# plot

## Description

`plot(`

plots a probability density function
(pdf) of the probability distribution object `pd`

)`pd`

. If
`pd`

is created by fitting a probability distribution to the data, the
pdf is superimposed over a histogram of the data.

`plot(___,`

specifies
options using one or more name-value arguments in addition to any of the input argument
combinations in the previous syntaxes. For example, you can indicate whether to plot a
cumulative distribution function (cdf) or a probability plot instead of a pdf.`Name=Value`

)

returns handles to
the plotted graphics objects.`H`

= plot(___)

## Examples

### Plot Normal Distribution

Generate random data points from a normal distribution with mean 0 and standard deviation 1.

rng("default") % Set the seed for reproducibility.

Fit a normal distribution to the data.

```
normaldata = normrnd(0,1,100,1);
normalpd = fitdist(normaldata,"Normal")
```

normalpd = NormalDistribution Normal distribution mu = 0.123085 [-0.10756, 0.353731] sigma = 1.1624 [1.02059, 1.35033]

`normalpd`

is a `NormalDistribution`

object that contains the parameter values for the normal distribution fit to the data, and the data. Plot a pdf for the normal distribution with a histogram of the data.

plot(normalpd)

Plot a cdf of the normal distribution fit to the data and a stairs plot of a cdf for the data.

`plot(normalpd,PlotType="cdf")`

Display a probability plot for the normal distribution fit to the data.

`plot(normalpd,PlotType="probability")`

The vertical axis is scaled so that the cdf for the fitted probability distribution is represented by a straight line.

### Multinomial Distribution Plots

Create a multinomial distribution that has five outcomes with probabilities of 0.1, 0.2, 0.4, 0.2, and 0.1.

`multinomialpd = makedist("Multinomial",probabilities=[0.1 0.2 0.4 0.2 0.1])`

multinomialpd = MultinomialDistribution Probabilities: 0.1000 0.2000 0.4000 0.2000 0.1000

Plot a pdf for the multinomial distribution.

plot(multinomialpd)

The plot contains a `Stem`

object that represents the probabilities for the data.

Plot the pdf as a continuous distribution.

plot(multinomialpd,Discrete=0)

Plot the cdf of the fitted multinomial distribution as a stairs plot.

`plot(multinomialpd,PlotType="cdf")`

Plot the cdf as a continuous distribution.

`plot(multinomialpd,PlotType="cdf",Discrete=0)`

## Input Arguments

`pd`

— Probability distribution

probability distribution object

Probability distribution, specified as one of the probability distribution objects in the following table.

Distribution Object | Function or App Used to Create Probability Distribution Object |
---|---|

`BetaDistribution` | `makedist` , `fitdist` , Distribution Fitter |

`BinomialDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`BirnbaumSaundersDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`BurrDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`ExponentialDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`ExtremeValueDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`GammaDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`GeneralizedExtremeValueDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`GeneralizedParetoDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`HalfNormalDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`InverseGaussianDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`KernelDistribution` | `fitdist` , Distribution Fitter |

`LogisticDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`LoglogisticDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`LognormalDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`LoguniformDistribution` | `makedist` |

`MultinomialDistribution` | `makedist` |

`NakagamiDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`NegativeBinomialDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`NormalDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`PiecewiseLinearDistribution` | `makedist` |

`PoissonDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`RayleighDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`RicianDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`StableDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`tLocationScaleDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`TriangularDistribution` | `makedist` |

`UniformDistribution` | `makedist` |

`WeibullDistribution` | `makedist` , `fitdist` ,
Distribution Fitter |

`ax`

— Axes for plot

`Axes`

graphics object

Axes for plot, specified as an `Axes`

graphics object. If you do not
specify the axes by using the `ax`

input argument or the
`Parent`

name-value argument, the `plot`

function plots into the current axes or creates an `Axes`

object if one
does not exist. For more information on creating an `Axes`

graphics
object, see `axes`

and Axes Properties.

### Name-Value Arguments

Specify optional pairs of arguments as
`Name1=Value1,...,NameN=ValueN`

, where `Name`

is
the argument name and `Value`

is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.

**Example: **`Discrete=1,PlotType="cdf"`

plots a cumulative distribution
function (cdf) of the probability distribution as a stairs plot.

`PlotType`

— Plot type

`"pdf"`

(default) | `"cdf"`

| `"probability"`

Plot type for the probability distribution, specified as one of the following.

`"pdf"` | Plot the probability density function (pdf). When
`pd` is fit to data, the pdf is superimposed on a
histogram of the data. |

`"cdf"` | Plot the cumulative distribution function (cdf). When
`pd` is fit to data, the cdf is superimposed over an
empirical cdf. |

`"probability"` | Display a probability plot using a cdf of the data and a cdf of the
fitted probability distribution. This option is available only when
`pd` is parametric and fit to data. |

**Example: **`PlotType="probability"`

**Data Types: **`char`

| `string`

`Discrete`

— Indicator to plot as discrete function

`1 (true)`

| `0 (false)`

Indicator to plot as a discrete function, specified as `1 (true)`

or `0 (false)`

. Specify `Discrete=0`

to display the
pdf or cdf as a line plot. Specify `Discrete=1`

to display the pdf
as a stem plot or to display the cdf as a stairs plot.

The default value for `Discrete`

is 1 when
`pd`

is a discrete probability distribution object and 0 when
`pd`

is a continuous probability distribution object. If
`pd`

is continuous, `plot`

ignores the
user-specified input for `Discrete`

and plots continuous
functions.

**Example: **`Discrete=0`

**Data Types: **`logical`

`Parent`

— Axes for plot

`Axes`

graphics object

Axes for plot, specified as an `Axes`

graphics object. If you do
not specify the axes by using the `ax`

input argument or the
`Parent`

name-value argument, the
`plot`

function plots into the current axes or creates an
`Axes`

object if one does not exist. For more information on creating
an `Axes`

graphics object, see `axes`

and Axes Properties.

## Output Arguments

`H`

— Handles to plotted graphics objects

`Line`

object | `Stem`

object | `Stairs`

object | graphics array

Handles to the plotted graphics objects, returned as a `Line`

object,
`Stem`

object, `Stairs`

object, or graphics array.

When

`PlotType`

is set to`"pdf"`

or`"cdf"`

, and`pd`

is not fit to data,`H`

is a single handle corresponding to the pdf or cdf for the distribution.When

`PlotType`

is set to`"pdf"`

or`"cdf"`

, and`pd`

is fit to data,`H`

is a 1-by-2 graphics array. The first entry of the graphics array corresponds to the pdf or cdf for the distribution, and the second entry corresponds to the data.When

`PlotType`

is set to`"probability"`

,`H`

is a 2-by-1 graphics array with entries corresponding to the data and the distribution.

The table below shows how the returned graphics object depends on whether the
distribution is discrete, whether `pd`

is fit to data, and the
specified values for the name-value arguments `Discrete`

and
`PlotType`

.

Distribution Type | Fit to Data | `Discrete` value | `PlotType` value | Returned Graphics Object |
---|---|---|---|---|

Discrete | No | 1 | `"pdf"` | `Stem` |

`"cdf"` | `Stairs` | |||

0 | `"pdf"` | `Line` | ||

`"cdf"` | `Line` | |||

Yes | 1 | `"pdf"` | `[` | |

`"cdf"` | `[` | |||

`"probability"` | `[` | |||

0 | `"pdf"` | `[` | ||

`"cdf"` | `[` | |||

`"probability"` | `[` | |||

Continuous | No | 0 | `"pdf"` | `Line` |

`"cdf"` | `Line` | |||

Yes | 0 | `"pdf"` | `[` | |

`"cdf"` | `[` | |||

`"probability"` | `[` |

## Version History

**Introduced in R2022b**

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