Vpmiss function

Partial Missing Value of a VARMA Series

Assuming that the data is only partially missing, this program estimates those missing values. The model is assumed to be known.

Vpmiss(zt, piwgt, sigma, tmiss, mdx, cnst = NULL, output = T)

Arguments

• zt: A T-by-k data matrix of a k-dimensional time series
• piwgt: pi-weights of the model in the form piwgt[pi0, pi1, pi2, ....]
• sigma: Residual covariance matrix
• tmiss: Time index of the partially missing data point
• mdx: A k-dimensional indicator with "0" denoting missing component and ""1" denoting observed value.
• cnst: Constant term of the model
• output: values of the partially missing data

Returns

Estimates of the missing values

References

Tsay (2014, Chapter 6). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

Author(s)

Ruey S. Tsay

See Also

Vmiss

Examples

#data("mts-examples",package="MTS")
#gdp=log(qgdp[,3:5])
#m1=VAR(gdp,1)
#piwgt=m1$Phi; cnst=m1$Ph0; Sig=m1$Sigma
#mdx=c(0,1,1)
#m2=Vpmiss(gdp,piwgt,Sig,50,mdx,cnst)