View source: R/plot.survFitTT.R
plot.survFitTT | R Documentation |
survFitTT
objectsThis is the generic plot
S3 method for the survFitTT
class. It
plots concentration-response fit under target time survival analysis.
## S3 method for class 'survFitTT'
plot(
x,
xlab = "Concentration",
ylab = "Survival probability",
main = NULL,
fitcol = "orange",
fitlty = 1,
fitlwd = 1,
spaghetti = FALSE,
cicol = "orange",
cilty = 2,
cilwd = 1,
ribcol = "grey70",
adddata = FALSE,
addlegend = FALSE,
log.scale = FALSE,
style = "ggplot",
...
)
x |
an object of class |
xlab |
a label for the |
ylab |
a label for the |
main |
main title for the plot |
fitcol |
color of the fitted curve |
fitlty |
line type of the fitted curve |
fitlwd |
width of the fitted curve |
spaghetti |
if |
cicol |
color of the 95 % credible interval limits |
cilty |
line type for the 95 % credible interval limits |
cilwd |
width of the 95 % credible interval limits |
ribcol |
color of the ribbon between lower and upper credible limits.
Transparent if |
adddata |
if |
addlegend |
if |
log.scale |
if |
style |
graphical backend, can be |
... |
Further arguments to be passed to generic methods |
The fitted curve represents the estimated survival probability at
the target time as a function of the concentration of chemical compound;
When adddata = TRUE
the black dots depict the observed survival
probability at each tested concentration. Note that since our model does not take
inter-replicate variability into consideration, replicates are systematically
pooled in this plot.
The function plots both 95% credible intervals for the estimated survival
probability (by default the grey area around the fitted curve) and 95% binomial confidence
intervals for the observed survival probability (as black segments if
adddata = TRUE
).
Both types of intervals are taken at the same level. Typically
a good fit is expected to display a large overlap between the two intervals.
If spaghetti = TRUE, the credible intervals are represented by two dotted
lines limiting the credible band, and a spaghetti plot is added to this band.
This spaghetti plot consists of the representation of simulated curves using parameter values
sampled in the posterior distribution (10% of the MCMC chains are randomly
taken for this sample).
a plot of class ggplot
When style = "ggplot"
, the function calls function
ggplot
and returns an object of class ggplot
.
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