ecx {bayesnec} | R Documentation |
bayesnecfit
or bayesnecfit
.Extracts the predicted ECx value as desired from an object of class
bayesnecfit
or bayesnecfit
.
ecx(
object,
ecx_val = 10,
precision = 1000,
posterior = FALSE,
type = "absolute",
hormesis_def = "control",
x_range = NA,
xform = NA,
prob_vals = c(0.5, 0.025, 0.975)
)
object |
An object of class |
ecx_val |
The desired percentage effect value. This must be a value between 1 and 99 (for type = "relative" and "absolute"), defaults to 10. |
precision |
The number of unique x values over which to find ECx - large values will make the ECx estimate more precise. |
posterior |
A |
type |
A |
hormesis_def |
A |
x_range |
A range of x values over which to consider extracting ECx. |
xform |
A function to apply to the returned estimated concentration values. |
prob_vals |
A vector indicating the probability values over which to return the estimated ECx value. Defaults to 0.5 (median) and 0.025 and 0.975 (95 percent credible intervals). |
type
"relative" is calculated as the percentage decrease
from the maximum predicted value of the response (top) to the minimum
predicted value of the response. Type "absolute" (the default) is
calculated as the percentage decrease from the maximum value of the
response (top) to 0 (or bot for a 4 parameter model fit). Type "direct"
provides a direct estimate of the x value for a given y.
Note that for the current version, ECx for an "nechorme" (NEC Hormesis)
model is estimated at a percent decline from the control.
For hormesis_def
, if "max", then ECx values are calculated as a
decline from the maximum estimates (i.e. the peak at NEC);
if "control", then ECx values are calculated relative to the control, which
is assumed to be the lowest observed concentration.
A vector containing the estimated ECx value, including upper and lower 95% credible interval bounds.
library(brms)
library(bayesnec)
data(manec_example)
ecx(manec_example, ecx_val = 50)
ecx(manec_example)