Gaussian {TrueSkillThroughTime}

Gaussian

Description

Gaussian class

Usage

Gaussian(mu = 0, sigma = 1)

Pi(N)

## S4 method for signature 'Gaussian'
Pi(N)

Tau(N)

## S4 method for signature 'Gaussian'
Tau(N)

forget(N, gamma, t)

## S4 method for signature 'Gaussian,numeric,numeric'
forget(N, gamma, t)

isapprox(N, M, tol = 1e-04)

## S4 method for signature 'Gaussian,Gaussian,numeric'
isapprox(N, M, tol = 1e-04)

## S4 method for signature 'Gaussian,Gaussian'
e1 + e2

## S4 method for signature 'Gaussian,Gaussian'
e1 - e2

## S4 method for signature 'Gaussian,Gaussian'
e1 * e2

## S4 method for signature 'Gaussian,Gaussian'
e1 / e2

## S4 method for signature 'Gaussian,Gaussian'
e1 == e2

## S4 method for signature 'Player'
performance(a)

Arguments

mu

A number, the mean of the Gaussian distribution.

sigma

A number, the standar deviation of the Gaussian distribution.

N

A Gaussian object

gamma

The dynamic factor, the dynamic uncertainty

t

The elapsed time

M

A Gaussian object

tol

The tolerance threshold for comparitions

e1

A Gaussian object

e2

A Gaussian object

a

A Gaussian object

Value

Gaussian object

Examples

N01 = Gaussian(0,1); N12 = Gaussian(mu = 1, sigma = 2)
N06 = Gaussian(); Ninf = Gaussian(0,Inf)
N01 * Ninf == N01
N01 * N12
N01 / N12
N01 + N12
N01 - N12
Pi(N12) == 1/(N12@sigma^2)
Tau(N12) == N12@mu/(N12@sigma^2)
Nnew = forget(N = N01, gamma = 0.01, t = 100)
isapprox(Nnew, Gaussian(N01@mu,sqrt(N01@sigma^2+100*(0.01^2))), tol=1e-6)