predict can now return standard errors and
prediction intervals.x-axis of the plot.plot when doses were not previously
sorted.x-axis of the plot when
data contained zeros.plot_data to FALSE (default
TRUE).It is now possible to fit models using either the log-dose or the dose scale.
To accommodate this extension it was necessary to change the default model parameterization, which now follows that of the Emax model (Macdougall, 2006).
Briefly, the 5-parameter logistic function is now defined as
alpha + delta / (1 + nu * exp(-eta * (x - phi)))^(1 / nu)Parameter alpha is the value of the function when
x approaches -Inf. Parameter
delta is the (signed) height of the curve. Parameter
eta > 0 represents the steepness (growth rate) of the
curve. Parameter phi is related to the mid-value of the
function. Parameter nu affects near which asymptote maximum
growth occurs.
Similarly, the newly implemented log-logistic function (when
x >= 0) is defined as
alpha + delta * (x^eta / (x^eta + nu * phi^eta))^(1 / nu)Check the vignette (vignette("drda", package = "drda"))
or the help page (help(drda)) to know more about the
available models.
Here is a change log from previous version:
effective_dose function for estimating
effective doses.First public release.