pred.plot {mpae} | R Documentation |
Observed vs. predicted plots
Description
Generates plots comparing predictions with observations.
Usage
pred.plot(pred, obs, ...)
## Default S3 method:
pred.plot(
pred,
obs,
xlab = "Predicted",
ylab = "Observed",
lm.fit = TRUE,
lowess = TRUE,
...
)
## S3 method for class 'factor'
pred.plot(
pred,
obs,
type = c("frec", "perc", "cperc"),
xlab = "Observed",
ylab = NULL,
legend.title = "Predicted",
label.bars = TRUE,
...
)
Arguments
pred |
a numeric vector with the predicted values. |
obs |
a numeric vector with the observed values. |
... |
additional graphical parameters or further arguments passed to
other methods (e.g. to |
xlab |
a title for the x axis. |
ylab |
a title for the y axis. |
lm.fit |
logical indicating if a |
lowess |
logical indicating if a |
type |
types of the desired plots. Any combination of the following
values is possible: |
legend.title |
a title for the legend. |
label.bars |
if |
Details
The default method draws a scatter plot of the observed values against the predicted values.
pred.plot.factor()
creates bar plots representing frequencies, percentages
or conditional percentages of pred
within levels of obs
.
This method is a front end to RcmdrMisc::Barplot()
.
Value
The default method invisibly returns the fitted linear model if
lm.fit == TRUE
.
pred.plot.factor()
invisibly returns the horizontal coordinates of the
centers of the bars.
See Also
Examples
set.seed(1)
nobs <- nrow(hbat)
itrain <- sample(nobs, 0.8 * nobs)
train <- hbat[itrain, ]
test <- hbat[-itrain, ]
# Regression
fit <- lm(fidelida ~ velocida + calidadp, data = train)
pred <- predict(fit, newdata = test)
obs <- test$fidelida
res <- pred.plot(pred, obs)
summary(res)
# Classification
fit2 <- glm(alianza ~ velocida + calidadp, family = binomial, data = train)
obs <- test$alianza
p.est <- predict(fit2, type = "response", newdata = test)
pred <- factor(p.est > 0.5, labels = levels(obs))
pred.plot(pred, obs, type = "frec", style = "parallel")
old.par <- par(mfrow = c(1, 2))
pred.plot(pred, obs, type = c("perc", "cperc"))
par(old.par)