EMMIX.Theta-class {rebmix}

Class "EMMIX.Theta"

Description

Object of class EMMIX.Theta.

Objects from the Class

Objects can be created by calls of the form new("EMMIX.Theta", ...). Accessor methods for the slots are a.c(x = NULL), a.d(x = NULL), a.pdf(x = NULL) and a.Theta(x = NULL), where x stands for an object of class EMMIX.Theta. Setter methods a.theta1(x = NULL, l = numeric()), a.theta2(x = NULL, l = numeric()), a.theta3(x = NULL, l = numeric()), a.theta1.all(x = NULL), a.theta2.all(x = NULL), a.theta3.all(x = NULL) and a.w(x = NULL) are provided to write to Theta slot, where l = 1, \ldots, c.

Slots

c:

number of components c > 0. The default value is 1.

d:

number of dimensions.

pdf:

a character vector of length d containing continuous or discrete parametric family types. One of "normal", "lognormal", "Weibull", "gamma", "Gumbel", "binomial", "Poisson", "Dirac" or "vonMises".

Theta:

a list containing c parametric family types pdfl. One of "normal", "lognormal", "Weibull", "gamma", "Gumbel", "binomial", "Poisson", "Dirac" or circular "vonMises" defined for 0 \leq y_{i} \leq 2 \pi. Component parameters theta1.l follow the parametric family types. One of \mu_{il} for normal, lognormal, Gumbel and von Mises distributions and \theta_{il} for Weibull, gamma, binomial, Poisson and Dirac distributions. Component parameters theta2.l follow theta1.l. One of \sigma_{il} for normal, lognormal and Gumbel distributions, \beta_{il} for Weibull and gamma distributions, p_{il} for binomial distribution, \kappa_{il} for von Mises distribution. Component parameters theta3.l follow theta2.l. One of \xi_{il} \in \{-1, 1\} for Gumbel distribution.

w:

a vector of length c containing component weights w_{l} summing to 1.

Author(s)

Branislav Panic

Examples

Theta <- new("EMMIX.Theta", c = 2, pdf = c("normal", "Gumbel"))  

a.w(Theta) <- c(0.4, 0.6)

a.theta1(Theta, l = 1) <- c(2, 10)
a.theta2(Theta, l = 1) <- c(0.5, 2.3)
a.theta3(Theta, l = 1) <- c(NA, 1.0)
a.theta1(Theta, l = 2) <- c(20, 50)
a.theta2(Theta, l = 2) <- c(3, 4.2)
a.theta3(Theta, l = 2) <- c(NA, -1.0)

Theta

Theta <- new("EMMIX.Theta", c = 2, pdf = c("normal", "Gumbel", "Poisson"))  

a.w(Theta) <- c(0.4, 0.6)

a.theta1.all(Theta) <- c(2, 10, 30, 20, 50, 60)
a.theta2.all(Theta) <- c(0.5, 2.3, NA, 3, 4.2, NA)
a.theta3.all(Theta) <- c(NA, 1.0, NA, NA, -1.0, NA)

Theta

Theta <- new("EMMVNORM.Theta", c = 2, d = 3)

a.w(Theta) <- c(0.4, 0.6)

a.theta1(Theta, l = 1) <- c(2, 10, -20)
a.theta2(Theta, l = 1) <- c(9, 0, 0, 0, 4, 0, 0, 0, 1)
a.theta1(Theta, l = 2) <- c(-2.4, -15.1, 30)
a.theta2(Theta, l = 2) <- c(4, -3.2, -0.2, -3.2, 4, 0, -0.2, 0, 1)

Theta

Theta <- new("EMMVNORM.Theta", c = 2, d = 3)

a.w(Theta) <- c(0.4, 0.6)

a.theta1.all(Theta) <- c(2, 10, -20, -2.4, -15.1, 30)

a.theta2.all(Theta) <- c(9, 0, 0, 0, 4, 0, 0, 0, 1, 
  4, -3.2, -0.2, -3.2, 4, 0, -0.2, 0, 1)

Theta