Vmiss function

VARMA Model with Missing Value

Assuming that the model is known, this program estimates the value of a missing data point. The whole data point is missing.

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

Arguments

• zt: A T-by-k data matrix of a k-dimensional time series
• piwgt: The pi-weights of a VARMA model defined as piwgt=[pi0, pi1, pi2, ....]
• sigma: Positive definite covariance matrix of the innovations
• tmiss: Time index of the missing data point
• cnst: Constant term of the model
• output: A logical switch to control output

Details

Use the least squares method to estimate a missing data point. The missing is random.

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

Vpmiss

Examples

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