We propose a new version of Stein's method of exchangeable pairs, which,
given a suitable exchangeable pair (W,W′) of real-valued random variables,
suggests the approximation of the law of W by a suitable absolutely
continuous distribution. This distribution is characterized by a first order
linear differential Stein operator, whose coefficients γ and η are
motivated by two regression properties satisfied by the pair (W,W′).
Furthermore, the general theory of Stein's method for such an absolutely
continuous distribution is developed and a general characterization result as
well as general bounds on the solution to the Stein equation are given. This
abstract approach is a certain extension of the theory developed in the papers
\cite{ChSh} and \cite{EiLo10}, which only consider the framework of the density
approach, i.e. η≡1. As an illustration of our technique we prove a
general plug-in result, which bounds a certain distance of the distribution of
a given random variable W to a Beta distribution in terms of a given
exchangeable pair (W,W′) and provide new bounds on the solution to the Stein
equation for the Beta distribution, which complement the existing bounds from
\cite{GolRei13}. The abstract plug-in result is then applied to derive bounds
of order n−1 for the distance between the distribution of the relative
number of drawn red balls after n drawings in a P\'olya urn model and the
limiting Beta distribution measured by a certain class of smooth test
functions.Comment: 37 pages, essential overlap with preprint "Stein's method of
exchangeable pairs for absolutely continuous, univariate distributions with
applications to the Polya urn model" (arXiv: 1207.0533) but completely new
written and with several additional results and also some omission