Plotmodel {cubfits} | R Documentation |
Plot Fitted Models
Description
Plot model results to visualize the effects of mutation and selection along with expression levels. The model can be fitted by MCMC or multinomial logistic regression.
Usage
prop.model.roc(b.Init, phi.Obs.lim = c(0.01, 10), phi.Obs.scale = 1,
nclass = 40, x.log10 = TRUE)
plotmodel(ret.model, main = NULL,
xlab = "Production Rate (log10)", ylab = "Proportion",
xlim = NULL, lty = 1, x.log10 = TRUE, ...)
plotaddmodel(ret.model, lty, u.codon = NULL, color = NULL,
x.log10 = TRUE)
Arguments
b.Init |
a |
phi.Obs.lim |
range of |
phi.Obs.scale |
optional scaling factor. |
nclass |
number of binning classes across the range of |
x.log10 |
|
ret.model |
model results from |
main |
an option passed to |
xlab |
an option passed to |
ylab |
an option passed to |
xlim |
range of X-axis. |
lty |
line type. |
u.codon |
unique synonymous codon names. |
color |
a color vector for unique codon, typically returns of
the internal function |
... |
options passed to |
Details
The function plotmodel()
plots the fitted curves obtained from
prop.model.roc()
.
The function plotaddmodel()
can append model curves to a binning plot
provided unique synonymous codons and colors are given. This function is
nearly for an internal call within plotmodel()
, but is exported and
useful for workflow.
Currently, only ROC model is supported.
Colors are controlled by .CF.PT
.
Value
A fitted curve plot is drawn.
Author(s)
Wei-Chen Chen wccsnow@gmail.com.
References
https://github.com/snoweye/cubfits/
See Also
plotbin()
, prop.bin.roc()
, and
prop.model.roc()
.
Examples
## Not run:
demo(plotbin, 'cubfits', ask = F, echo = F)
## End(Not run)