R: Generate synthetic data from a time-varying parameter model

simTVP {shrinkTVP}

R Documentation

Generate synthetic data from a time-varying parameter model

Description

simTVP generates synthetic data from a time-varying parameter model. The covariates are always generated i.i.d. from a Normal(0,1) distribution.

Usage

simTVP(
  N = 200,
  d = 3,
  sv = FALSE,
  DTG = FALSE,
  sigma2 = 1,
  theta,
  beta_mean,
  sv_mu = 0,
  sv_phi = 0.98,
  sv_sigma2 = 0.2,
  a_psi = 0.5,
  c_psi = 2,
  rho = 0.9
)

Arguments

`N`	integer > 2. Indicates the length of the time series to be generated. The default value is 200.
`d`	positive integer. Indicates the number of covariates to simulate. The default value is 3.
`sv`	logical value. If set to `TRUE`, the data will be generated with stochastic volatility for the errors of the observation equation using `svsim`. The default value is FALSE.
`DTG`	logical value. If set to `TRUE`, the betas will be generated as dynamic triple gamma processes. The default value is FALSE.
`sigma2`	positive real number. Determines the variance of the errors of the observation equation. Ignored if sv is `TRUE`. The default value is 1.
`theta`	(optional) vector containing positive real numbers. If supplied, these determine the variances of the innovations of the state equation. Otherwise, the elements of `theta` are generated from a X^2(1) distribution. Has to be of length `d` or an error will be thrown.
`beta_mean`	(optional) vector containing real numbers. If supplied, these determine the mean of the initial value of the state equation. Otherwise, the elements of `beta_mean` are generated from a Normal(0,1) distribution. Has to be of length `d` or an error will be thrown.
`sv_mu`	real number. Determines the mean of the logarithm of the volatility. Ignored if `sv` is `FALSE`. The default value is 0.
`sv_phi`	real number between -1 and 1. Determines the persistence of the SV process. Ignored if `sv` is `FALSE`. The default value is 0.98.
`sv_sigma2`	positive, real number. Determines the variance of the innovations of the logarithm of the volatility. Ignored if `sv` is `FALSE`. The default value is 0.2.
`a_psi`	positive, real number. Determines the pole parameter of the dynamic triple gamma process. Ignored if `DTG` is `FALSE`. The default value is 0.5.
`c_psi`	positive, real number. Determines the tail parameter of the dynamic triple gamma process. Ignored if `DTG` is `FALSE`. The default value is 2.
`rho`	real number between 0 and 1. Determines the persistence of the dynamic triple gamma process. Ignored if `DTG` is `FALSE`. The default value is 0.9

Value

The value returned is a list object containing:

data

data frame that holds the simulated data.

true_vals

list object containing:

theta: the values of theta used in the data generating process.
beta_mean: the values of beta_mean used in the data generating process.
beta: the true paths of beta used for the data generating process.
sigma2: the value(s) of sigma2 used in the data generating process.
lambda_p: the true paths of lambda_p used for the data generating process. Not returned if DTG is FALSE.
lambda_p_0: the values of lambda_p_0 used for the data generating process. Not returned if DTG is FALSE.
kappa_p: the true paths of kappa_p used for the data generating process. Not returned if DTG is FALSE.
psi: the true paths of psi used for the data generating process. Not returned if DTG is FALSE.

Author(s)

Peter Knaus peter.knaus@wu.ac.at

Examples

# Generate a time series of length 300
res <- simTVP(N = 300)

# Extract the generated data
data <- res$data

# Now with stochastic volatility
res_sv <- simTVP(N = 300, sv = TRUE)

# Now with dynamic triple gamma process
res_DTG <- simTVP(N = 300, DTG = TRUE, c_psi = 1)

[Package shrinkTVP version 3.0.1 Index]