Plotprxy {cubfits} | R Documentation |
Predictive X-Y Plot
Description
This utility function provides a basic plot of production rates.
Usage
plotprxy(x, y, x.ci = NULL, y.ci = NULL,
log10.x = TRUE, log10.y = TRUE,
add.lm = TRUE, add.one.to.one = TRUE, weights = NULL,
add.legend = TRUE,
xlim = NULL, ylim = NULL,
xlab = "Predicted Production Rate (log10)",
ylab = "Observed Production Rate (log10)",
main = NULL)
Arguments
x |
expression values. |
y |
expression values, of the same length of |
x.ci |
confidence interval of |
y.ci |
confidence interval of |
log10.x |
|
log10.y |
|
add.lm |
if add |
add.one.to.one |
if add one-to-one line. |
weights |
weights to |
add.legend |
if add default legend. |
xlim |
limits of x-axis. |
ylim |
limits of y-axis. |
xlab |
an option passed to |
ylab |
an option passed to |
main |
an option passed to |
Details
As the usual X-Y plot where x
and y
are expression values.
If add.lm = TRUE
and weights
are given, then both ordinary
and weighted least squares results will be plotted.
Value
A scatter plot with a fitted lm()
line and R squared value.
Author(s)
Wei-Chen Chen wccsnow@gmail.com.
References
https://github.com/snoweye/cubfits/
See Also
Examples
## Not run:
suppressMessages(library(cubfits, quietly = TRUE))
y.scuo <- convert.y.to.scuo(ex.train$y)
SCUO <- calc_scuo_values(y.scuo)$SCUO
plotprxy(ex.train$phi.Obs, SCUO)
## End(Not run)