  Context. A lot of photometric data is produced by surveys such as Pan-STARRS,
LONEOS, WISE or Catalina. These data are a rich source of information about the
physical properties of asteroids. There are several possible approaches for
utilizing these data. Lightcurve inversion is a typical method that works with
individual asteroids. Our approach in this paper is statistical when we focused
on large groups of asteroids like dynamical families and taxonomic classes, and
the data were not sufficient for individual models.
  Aims. Our aim was to study the distributions of shape elongation $b/a$ and
the spin axis latitude $\beta$ for various subpopulations of asteroids and to
compare our results, based on Pan-STARRS1 survey, with statistics previously
done using different photometric data (Lowell database, WISE data).
  Methods. We use the LEADER algorithm to compare the $b/a$ and $\beta$
distributions for different subpopulations of asteroids. The algorithm creates
a cumulative distributive function (CDF) of observed brightness variations, and
computes the $b/a$ and $\beta$ distributions using analytical basis functions
that yield the observed CDF. A variant of LEADER is used to solve the joint
distributions for synthetic populations to test the validity of the method.
  Results. When comparing distributions of shape elongation for groups of
asteroids with different diameters $D$, we found that there are no differences
for $D < 25$ km. We also constructed distributions for asteroids with different
rotation periods and revealed that the fastest rotators with $P = 0 - 4$ h are
more spheroidal than the population with $P = 4 - 8$ h.
