VAR.boot: Simulate or bootstrap a VAR model
In tsDyn: Nonlinear Time Series Models with Regime Switching

VAR.sim

R Documentation

Simulate or bootstrap a VAR model

Description

Allow to either simulate from scratch (by providing coefficients) or bootstrap from an estimated VAR model,

Usage

VAR.sim(
  B,
  n = 200,
  lag = 1,
  include = c("const", "trend", "none", "both"),
  starting = NULL,
  innov = rmnorm(n, varcov = varcov),
  varcov = diag(1, nrow(B)),
  show.parMat = FALSE,
  returnStarting = FALSE,
  ...
)

VAR.boot(
  VARobject,
  boot.scheme = c("resample", "wild1", "wild2", "check"),
  seed,
  ...
)

Arguments

`B`	Matrix of coefficients.
`n`	Number of observations to simulate
`lag`	Number of lags of the VAR to simulate
`include`	Type of deterministic regressors to include in the VAR to simulate
`starting`	Starting values (matrix of dimension lag x k) for the VAR to simulate. If not given, set to zero.
`innov`	Innovations used for in the VAR to simulate. Should be matrix of dim n x k. By default multivariate normal.
`varcov`	Variance-covariance matrix for the innovations. By default identity matrix.
`show.parMat`	Logical. Should the parameter matrix be shown? Useful to understand how to give right input
`returnStarting`	Whether starting values are returned. Default to FALSE
`...`	Further arguments passed to the underlying (un-exported) `VAR.gen` function
`VARobject`	Object of class `VAR` generated by function `lineVar`
`boot.scheme`	The bootstrap scheme. See details.
`seed`	Optional. Seed for the random resampling function.

Details

For the bootstrap, the function resamples data from a given VAR model generated by lineVar, returning the resampled data. A residual recursive bootstrap is used, where one uses either a simple resampling, or the Wild bootstrap, either with a normal distribution (wild1) or inverting the sign randomly (wild2)

Value

A matrix with the resampled series.

Author(s)

Matthieu Stigler

Examples


## VAR.sim: simulate VAR as in Enders 2004, p 268
B1<-matrix(c(0.7, 0.2, 0.2, 0.7), 2)
var1 <- VAR.sim(B=B1, n=100, include="none")
ts.plot(var1, type="l", col=c(1,2))


B2<-rbind(c(0.5, 0.5, 0.5), c(0, 0.5, 0.5))
varcov<-matrix(c(1,0.2, 0.3, 1),2)
var2 <- VAR.sim(B=B2, n=100, include="const", varcov=varcov)
ts.plot(var2, type="l", col=c(1,2))

## VAR.boot: Bootstrap a VAR 
data(zeroyld)
mod <- lineVar(data=zeroyld,lag=1)
VAR.boot(mod)

tsDyn documentation built on Oct. 31, 2024, 5:08 p.m.