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.
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