  We consider the problem of private linear computation (PLC) in a distributed
storage system. In PLC, a user wishes to compute a linear combination of $f$
messages stored in noncolluding databases while revealing no information about
the coefficients of the desired linear combination to the databases. In
extension of our previous work we employ linear codes to encode the information
on the databases. We show that the PLC capacity, which is the ratio of the
desired linear function size and the total amount of downloaded information,
matches the maximum distance separable (MDS) coded capacity of private
information retrieval for a large class of linear codes that includes MDS
codes. In particular, the proposed converse is valid for any number of messages
and linear combinations, and the capacity expression depends on the rank of the
coefficient matrix obtained from all linear combinations.
