# Release Notes

## drda 2.0.4

- Fitted values and residuals have now the correct length even when
there are zero weights.
- Fixed a bug when calculating the variance for models with fixed
parameters.
- Function
`predict`

can now return standard errors and
prediction intervals.
- Upgraded Roxygen2 to version 7.3.2.

## drda 2.0.3

- Updated vignette after review from the Journal of Statistical
Software.
- Fixed again the
`x`

-axis of the plot.

## drda 2.0.2

- Fixed a bug in the
`plot`

when doses were not previously
sorted.
- Fixed a bug in the
`x`

-axis of the `plot`

when
data contained zeros.
- It is now possible to not plot data points by setting option
`plot_data`

to `FALSE`

(default
`TRUE`

).

## drda 2.0.1

- Small fixes to unit tests because they were not passing on specific
systems.
- Updated vignette with new simulation results.

## drda 2.0.0

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:

- Change parameterization to follow that of the Emax model.
- Implement the log-logistic family of models.
- Improve initialization algorithm to be more efficient and
(hopefully) robust.
- Exported functions for evaluating theoretical gradient and Hessian
of each implemented model.
- Implement the
`effective_dose`

function for estimating
effective doses.
- Added examples to help pages.
- Many minor bug fixes (too many to list them all).

## drda 1.0.0

First public release.