View source: R/plot.survFitCstExp.R
plot.survFitCstExp | R Documentation |
survFit
objectsThis is the generic plot
S3 method for the
survFit
. It plots the fit obtained for each
concentration of chemical compound in the original dataset.
## S3 method for class 'survFitCstExp' plot( x, xlab = "Time", ylab = "Survival probability", main = NULL, concentration = NULL, spaghetti = FALSE, one.plot = FALSE, adddata = TRUE, addlegend = FALSE, style = "ggplot", ... )
x |
An object of class |
xlab |
A label for the X-axis, by default |
ylab |
A label for the Y-axis, by default |
main |
A main title for the plot. |
concentration |
A numeric value corresponding to some specific concentrations in
|
spaghetti |
if |
one.plot |
if |
adddata |
if |
addlegend |
if |
style |
graphical backend, can be |
... |
Further arguments to be passed to generic methods. |
The fitted curves represent the estimated survival probability as a function
of time for each concentration.
The black dots depict the observed survival
probability at each time point. 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 error bars 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 types of 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 (2% of the MCMC chains are randomly
taken for this sample).
a plot of class ggplot
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