which
argument in plot_survival()
and plot_stress()
.which
argument in the plot functions. Now it contains the proper default curve names. If it is NA
only the axes and labels will get drawn.NULL
to the console.predict_mixture()
, which was a temporary development name, to multi_tox()
.proportion_ca
in the mixture model multi_tox()
was renamed and its value reversed. It is now called sa_contribution
and specifies the proportion of stress addition in the calculation of toxicant stress. To convert your code from the old version use this equation: sa_contribution = 1 - proportion_ca
.stress_tox_sam
to stress_tox_sa
in the output of multi_tox()
.plot_stress()
with argument which = NULL
would result in an error. Now it correctly draws the axes without data.log10_ticks()
for calculating tick mark labels and positions on a base 10 logarithmic axis.multiple_stress
for use with multi_tox()
.predict_mixture()
now also returns the various stresses.curves
data frame in the output of ecxsys()
now contains a column with the concentrations which are used for the plot functions in this package. This is useful for generating a nicer concentration axis.ec()
:response_value
to effect
in the output list.response_level
of 0 or 100 is now allowed. 0 returns the concentration 0 and 100 returns the concentration Inf
. Previously this resulted in an error.plot_effect()
and plot_stress()
where supplying an empty vector caused the four standard curves to show. Now setting which
to an empty vector or NULL
shows just the axes. The default value is NA.mixture_effect
column in the predict_mixture
output data frame to effect
.predict_mixture()
must be the same length. The longer length must be a multiple of the shorter length because the shorter vector gets recycled to the longer length.plot_effect()
and plot_stress()
. You can now control whether the observed values (the points) should be plotted using the which
argument.sys_tox_not_fitted
and sys_tox_env_not_fitted
to sys_tox_observed
and sys_tox_env_observed
in the output of ecxsys()
.predict_mixture()
now accepts multiple values for the concentration of the second toxicant. Both concentration vectors must be the same length.predict_mixture()
now returns a data frame with the concentrations and effects. Previously it was only a vector of effects.predict_mixture()
received a new argument "effect_max" which scales the returned effect values.predict_mixture()
to use underscore letters a and b instad of 1 and 2. For example model_1 is now model_a.predict_mixture()
and included example of symmetry.ec()
now raises an error if the curve does not cross the desired response level.ecxsys()
gained a new argument curves_concentration_max
which allows setting the maximum concentration of the predicted curves.plot_effect()
to also show effect_tox
and effect_tox_env
.plot_effect()
and plot_stress()
gained a which
argument that controls which curves are plotted. Consequently, the show_LL5_model
argument of plot_effect()
was removed.xlab
and ylab
to plot_stress
.main
to both plot functions.predict_mixture()
for the prediction of the effects of mixtures of two toxicants.ecxsys()
and predict_ecxsys()
.ecxsys()
.hormesis_index
argument from ecxsys()
. Use hormesis_concentration
instead.predict_ecxsys()
replaces fn()
from the ecxsys()
output.ec()
.ec()
more flexible. It now also accepts a data.frame with a concentration column and a column of response values.plot_effect()
.plot_system_stress()
to plot_stress()
because it is planned to plot more stresses with this function in a future update.predict_ecxsys()
.NEWS.md
file to track changes to the package.Add the following code to your website.
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