Kernel: Abstract Kernel Class

In distr6: The Complete R6 Probability Distributions Interface

Abstract Kernel Class

Description

Abstract class that cannot be constructed directly.

Value

Returns error. Abstract classes cannot be constructed directly.

Super class

distr6::Distribution -> Kernel

Public fields

package

Deprecated, use $packages instead.

packages

Packages required to be installed in order to construct the distribution.

Methods

Public methods

• Kernel$new()

• Kernel$mode()

• Kernel$mean()

• Kernel$median()

• Kernel$pdfSquared2Norm()

• Kernel$cdfSquared2Norm()

• Kernel$skewness()

• Kernel$clone()

Inherited methods

• distr6::Distribution$cdf()

• distr6::Distribution$confidence()

• distr6::Distribution$correlation()

• distr6::Distribution$getParameterValue()

• distr6::Distribution$iqr()

• distr6::Distribution$liesInSupport()

• distr6::Distribution$liesInType()

• distr6::Distribution$parameters()

• distr6::Distribution$pdf()

• distr6::Distribution$prec()

• distr6::Distribution$print()

• distr6::Distribution$quantile()

• distr6::Distribution$rand()

• distr6::Distribution$setParameterValue()

• distr6::Distribution$stdev()

• distr6::Distribution$strprint()

• distr6::Distribution$summary()

• distr6::Distribution$workingSupport()

---

Method new()

Creates a new instance of this R6 class.

Usage

Kernel$new(decorators = NULL, support = Interval$new(-1, 1))

Arguments

decorators

(character())
Decorators to add to the distribution during construction.

support

[set6::Set]
Support of the distribution.

---

Method mode()

Calculates the mode of the distribution.

Usage

Kernel$mode(which = "all")

Arguments

which

(character(1) | numeric(1)
Ignored if distribution is unimodal. Otherwise "all" returns all modes, otherwise specifies which mode to return.

---

Method mean()

Calculates the mean (expectation) of the distribution.

Usage

Kernel$mean(...)

Arguments

...

Unused.

---

Method median()

Calculates the median of the distribution.

Usage

Kernel$median()

---

Method pdfSquared2Norm()

The squared 2-norm of the pdf is defined by

\int_a^b (f_X(u))^2 du

where X is the Distribution, f_X is its pdf and a, b are the distribution support limits.

Usage

Kernel$pdfSquared2Norm(x = 0, upper = Inf)

Arguments

x

(numeric(1))
Amount to shift the result.

upper

(numeric(1))
Upper limit of the integral.

---

Method cdfSquared2Norm()

The squared 2-norm of the cdf is defined by

\int_a^b (F_X(u))^2 du

where X is the Distribution, F_X is its pdf and a, b are the distribution support limits.

Usage

Kernel$cdfSquared2Norm(x = 0, upper = Inf)

Arguments

x

(numeric(1))
Amount to shift the result.

upper

(numeric(1))
Upper limit of the integral.

---

Method skewness()

The skewness of a distribution is defined by the third standardised moment,

sk_X = E_X[((x - μ)/σ)^3]

where E_X is the expectation of distribution X, μ is the mean of the distribution and σ is the standard deviation of the distribution.

Usage

Kernel$skewness(...)

Arguments

...

Unused.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

Kernel$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

distr6 documentation built on March 28, 2022, 1:05 a.m.