Multivariate temporal disaggregation with transversal constraint
[y,res]=difonzo(namey,namex,namez,d,arg1, ,argn)
nameY = a (NxM) matrix, a list of M vectors or ts or a string vector representing names such objects
---> M series of low frequency data with N observations
namex = a (nxM) matrix, a list of M vectors or ts or a string vector representing names such objects
---> M series of high frequency data with n observations
namez = a (nx1) vector or a ts
---> high frequency transversal constraint
d = objective function to be minimized: volatility of
- d=0 ---> levels
- d=1 ---> first differences
- d=2 ---> second differences
argi=an argument which can be
- the string 'divfq=n' where n is the number of high frequency data points for each low frequency data points
- the string 'ta=n' where n is the aggregation type:
* n=-1 (default) ---> sum (flow)
* n=0 ---> average (index)
* n=i ---> i th element (stock) ---> interpolation
- the string 'typemod=n' where n is either 'wn' for the multivariare white noise model (default) or 'rw' for the multivariate random walk model
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
- res('namey') = Name of the high frequency aggregate
- res('namex') = Name of the low frequency indicators
- res('namez') = Name of the high frequency transversal constraint
[y,res] = difonzo(Y,x,z,'ta=0','typemod=rw') //Example taken from function difonzo_d. 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 (ta=0); the order of aggregation is determined by the function; // residuals are assumed to follow a multivariate random walk ('typemod=rw').