# R/logiGrowth.r In OnofriAndreaPG/aomisc: Statistical methods for the agricultural sciences

```"DRClogiGrowth.1" <-
function(fixed = c(NA, NA, NA), names = c("a", "b", "c"))
{
## Checking arguments
numParm <- 3
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]; b <- parmMat[, 3]; c <- parmMat[, 2]
a / (1 + exp(- b * x + c))
}

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

a <- max(y) * 1.05

## Linear regression on pseudo y values
pseudoY <- log( (a / y ) - 1 )
coefs <- coef( lm(pseudoY ~ x) )
b <- - coefs[2]
c <- coefs[1]

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

## Defining names
pnames <- names[notFixed]

## Defining derivatives

## Defining the ED function

## Defining the inverse function

## Defining descriptive text
text <- "Logistic Growth Model - 1"

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

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

"DRClogiGrowth.2" <-
function(fixed = c(NA, NA, NA), names = c("a", "b", "c"))
{
## Checking arguments
numParm <- 3
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]; b <- parmMat[, 3]; c <- parmMat[, 2]
a / (1 + b * exp(- c * x))
}

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

a <- max(y) * 1.05

## Linear regression on pseudo y values
pseudoY <- log( (a / y ) - 1 )
coefs <- coef( lm(pseudoY ~ x) )
c <- - coefs[2]
b <- exp(coefs[1])

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

## Defining names
pnames <- names[notFixed]

## Defining derivatives

## Defining the ED function

## Defining the inverse function

## Defining descriptive text
text <- "Logistic Growth Model - 2"

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

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

"DRClogiGrowth.3" <-
function(fixed = c(NA, NA, NA), names = c("init", "m", "plateau"))
{
## Checking arguments
numParm <- 3
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

W0 <- parmMat[, 1]; Wf <- parmMat[, 3]; m <- parmMat[, 2]
W0 * Wf / (W0 + (Wf - W0) * exp( - m * 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( (plateau / (y + 0.0001) ) - 1 )
coefs <- coef( lm(pseudoY ~ x) )
b <- exp(coefs[1])
init <- plateau / (1 + b)
m <- - coefs[2]

return(c(init, m, plateau)[notFixed])
}

## Defining names
pnames <- names[notFixed]

## Defining derivatives

## Defining the ED function

## Defining the inverse function

## Defining descriptive text
text <- "Logistic Growth Model - 3"

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

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

"DRClogiGrowth.4" <-
function(fixed = c(NA, NA, NA), names = c("m", "plateau", "t50"))
{
## Checking arguments
numParm <- 3
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

m <- parmMat[, 1]; plateau <- parmMat[, 2]; t50 <- parmMat[, 3]
plateau / (1 + exp(- m * (x - t50)))
}

## 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( (plateau / (y + 0.0001) ) - 1 )
coefs <- coef( lm(pseudoY ~ x) )
m <- - coefs[2]
t50 <- coefs[1] / m

return(c(m, plateau, t50)[notFixed])
}

## Defining names
pnames <- names[notFixed]

## Defining derivatives

## Defining the ED function

## Defining the inverse function

## Defining descriptive text
text <- "Logistic Growth Model - 4"

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

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

"DRCfpl" <-
function(fixed = c(NA, NA, NA, NA), names = c("c", "d", "mu", "sigma"))
{
## Checking arguments
numParm <- 4
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]; d <- parmMat[, 2]; mu <- parmMat[, 3]; sigma <- parmMat[, 3]
c + (d - c) / (1 + exp((mu-x)/sigma))
}

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

d <- max(y) * 1.05
c <- min(y) - 0.0001
## Linear regression on pseudo y values
pseudoY <- log((d - y) / (y - c ))
coefs <- coef( lm(pseudoY ~ x) )
m <- - coefs[2]
mu <- coefs[1] / m
sigma <- 1/m

return(c(c, d, mu, sigma)[notFixed])
}

## Defining names
pnames <- names[notFixed]

## Defining derivatives

## Defining the ED function

## Defining the inverse function

## Defining descriptive text
text <- "Logistic function (4 parms)"

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

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

"logLogisticD.2" <-
function(fixed = c(NA, NA), names = c("a", "b"))
{
## 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]; b <- parmMat[, 2]
1 - (1 / (1 + exp(a + b*log(x))))
}

## Defining self starter function
ssfct <- function(dataf)
{
x <- dataf[, 1]
y <- 1 - dataf[, 2] - 0.000001

## Linear regression on pseudo y values
pseudoY <- log( y / (1-y ))
coefs <- coef( lm(pseudoY ~ x) )
b <- coefs[2]
a <- coefs[1]

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

## Defining names
pnames <- names[notFixed]

## Defining derivatives

## Defining the ED function

## Defining the inverse function

## Defining descriptive text

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

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

"logLogisticD.3" <-
function(fixed = c(NA, NA, NA), names = c("plateau","a", "b"))
{
## Checking arguments
numParm <- 3
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

plateau <- parmMat[,1]; a <- parmMat[, 2]; b <- parmMat[, 3]
1 - (plateau / (1 + exp(a + b*log(x))))
}

## Defining self starter function
ssfct <- function(dataf)
{
x <- dataf[, 1]
y <- 1 - dataf[, 2] + 0.000001

## Linear regression on pseudo y values
plateau <- max(y) * 1.05

pseudoY <- log( y / (1-y))
coefs <- coef( lm(pseudoY ~ x) )
b <- coefs[2]
a <- coefs[1]

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

## Defining names
pnames <- names[notFixed]

## Defining derivatives

## Defining the ED function

## Defining the inverse function

## Defining descriptive text
text <- "Traditional log-Logistic model with upper asymptote"

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

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

"logLogistic.2" <-
function(fixed = c(NA, NA), names = c("a", "b"))
{
## 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]; b <- parmMat[, 2]
1 / (1 + exp(-(a + b*log(x))))
}

## Defining self starter function
ssfct <- function(dataf)
{
x <- dataf[, 1]
y <- dataf[, 2] + 0.000001

## Linear regression on pseudo y values
pseudoY <- log( y / (1-y) )
coefs <- coef( lm(pseudoY ~ x) )
b <- coefs[2]
a <- coefs[1]

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

## Defining names
pnames <- names[notFixed]

## Defining derivatives

## Defining the ED function

## Defining the inverse function

## Defining descriptive text

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

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

"logLogistic.3" <-
function(fixed = c(NA, NA, NA), names = c("plateau","a", "b"))
{
## Checking arguments
numParm <- 3
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

plateau <- parmMat[,1]; a <- parmMat[, 2]; b <- parmMat[, 3]
plateau / (1 + exp(-(a + b*log(x))))
}

## Defining self starter function
ssfct <- function(dataf)
{
x <- dataf[, 1]
y <- dataf[, 2] + 0.000001

## Linear regression on pseudo y values
plateau <- max(y) * 1.05

pseudoY <- log( y / (plateau - y) )
coefs <- coef( lm(pseudoY ~ x) )
b <- coefs[2]
a <- coefs[1]

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

## Defining names
pnames <- names[notFixed]

## Defining derivatives

## Defining the ED function

## Defining the inverse function

## Defining descriptive text
text <- "Traditional log-Logistic model with upper asymptote"

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

class(returnList) <- "drcMean"
invisible(returnList)
}
```
OnofriAndreaPG/aomisc documentation built on Feb. 2, 2023, 12:13 p.m.