simulateData | R Documentation |
Simulate data according to the funLBM model with K=4 groups for rows and L=3 groups for columns.
simulateData(n = 100, p = 100, t = 30)
n |
The number of rows (individuals) of the simulated data array, |
p |
The number of columns (functional variables) of the simulated data array, |
t |
The number of measures for the functions of the simulated data array. |
The resulting object contains:
data |
data array of size n x p x t |
row_clust |
Group memberships of rows |
col_clust |
Group memberships of columns |
C. Bouveyron, L. Bozzi, J. Jacques and F.-X. Jollois, The Functional Latent Block Model for the Co-Clustering of Electricity Consumption Curves, Journal of the Royal Statistical Society, Series C, 2018 (https://doi.org/10.1111/rssc.12260).
funLBM
set.seed(12345) # Simulate data and co-clustering X = simulateData(n = 30, p = 30, t = 15) # Co-clustering with funLBM out = funLBM(X$data,K=4,L=3) # Visualization of results plot(out,type='blocks') plot(out,type='proportions') plot(out,type='means') # Evaluating clustering results ari(out$col_clust,X$col_clust) ari(out$row_clust,X$row_clust)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.