Plot density function based on fit to data

MASS::fitdistr() is used to fit coefficients of a specified family of distributions and the resulting density curve is displayed.

gf_fitdistr(
  object = NULL,
  gformula = NULL,
  data = NULL,
  ...,
  dist = "dnorm",
  start = NULL,
  alpha,
  color,
  fill,
  group,
  linetype,
  linewidth,
  size,
  xlab,
  ylab,
  title,
  subtitle,
  caption,
  geom = "path",
  stat = "fitdistr",
  position = "identity",
  show.legend = NA,
  show.help = NULL,
  inherit = FALSE,
  environment = parent.frame()
)

Arguments

object

When chaining, this holds an object produced in the earlier portions of the chain. Most users can safely ignore this argument. See examples.

gformula

A formula with shape ~ x used to specify the data to be fit to a family of distributions.

data

A data frame containing the variable to be fitted.

...

Additional arguments

dist

A quoted name of a distribution function. See mosaicCore::fit_distr_fun() for more details about allowable distributions.

start

Starting value(s) for the search for MLE. (See MASS::fitdistr.)

alpha

Opacity (0 = invisible, 1 = opaque).

color

A color or a formula used for mapping color.

fill

A color for filling, or a formula used for mapping fill.

group

Used for grouping.

linetype

A linetype (numeric or "dashed", "dotted", etc.) or a formula used for mapping linetype.

linewidth

A numerical line width or a formula used for mapping linewidth.

size

size aesthetic for dots in pmf plots.

xlab

Label for x-axis. See also gf_labs().

ylab

Label for y-axis. See also gf_labs().

title, subtitle, caption

Title, sub-title, and caption for the plot. See also gf_labs().

geom

A character string naming the geom used to make the layer.

stat

A character string naming the stat used to make the layer.

position

Either a character string naming the position function used for the layer or a position object returned from a call to a position function.

show.legend

A logical indicating whether this layer should be included in the legends. NA, the default, includes layer in the legends if any of the attributes of the layer are mapped.

show.help

If TRUE, display some minimal help.

inherit

A logical indicating whether default attributes are inherited.

environment

An environment in which to look for variables not found in data.

Value

a gg object

Specifying plot attributes

Positional attributes (a.k.a, aesthetics) are specified using the formula in gformula. Setting and mapping of additional attributes can be done through the use of additional arguments. Attributes can be set can be set using arguments of the form attribute = value or mapped using arguments of the form attribute = ~ expression.

In formulas of the form A | B, B will be used to form facets using facet_wrap() or facet_grid(). This provides an alternative to gf_facet_wrap() and gf_facet_grid() that is terser and may feel more familiar to users of lattice.

Evaluation

Evaluation of the ggplot2 code occurs in the environment of gformula. This will typically do the right thing when formulas are created on the fly, but might not be the right thing if formulas created in one environment are used to create plots in another.

See also

mosaicCore::fit_distr_fun()

Examples

gf_fitdistr(~length, data = mosaicData::KidsFeet, inherit = FALSE) |>
  gf_dhistogram(~length, data = mosaicData::KidsFeet, binwidth = 0.5, alpha = 0.25)


gf_dhistogram(~length, data = mosaicData::KidsFeet, binwidth = 0.5, alpha = 0.25) |>
  gf_fitdistr()


set.seed(12345)
Dat <- data.frame(
  f = rf(500, df1 = 3, df2 = 47),
  g = rgamma(500, 3, 10)
)
gf_dhistogram(~g, data = Dat) |>
  gf_fitdistr(dist = "dgamma", linewidth = 1.4)


gf_dhistogram(~g, data = Dat) |>
  gf_fun(mosaicCore::fit_distr_fun(~g, data = Dat, dist = "dgamma"))


gf_dhistogram(~f, data = Dat) |>
  gf_fitdistr(dist = "df", start = list(df1 = 2, df2 = 50))


# fitted parameters are default argument values
args(
  mosaicCore::fit_distr_fun(~f,
    data = Dat, dist = "df",
    start = list(df1 = 2, df2 = 50)
  )
)
#> function (x, df1 = 3.20565597290919, df2 = 33.6603043440824, 
#>     ncp, log = FALSE) 
#> NULL
args(mosaicCore::fit_distr_fun(~g, data = Dat, dist = "dgamma"))
#> function (x, shape = 3.06811349020082, rate = 10.7081791969972, 
#>     scale = 1/rate, log = FALSE) 
#> NULL