mixmodCluster {Rmixmod} | R Documentation |
Create an instance of the [MixmodCluster
] class
Description
This function computes an optimal mixture model according to the criteria furnished,
and the list of model defined in [Model
], using the algorithm specified in [Strategy
].
Usage
mixmodCluster(...)
Arguments
... |
all arguments are transfered to the MixmodCluster constructor. Valid arguments are:
- data:
frame containing quantitative,qualitative or heterogeneous data. Rows correspond to observations and columns correspond to variables.
- nbCluster:
numeric listing the number of clusters.
- dataType:
character. Type of data is "quantitative", "qualitative" or "composite". Set as NULL by default, type will be guessed depending on variables type.
- models:
a [Model ] object defining the list of models to run. For quantitative data, the model "Gaussian_pk_Lk_C" is called (see mixmodGaussianModel() to specify other models). For qualitative data, the model "Binary_pk_Ekjh" is called (see mixmodMultinomialModel() to specify other models).
- strategy:
a [Strategy ] object containing the strategy to run. Call mixmodStrategy() method by default.
- criterion:
list of character defining the criterion to select the best model. The best model is the one with the lowest criterion value. Possible values: "BIC", "ICL", "NEC", c("BIC", "ICL", "NEC"). Default is "BIC".
- weight:
numeric vector with n (number of individuals) rows. Weight is optionnal. This option is to be used when weight is associated to the data.
- knownLabels:
vector of size nbSample. it will be used for semi-supervised classification when labels are known. Each cell corresponds to a cluster affectation.
|
Value
Returns an instance of the [MixmodCluster
] class. Those two attributes will contain all outputs:
- results
a list of [MixmodResults
] object containing all the results sorted in ascending order according to the given criterion.
- bestResult
a S4 [MixmodResults
] object containing the best model results.
Author(s)
Florent Langrognet and Remi Lebret and Christian Poli ans Serge Iovleff, with contributions from C. Biernacki and G. Celeux and G. Govaert contact@mixmod.org
Examples
## A quantitative example with the famous geyser data set
data(geyser)
## with default values
mixmodCluster(geyser, nbCluster=2:6)
## A qualitative example with the birds data set
data(birds)
mixmodCluster(data=birds, nbCluster = 2:5, criterion= c("BIC","ICL","NEC"),
model = mixmodMultinomialModel())
## use graphics functions
xem <- mixmodCluster(data=geyser, nbCluster=3)
## Not run:
plot(xem)
hist(xem)
## End(Not run)
## get summary
summary(xem)
## A composite example with a heterogeneous data set
data(heterodata)
mixmodCluster(heterodata,2)
[Package
Rmixmod version 2.1.2.2
Index]