#' Fit the model for Weibull distribution of the expected load with shift of response values
#'
#' @param data A data frame
#' @param response A character string. Response (e.g. "worm_count")
#' @param hybridIndex A vector of points representing the index used as x axis
#' @param paramBounds A vector of parameters (upper, lower, start) for the optimisation
#' @param config A list containing an optimizer (default: "optimx"), a method (default "bobyqa", "L-BFGS-B") and a control (default list(follow.on = TRUE))
#' @return A fit for binomial distributed data
#' @export
# no difference between subspecies, no hybrid effect
FitBasicNoAlphaWeibullShifted <-
function(data, response, hybridIndex, paramBounds, config){
print("Fitting model basic without alpha")
data$response <- data[[response]] # little trick
HI <- data[[hybridIndex]]
start <- list(L1 = paramBounds[["L1start"]],
myshape = paramBounds[["myshapeStart"]],
SHIFT = paramBounds[["SHIFTStart"]])
fit <- bbmle::mle2(
response ~ dweibull(shape = myshape,
scale = (MeanLoad(L1, L1, 0, HI)+ SHIFT) /
gamma(1 + (1 / myshape))),
data = data,
start = start,
lower = c(L1 = paramBounds[["L1LB"]],
myshape = paramBounds[["myshapeLB"]],
SHIFT = paramBounds[["SHIFTLB"]]),
upper = c(L1 = paramBounds[["L1UB"]],
myshape = paramBounds[["myshapeUB"]],
SHIFT = paramBounds[["SHIFTUB"]]),
optimizer = config$optimizer,
method = config$method,
control = config$control)
printConvergence(fit)
return(fit)
}
# no difference between subspecies, flexible hybrid effect
FitBasicAlphaWeibullShifted <-
function(data, response, hybridIndex, paramBounds, config){
print("Fitting model basic with alpha")
data$response <- data[[response]] # little trick
HI <- data[[hybridIndex]]
start <- list(L1 = paramBounds[["L1start"]],
alpha = paramBounds[["alphaStart"]],
myshape = paramBounds[["myshapeStart"]],
SHIFT = paramBounds[["SHIFTStart"]])
fit <- bbmle::mle2(
response ~ dweibull(shape = myshape,
scale = (MeanLoad(L1, L1, alpha, HI)+ SHIFT) /
gamma(1 + (1 / myshape))),
data = data,
start = start,
lower = c(L1 = paramBounds[["L1LB"]],
alpha = paramBounds[["alphaLB"]],
myshape = paramBounds[["myshapeLB"]],
SHIFT = paramBounds[["SHIFTLB"]]),
upper = c(L1 = paramBounds[["L1UB"]],
alpha = paramBounds[["alphaUB"]],
myshape = paramBounds[["myshapeUB"]],
SHIFT = paramBounds[["SHIFTUB"]]),
optimizer = config$optimizer,
method = config$method,
control = config$control)
printConvergence(fit)
return(fit)
}
# difference between subspecies, flexible hybrid effect
FitAdvancedNoAlphaWeibullShifted <-
function(data, response, hybridIndex, paramBounds, config){
print("Fitting model advanced without alpha")
data$response <- data[[response]]
HI <- data[[hybridIndex]]
start <- list(L1 = paramBounds[["L1start"]],
L2 = paramBounds[["L2start"]],
myshape = paramBounds[["myshapeStart"]],
SHIFT = paramBounds[["SHIFTStart"]])
fit <- bbmle::mle2(
response ~ dweibull(shape = myshape,
scale = (MeanLoad(L1, L2, 0, HI)+ SHIFT) /
gamma(1 + (1 / myshape))),
data = data,
start = start,
lower = c(L1 = paramBounds[["L1LB"]],
L2 = paramBounds[["L2LB"]],
myshape = paramBounds[["myshapeLB"]],
SHIFT = paramBounds[["SHIFTLB"]]),
upper = c(L1 = paramBounds[["L1UB"]],
L2 = paramBounds[["L2UB"]],
myshape = paramBounds[["myshapeUB"]],
SHIFT = paramBounds[["SHIFTUB"]]),
optimizer = config$optimizer,
method = config$method,
control = config$control)
printConvergence(fit)
return(fit)
}
# difference between subspecies, flexible hybrid effect
FitAdvancedAlphaWeibullShifted <-
function(data, response, hybridIndex, paramBounds, config){
print("Fitting model advanced with alpha")
data$response <- data[[response]]
HI <- data[[hybridIndex]]
start <- list(L1 = paramBounds[["L1start"]],
L2 = paramBounds[["L2start"]],
alpha = paramBounds[["alphaStart"]],
myshape = paramBounds[["myshapeStart"]],
SHIFT = paramBounds[["SHIFTStart"]])
fit <- bbmle::mle2(
response ~ dweibull(shape = myshape,
scale = (MeanLoad(L1, L2, alpha, HI) + SHIFT) /
gamma(1 + (1 / myshape))),
data = data,
start = start,
lower = c(L1 = paramBounds[["L1LB"]],
L2 = paramBounds[["L2LB"]],
alpha = paramBounds[["alphaLB"]],
myshape = paramBounds[["myshapeLB"]],
SHIFT = paramBounds[["SHIFTLB"]]),
upper = c(L1 = paramBounds[["L1UB"]],
L2 = paramBounds[["L2UB"]],
alpha = paramBounds[["alphaUB"]],
myshape = paramBounds[["myshapeUB"]],
SHIFT = paramBounds[["SHIFTUB"]]),
optimizer = config$optimizer,
method = config$method,
control = config$control)
printConvergence(fit)
return(fit)
}
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