  We perform a principal component analysis (PCA) of two one-dimensional
lattice models belonging to distinct nonequilibrium universality classes -
directed bond percolation and branching and annihilating random walks with even
number of offspring. We find that the uncentered PCA of datasets storing
various system's configurations can be successfully used to determine the
critical properties of these nonequilibrium phase transitions. In particular,
in both cases, we obtain good estimates of the critical point and the dynamical
critical exponent of the models. For directed bond percolation we are,
furthermore, able to extract critical exponents associated with the correlation
length and the order parameter. We discuss the relation of our analysis with
low-rank approximations of datasets.
