RNGMIX-class | R Documentation |
"RNGMIX"
Object of class RNGMIX
.
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.
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"
, "Gumbel"
, "binomial"
, "Poisson"
, "Dirac"
, "uniform"
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, Gumbel and von Mises distributions, θ_{il} for Weibull, gamma, binomial, Poisson and Dirac distributions and a for uniform distribution.
Component parameters theta2.l
follow theta1.l
. One of σ_{il} for normal, lognormal and Gumbel distributions, β_{il} for Weibull and gamma distributions, p_{il} for binomial distribution, κ_{il} for von Mises distribution and b for uniform distribution.
Component parameters theta3.l
follow theta2.l
. One of ξ_{il} \in \{-1, 1\} for Gumbel distribution.
Dataset
:a list of length n_{\mathrm{D}} 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.
Marko Nagode
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