kernelIntensities {ppsbm} | R Documentation |
Direct kernel estimator intensities
Description
Compute smooth intensities with direct kernel estimation of intensities relying on a classification \tau
.
This can be used with the values \tau
obtained on a dataset with mainVEM function.
Usage
kernelIntensities(
data,
tau,
Q,
n,
directed,
rho = 1,
sparse = FALSE,
nb.points = 1000 * data$Time
)
Arguments
data |
List with 3 components:
|
tau |
Matrix with size |
Q |
Total number of groups. |
n |
Total number of nodes, |
directed |
Boolean for directed (TRUE) or undirected (FALSE) case |
rho |
Either 1 (non sparse case) or vector with length |
sparse |
Boolean for sparse (TRUE) or not sparse (FALSE) case. |
nb.points |
Number of points for the kernel estimation. |
Details
Warning: sparse case not implemented !!!
Examples
# The generated_sol_kernel solution was generated calling mainVEM
# with kernel method on the generated_Q3$data dataset.
# (50 individuals and 3 clusters)
data <- generated_Q3$data
n <- 50
Q <- 3
# Compute smooth intensity estimators
sol.kernel.intensities <- kernelIntensities(data,generated_sol_kernel$tau,Q,n,directed=FALSE)