DetectCpObj: DetectCpObj class constructor

Description

A constructor for the DetectCpObj class. The class DetectCpObj contains...

Usage

DetectCpObj(
  data = NULL,
  n_iterations = NULL,
  n_burnin = NULL,
  orders = NULL,
  time = NULL,
  phi_MCMC = NULL,
  phi_MCMC_01 = NULL,
  sigma_MCMC = NULL,
  sigma_MCMC_01 = NULL,
  delta_MCMC = NULL,
  I0_MCMC = NULL,
  I0_MCMC_01 = NULL,
  kernel_ts = NULL,
  kernel_epi = NULL,
  univariate_ts = NULL
)

Arguments

data: a vector or a matrix containing the values of the time series;
n_iterations: number of iterations of the MCMC algorithm;
n_burnin: number of MCMC iterations to exclude in the posterior estimate;
orders: a matrix where each row corresponds to the output order of the corresponding iteration;
time: computational time in seconds;
phi_MCMC: traceplot for \(\gamma\).
phi_MCMC_01: a \(0/1\) vector, the \(n\)-th element is equal to \(1\) if the proposed \(\phi\) was accepted, \(0\) otherwise.
sigma_MCMC: traceplot for \(\sigma\).
sigma_MCMC_01: a \(0/1\) vector, the \(n\)-th element is equal to \(1\) if the proposed \(\sigma\) was accepted, \(0\) otherwise.
delta_MCMC: traceplot for \(\delta\).
I0_MCMC: traceplot for \(I_0\).
I0_MCMC_01: a \(0/1\) vector, the \(n\)-th element is equal to \(1\) if the proposed \(I_0\) was accepted, \(0\) otherwise.
kernel_ts: if TRUE data are time series.
kernel_epi: if TRUE data are epidemic diffusions.
univariate_ts: TRUE/FALSE if time series is univariate or not.