generateTestData_2D {clusternomics} | R Documentation |
Generate simple 2D dataset with two contexts, where the data are generated from Gaussian distributions. The generated output contains two datasets, where each dataset contains 4 global clusters, originating from two local clusters in each context.
generateTestData_2D(groupCounts, means, variances = NULL)
groupCounts |
Number of data samples in each global cluster.
It is assumed to be a vector of four elements: |
means |
Means of the simulated clusters.
It is assumed to be a vector of two elements: |
variances |
Optionally, it is possible to specify different variance
for each of the clusters. The variance is assumed to be a vector
of two elements: |
Returns the simulated datasets together with true assignmets.
data |
List of datasets for each context. This can be used as an input
for the |
groups |
True cluster assignments that were used to generate the data. |
groupCounts <- c(50, 10, 40, 60) means <- c(-1.5,1.5) testData <- generateTestData_1D(groupCounts, means) # Use the dataset as an input for the contextCluster function for testing datasets <- testData$data