# qqPlot

Produces a Q-Q plot (quantile-quantile plot).

Supply the `sample`

parameter to compare distribution of observations with a theoretical distribution ('normal' or as otherwise specified by the `distribution`

parameter). Alternatively, supply `x`

and `y`

parameters to compare the distribution of `x`

with the distribution of `y`

.

## Examples

#### Parameters

__data__

The data to be displayed in this layer. If null, the default, the data is inherited from the plot data as specified in the call to letsPlot.

__sample__

Name of variable. Specifies a vector of observations used for computing of "sample quantiles". Use this parameter to produce a "sample vs. theoretical" Q-Q plot.

__x__

Name of variable specifying a vector of observations used for computing of x "sample quantiles". Use `x`

and `y`

parameters to produce a "sample X vs. sample Y" Q-Q plot.

__y__

Name of variable specifying a vector of observations used for computing of y "sample quantiles". Use `x`

and `y`

parameters to produce a "sample X vs. sample Y" Q-Q plot.

__distribution__

default = "norm". Distribution function to use: "norm", "uniform", "t", "gamma", "exp", "chi2". Could be specified if `sample`

is.

__d__Params

Additional parameters passed on to distribution function. Could be specified if `sample`

is.

If

`distribution`

is "norm" then`dParams`

is a pair (mean, std) (default = listOf(0.0, 1.0)).If

`distribution`

is "uniform" then`dParams`

is a pair (a, b) (default = listOf(0.0, 1.0)).If

`distribution`

is "t" then`dParams`

is an integer number (d) (default = listOf(1)).If

`distribution`

is "gamma" then`dParams`

is a pair (alpha, beta) (default = listOf(1.0, 1.0)).If

`distribution`

is "exp" then`dParams`

is a float number (lambda) (default = listOf(1.0)).If

`distribution`

is "chi2" then`dParams`

is an integer number (k) (default = listOf(1)).

__quantiles__

default = Pair(0.25, 0.75). Pair of quantiles to use when fitting the Q-Q line.

__group__

Grouping parameter. If it is specified and color-parameters isn't then different groups will have different colors.

__show__Legend

default = true. false - do not show legend for this layer.

__color__

Color of a points. String in the following formats:

RGB/RGBA (e.g. "rgb(0, 0, 255)")

HEX (e.g. "#0000FF")

color name (e.g. "red")

role name ("pen", "paper" or "brush")

Or an instance of the `java.awt.Color`

class.

__fill__

Color to paint shape's inner points. Is applied only to the points of shapes having inner points.

__alpha__

default = 0.5. Transparency level of a points. Understands numbers between 0 and 1.

__size__

default = 3.0. Size of the points.

__shape__

Shape of the points.

__line__Color

default = "#FF0000". Color of the fitting line.

__line__Size

default = 0.75. Width of the fitting line.

__linetype__

Int or String. Type of the fitting line. Codes and names: 0 = "blank", 1 = "solid", 2 = "dashed", 3 = "dotted", 4 = "dotdash", 5 = "longdash", 6 = "twodash"