, 
                           text = text, noParm = sum(is.na(fixed)),
                           deriv1 = deriv1, derivx = derivx)
        
        class(returnList) <- "drcMean"
        invisible(returnList)
    }