The book titled "Linear Time Series With Matlab and Octave" written
by Víctor Gómez is forthcoming in the Statistics and Computing
Series of Springer Verlag.

The motivation of this book is to provide time series students and
researchers with a software package called SSMMATLAB, written in
MATLAB, that will allow them to work with general state space
models. Since many time series models used in practice can be put
into state space form, special functions have been written for the
most usual ones, such as multiplicative ARIMA and VARMA models,
cointegrated VARMA models, VARMAX models in echelon form, transfer
function models, univariate structural models, like those
considered by Harvey (1993) or Kitagawa and Gersch (1996), and
ARIMA model-based (AMB) unobserved components models (Gómez and
Maravall 2001). However, if the user intends to work with more
sophisticated state space models that are not available in standard
commercial packages for time series analysis or econometrics, he
can program his own model in SSMMATLAB and carry out model
estimation, interpolation, forecasting and smoothing.

All the programs contained in SSMMATLAB can also run in the free
software OCTAVE platform. The series can be univariate or
multivariate and the state space model can be very general. It may
have time-varying system matrices, exogenous inputs, regression
effects, incompletely specified initial conditions, such as those
that arise with nonstationary VARMA models, and missing values. A
brief description of SSMMATLAB appeared in Gómez (2015).