  A coagulation process is studied in a set of random masses, in which two
randomly chosen masses and the smallest mass of the set multiplied by some
fixed parameter $\omega\in [-1,1]$ are iteratively added. Besides masses (or
primary variables), secondary variables are also considered that are correlated
with primary variables and coagulate according to the above rule with
$\omega=0$. This process interpolates between known statistical physical
models: The case $\omega=-1$ corresponds to the strong disorder renormalisation
group transformation of certain disordered quantum spin chains whereas
$\omega=1$ describes coarsening in the one-dimensional Glauber-Ising model. The
case $\omega=0$ is related to the renormalisation group transformation of a
recently introduced graph with a fat-tail edge-length distribution. In the
intermediate range $-1<\omega<1$, the exponents $\alpha_{\omega}$ and
$\beta_{\omega}$ that characterise the growth of the primary and secondary
variable, respectively, are accurately estimated by analysing the differential
equations describing the process in the continuum formulation. According to the
results, the exponent $\alpha_{\omega}$ varies monotonically with $\omega$
while $\beta_{\omega}$ has a maximum at $\omega=0$.
