plot | R Documentation |
This function provides an easy way to illustrate objects of class
SmallMetrics
and LargeMetrics
, using the ggplot2
package. See details.
plot(x, y, ...)
## S4 method for signature 'SmallMetrics,missing'
plot(
x,
y = NULL,
colors = NULL,
title = NULL,
save = FALSE,
path = NULL,
name = "myplot.pdf",
width = 15,
height = 8
)
## S4 method for signature 'LargeMetrics,missing'
plot(
x,
y = NULL,
colors = NULL,
title = NULL,
save = FALSE,
path = NULL,
name = "myplot.pdf",
width = 15,
height = 8
)
x |
An object of class |
y |
NULL. |
... |
extra arguments. |
colors |
character. The colors to be used in the plot. |
title |
character. The plot title. |
save |
logical. Should the plot be saved? |
path |
A path to the directory in which the plot will be saved. |
name |
character. The name of the output pdf file. |
width |
numeric. The plot width in inches. |
height |
numeric. The plot height in inches. |
Objects of class SmallMetrics
and LargeMetrics
are returned by the
small_metrics()
and large_metrics()
functions, respectively.
For the SmallMetrics
, a grid of line charts is created for each metric and
sample size. For the LargeMetrics
, a grid of line charts is created for
each element of the asymptotic variance - covariance matrix.
Each estimator is plotted with a different color and line type. The plot can be saved in pdf format.
The plot is returned invisibly in the form of a ggplot
object.
SmallMetrics, LargeMetrics
# -----------------------------------------------------
# Beta Distribution Example
# -----------------------------------------------------
D <- Beta(shape1 = 1, shape2 = 2)
prm <- list(name = "shape1",
val = seq(0.5, 2, by = 0.1))
x <- small_metrics(D, prm,
est = c("mle", "me", "same"),
obs = c(20, 50),
sam = 1e2,
seed = 1)
plot(x)
# -----------------------------------------------------
# Dirichlet Distribution Example
# -----------------------------------------------------
D <- Dir(alpha = 1:2)
prm <- list(name = "alpha",
pos = 1,
val = seq(0.5, 2, by = 0.1))
x <- small_metrics(D, prm,
est = c("mle", "me", "same"),
obs = c(20, 50),
sam = 1e2,
seed = 1)
plot(x)
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