RNGMIX-class {rebmix}R Documentation

Class "RNGMIX"

Description

Object of class RNGMIX.

Objects from the Class

Objects can be created by calls of the form new("RNGMIX", ...). Accessor methods for the slots are a.Dataset.name(x = NULL), a.rseed(x = NULL), a.n(x = NULL), a.Theta(x = NULL), a.Dataset(x = NULL, pos = 0), a.Zt(x = NULL), a.w(x = NULL), a.Variables(x = NULL), a.ymin(x = NULL) and a.ymax(x = NULL), where x and pos stand for an object of class RNGMIX and a desired slot item, respectively.

Slots

Dataset.name:

a character vector containing list names of data frames of size n \times d that d-dimensional datasets are written in.

rseed:

set the random seed to any negative integer value to initialize the sequence. The first file in Dataset.name corresponds to it. For each next file the random seed is decremented r_{\mathrm{seed}} = r_{\mathrm{seed}} - 1. The default value is -1.

n:

a vector containing numbers of observations in classes n_{l}, where number of observations n = ∑_{l = 1}^{c} n_{l}.

Theta:

a list containing c parametric family types pdfl. One of "normal", "lognormal", "Weibull", "gamma", "binomial", "Poisson", "Dirac" or circular "vonMises" defined for 0 ≤q y_{i} ≤q 2 π. Component parameters theta1.l follow the parametric family types. One of μ_{il} for normal, lognormal and von Mises distributions and θ_{il} for Weibull, gamma, binomial, Poisson and Dirac distributions. Component parameters theta2.l follow theta1.l. One of σ_{il} for normal and lognormal distributions, β_{il} for Weibull and gamma distributions, p_{il} for binomial distribution, κ_{il} for von Mises distribution and "NA" otherwise.

Dataset:

a list of data frames of size n \times d containing d-dimensional datasets. Each of the d columns represents one random variable. Numbers of observations n equal the number of rows in the datasets.

Zt:

a factor of true cluster membership.

w:

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

Variables:

a character vector containing types of variables. One of "continuous" or "discrete".

ymin:

a vector of length d containing minimum observations.

ymax:

a vector of length d containing maximum observations.

Author(s)

Marko Nagode


[Package rebmix version 2.10.3 Index]