  This paper introduces and describes the R package ts.extend, which adds
probability functions for stationary Gaussian ARMA models and some related
utility functions for time-series. We show how to use the package to compute
the density and distributions functions for models in this class, and generate
random vectors from this model. The package allows the user to use marginal or
conditional models using a simple syntax for conditioning variables and
marginalised elements. This allows users to simulate time-series vectors from
any stationary Gaussian ARMA model, even if some elements are conditional
values or omitted values. We also show how to use the package to compute the
spectral intensity of a time-series vector and implement the
permutation-spectrum test for a time-series vector to detect the presence of a
periodic signal.
