Watson distribution class

This class defines the Watson distribution. It provides methods for fitting the distribution to data and generating random samples.

Super class

midi::BaseDistribution -> WatsonDistribution

Methods

Public methods

• WatsonDistribution$new()

• WatsonDistribution$get_axis()

• WatsonDistribution$get_concentration()

• WatsonDistribution$clone()

Inherited methods

• midi::BaseDistribution$fit()
• midi::BaseDistribution$get_mean()
• midi::BaseDistribution$get_variance()
• midi::BaseDistribution$random()

---

Method new()

Creates a new Watson distribution.

Usage

WatsonDistribution$new(mu = c(0, 0, 1), kappa = 10)

Arguments

mu

A numeric vector of length 3 specifying the mean direction of the Watson distribution. Defaults to (0, 0, 1).

kappa

A numeric value specifying the concentration parameter of the Watson distribution. Defaults to 10.0.

Returns

An instance of the Watson distribution as an object of class WatsonDistribution.

---

Method get_axis()

Retrieves the mean axis of the Watson distribution.

Usage

WatsonDistribution$get_axis()

Returns

A numeric vector of length 3 storing the mean axis of the Watson distribution.

---

Method get_concentration()

Retrieves the concentration parameter of the Watson distribution.

Usage

WatsonDistribution$get_concentration()

Returns

A numeric value storing the concentration parameter of the Watson distribution.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

WatsonDistribution$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

wd <- WatsonDistribution$new(
  mu = c(0, 0, 1),
  kappa = 10
)
wd$get_axis()
#> [1] 0 0 1
wd$get_concentration()
#> [1] 10
wd$random(10)
#> [[1]]
#> [1] -0.1305185  0.1437479  0.9809697
#> 
#> [[2]]
#> [1] 0.2882047 0.2054522 0.9352686
#> 
#> [[3]]
#> [1] -0.3405410 -0.1093761  0.9338462
#> 
#> [[4]]
#> [1] -0.07887883  0.27967791  0.95684816
#> 
#> [[5]]
#> [1] -0.1012958 -0.1123559  0.9884914
#> 
#> [[6]]
#> [1] -0.0726425  0.8331471  0.5482600
#> 
#> [[7]]
#> [1] 0.2639347 0.1784568 0.9478880
#> 
#> [[8]]
#> [1]  0.0006495886 -0.4170701965  0.9088740447
#> 
#> [[9]]
#> [1] -0.02479583  0.35059414  0.93619919
#> 
#> [[10]]
#> [1] -0.2105415 -0.2716214  0.9390922
#> 
wd$fit(wd$random(100))
wd$get_axis()
#> [1]  0.02163945  0.03845331 -0.99902606
wd$get_concentration()
#> [1] 10.15158