Description Usage Arguments Value Examples
Generates n random samples from a G-Latent Variable Model. The caller can specify the graph structure on the latent variables via several parameters. The magnitude of the non-zero entries in the population precision matrix can also be specified. Observed variables are assigned uniformly at random to K groups with minimum size m.
1 2 3 | gforce.generator(K, d, n, m, graph = "DeltaC", num_hubs = NULL,
band_size = 3, cov_gap_mult = 1, error_base = 0.25,
error_add = 0.25, corr_value = 0.3, normalize = TRUE)
|
K |
number of clusters. |
d |
dimension of the observed random vector. |
n |
number of samples. |
m |
minimal group size. |
graph |
latent graph structure. Can be 'scalefree', 'hub', 'band', 'identity' or 'DeltaC'. |
num_hubs |
number of hubs in the latent graph. Ignored unless |
band_size |
size of bands in the latent graph. Ignored unless |
cov_gap_mult |
scales the size of Δ C. Ignored unless |
error_base |
minimum variance of errors. |
error_add |
size of range of possible variances for errors. |
corr_value |
size of off diagonal entries in latent precision matrix. |
normalize |
logical. If |
An S3 object with the slots Z,E,X,group_assignments,CStar,Theta_Star
1 2 3 | dat <- gforce.generator(5,20,20,3)
dat <- gforce.generator(10,100,100,3,graph='hub',num_hubs=2)
dat <- gforce.generator(10,100,100,3,graph='band',band_size=3)
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