Distribution: Distribution class

In terminological/classifier-result:

Description

Distribution class

Distribution class

Details

The distribution class wrapps PDF and Quatile functions from a number of distributions and provides some simple stats for those functions, including a sampling function

Public fields

pdf

the density function

invCdf

the centile function

cdf

the distribution function

dots

the parameters of the pdf

Methods

Public methods

• Distribution$new()

• Distribution$p()

• Distribution$bigP()

• Distribution$q()

• Distribution$getPdf()

• Distribution$getInverseCdf()

• Distribution$theoreticalEntropy()

• Distribution$label()

• Distribution$inverse()

• Distribution$sample()

• Distribution$plot()

• Distribution$twoDp()

• Distribution$clone()

---

Method new()

Creates a distribution

Usage

Distribution$new(density, quantile, distribution, ...)

Arguments

density

a function that accepts at least a vector of x value (e.g. dnorm)

quantile

a function that accepts at least a vector of p values (e.g. qnorm)

...

passed to pdfFunction and centileFunction

---

Method p()

calculate the probability density at x

Usage

Distribution$p(x)

Arguments

x

a vector of values of x

Returns

a vector of values of (p(x))

---

Method bigP()

calculate the cumulative density at x

Usage

Distribution$bigP(x)

Arguments

x

a vector of values of x

Returns

a vector of values of (P(x))

---

Method q()

calculate the value of x for a centile y

Usage

Distribution$q(y)

Arguments

y

a vector of centiles

Returns

a vector of values of x

---

Method getPdf()

the PDF and CDF for a distribution as a dataframe

Usage

Distribution$getPdf(xmin, xmax, resolution = 1001)

Arguments

xmin

the smallest value

xmax

the smallest value

resolution

the number of increments in x

Returns

a dataframe

---

Method getInverseCdf()

defines a inverse CDF as a data frame

Usage

Distribution$getInverseCdf(resolution = 1001)

Arguments

resolution

the number of increments in y

Returns

a dataframe

---

Method theoreticalEntropy()

calculates the integral of -p(x)*log(p(x)) from -Infinity to Infinity

Usage

Distribution$theoreticalEntropy()

Returns

a value

---

Method label()

gets a label for this distribution based on the parameters passed

Usage

Distribution$label()

Returns

a string

---

Method inverse()

gets a label for this distribution based on the parameters passed

Usage

Distribution$inverse(y)

Arguments

y

a vector of y values to apply the quantile function to

Returns

a daat frame of y and corresponding x values

---

Method sample()

produce a set of samples conforming to this distribution

Usage

Distribution$sample(n = 10)

Arguments

n

the number of samples

Returns

a data frame of samples (labelled x)

---

Method plot()

plot this dictributions as pdf and cdf

Usage

Distribution$plot(xmin, xmax, resolution = 1001)

Arguments

xmin

the minimum of the support range to plot

xmax

the maximum of the support range to plot

resolution

the number of points to generate for the plot (default 1001)

Returns

a ggassemble plot object

---

Method twoDp()

a 2 dp formatter

Usage

Distribution$twoDp(x, unit = "")

Arguments

x

a number

unit

a unit

---

Method clone()

The objects of this class are cloneable with this method.

Usage

Distribution$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

terminological/classifier-result documentation built on March 14, 2020, 8:04 a.m.