kernelIntensities: Direct kernel estimator intensities

In ppsbm: Clustering in Longitudinal Networks

Description

Compute smooth intensities with direct kernel estimation of intensities relying on a classification tau. This can be used with the values τ obtained on a dataset with mainVEM function run with 'hist' method.

Usage

kernelIntensities(data, tau, Q, n, directed, rho = 1, sparse = FALSE,
  nb.points = 1000)

Arguments

data	List with 3 components: data$time.seq : sequence of observed time points of the m-th event (M-vector) data$type.seq : sequence of observed values convertNodePair(i,j,n,directed) (auxiliary.R) of process that produced the mth event (M-vector) $Time - [0,data$Time] is the total time interval of observation
tau	τ
Q	Total number of groups
n	Total number of nodes
directed	Boolean for directed (TRUE) or undirected (FALSE) case
rho	ρ
sparse	Boolean for sparse (TRUE) or not sparse (FALSE) case
nb.points	Number of points

Details

Warning : sparse case not implemented !!!

Examples

# The generated_sol_kernel was generated calling mainVEM with kernel method on the generated_Q3 data
# (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)

ppsbm documentation built on May 1, 2019, 11:26 p.m.