Automatic Identification and Forecasting of Structural Unobserved Components Models with UComp

Automatic Identification and Forecasting of Structural Unobserved Components Models with UComp

unobserved components models, state space models, Kalman filter, fixed point
smoother, maximum likelihood, R, MATLAB, Octave.

UComp is a powerful library for building unobserved components models, useful for
forecasting and other important operations, such us de-trending, cycle analysis, seasonal
adjustment, signal extraction, etc. One of the most outstanding features that makes
UComp unique among its class of related software implementations is that models may
be built automatically by identification algorithms (three versions are available). These
algorithms select the best model among many possible combinations. Another relevant
feature is that it is coded in C++, opening the door to link it to different popular and
widely used environments, like R, MATLAB, Octave, Python, etc. The implemented models for the components are more general than the usual ones in the field of unobserved
components modeling, including different types of trend, cycle, seasonal and irregular components, input variables and outlier detection. The automatic character of the algorithms
required the development of many complementary algorithms to control performance and
make it applicable to as many different time series as possible. The library is open source
and available in different formats in public repositories. The performance of the library
is illustrated working on real data in several varied examples.

Diego J. Pedregal

https://www.jstatsoft.org/article/view/v103i09

Universidad de Castilla-La Mancha

July 2022

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