RT Report
T1 An exact multivariate model-based structural decomposition
A1 Casals Carro, José
A1 Jerez Méndez, Miguel
A1 Sotoca López, Sonia
AB We describe a simple procedure for decomposing a vector of time series into trend, cycle, seasonal and irregular components. Contrary to common practice, we do not assume these components to be orthogonal conditional on their past. However, the state-space representation employed assures that their smoothed estimates converge to exact values, with null variances and covariances. Among ather implications, this means that the components are not revised when the sample increases. The practical application of the method is illustrated both with simulated and real data.
PB Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
YR 2000
FD 2000
LK https://hdl.handle.net/20.500.14352/64235
UL https://hdl.handle.net/20.500.14352/64235
LA eng
DS Docta Complutense
RD 12 may 2025