missingValues-methods: Return the missing values of a component or a cluster class.

In MixAll: Clustering and Classification using Model-Based Mixture Models

Description

The missing methods allow the user to get the imputed mssing values from a mixture model.

Usage

missingValues(x)

## S4 method for signature 'ClusterMixedDataModel'
missingValues(x)

## S4 method for signature 'ClusterDiagGaussianComponent'
missingValues(x)

## S4 method for signature 'ClusterDiagGaussian'
missingValues(x)

## S4 method for signature 'ClusterGammaComponent'
missingValues(x)

## S4 method for signature 'ClusterGamma'
missingValues(x)

## S4 method for signature 'ClusterCategoricalComponent'
missingValues(x)

## S4 method for signature 'ClusterCategorical'
missingValues(x)

## S4 method for signature 'ClusterPoissonComponent'
missingValues(x)

## S4 method for signature 'ClusterPoisson'
missingValues(x)

## S4 method for signature 'ClusterPredict'
missingValues(x)

## S4 method for signature 'ClusterPredictMixedData'
missingValues(x)

## S4 method for signature 'KmmComponent'
missingValues(x)

## S4 method for signature 'KmmModel'
missingValues(x)

Arguments

x	an object that can return the imputed missing values

Value

A matrix with three columns (row index, column index, value)

Examples

## Not run: 
## add 10 missing values as random
data(geyser)
x = as.matrix(geyser); n <- nrow(x); p <- ncol(x);
indexes <- matrix(c(round(runif(5,1,n)), round(runif(5,1,p))), ncol=2);
x[indexes] <- NA;
## estimate model (using fast strategy, results may be misleading)
model <- clusterDiagGaussian(data=x, nbCluster=2:3, strategy = clusterFastStrategy())
missingValues(model)

## End(Not run)

MixAll documentation built on Sept. 12, 2019, 5:05 p.m.