difonzo1 — Multivariate temporal disaggregation with transversal constraint
[y,res]=difonzo1(Y,x,z,ta,s,typemod)
NxM real vector
x = nxM real vector
z = nx1 ---> high frequency transversal constraint with nz obs.
ta = type of disaggregation
ta=1 ---> sum (flow)
ta=0 ---> average (index)
ta=i ---> i th element (stock) ---> interpolation
s = number of high frequency data points for each low frequency data points
s= 4 ---> annual to quarterly
s=12 ---> annual to monthly
s= 3 ---> quarterly to monthly
typemod = model for the high frequency innovations
typemod='wn' ---> multivariate white noise
typemod='rw' ---> multivariate random walk
y = High frequency estimate
res = a results tlist with:
- res('meth') = 'Multivariate difonzo'
- res('typemod') = type of the model for the high frequency innovations
- res('ta') = type of disaggregation
- res('nobs_lf') = nobs. of low frequency data
- res('nobs_hf') = nobs. of high-frequency data
- res('pred') = number of extrapolations
- res('s') = frequency conversion between low and high freq.
- res('diff') = Degree of differencing
- res('y') = high frequency estimate
- res('y_lf') = low frequency data
- res('indicator') = high frequency indicators
- res('transversal') = data for the transversal constraint
- res('y_dt') = high frequency estimate: standard deviation
- res('resid') = high frequency residuals
- res('resid_U') = low frequency residuals
- res('beta') = estimated model parameters
- res('sd') = standard deviation of the estimated model parameters
[y,res] = difonzo1(Y,x,z,0,4,'rw') Provides quarterly disaggregation of (23x2) matrix Y (representing 2 annual data) with (92x2) matrix x (representing 2 quarterly series) and transversality constraint represented by the (92x1) matrix z. Annual series are built by averaging quarterly series (4th argument is 0); the order of aggregation is 4 (fifth argument); residuals are assumed to follow a multivariate random walk (sixth argument is 'rw').