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Plot Metrics

Source: R/03_metrics.R
plot.Rd

This function provides an easy way to illustrate objects of class SmallMetrics and LargeMetrics, using the ggplot2 package. See details.

Usage

plot(x, y, ...)

# S4 method for class 'SmallMetrics,missing'
plot(
  x,
  y = NULL,
  colors = NULL,
  title = NULL,
  save = FALSE,
  path = NULL,
  name = "myplot.pdf",
  width = 15,
  height = 8
)

# S4 method for class 'LargeMetrics,missing'
plot(
  x,
  y = NULL,
  colors = NULL,
  title = NULL,
  save = FALSE,
  path = NULL,
  name = "myplot.pdf",
  width = 15,
  height = 8
)

Arguments

x

An object of class SmallMetrics or LargeMetrics.

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.

Value

The plot is returned invisibly in the form of a ggplot object.

Details

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.

See also

SmallMetrics, LargeMetrics

Examples

# \donttest{
# -----------------------------------------------------
# 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)

# }