grou_mle: Computes the GrOUs MLE of a batch of data

In ntwk: Statistical Inference for Network Time Series

Description

Computes the GrOUs MLE of a batch of data

Usage

grou_mle(
  times,
  data,
  adj = NA,
  thresholds = NA,
  div = 1000,
  mode = "node",
  output = "vector"
)

Arguments

times	Times at which data is given
data	Values to compute the MLE with.
adj	Adjacency matrix of the underlying network.
thresholds	Jump threshold values.
div	Batch size/divisor to avoid large memory allocation.
mode	GrOU mode: either "node" (psi-GrOU) or "network" (theta-GrOU).
output	Output type: either "vector"or "matrix".

Value

The GrOU MLE in matrix/vector form in theta or psi parametrisation.

Examples

n <- 1000
d <- 10
times <- seq(n)
delta_time <- 0.01
noise <- matrix(rnorm(n * d, sd = sqrt(delta_time)), ncol = d)
data <- construct_path(
  diag(d),
  noise = noise, y_init = rep(0, d), delta_time = delta_time
)
grou_mle(times, data, adj = diag(d), div = 1e2)

ntwk documentation built on Sept. 13, 2021, 9:07 a.m.