5.2. Residual Autocorrelation Function
The sky plots shown above provide visual evidence that the
I
= 0.5 plus quadrupole fit has small residuals generally, although they are
correlated to some degree. In this section, we quantify these correlations
with the residual autocorrelation function,
![]() | (25) |
where m
was defined in equation (23) and the sum is over
the Np(
)
distinct pairs with IRAS-predicted
separation dij within
= 100 km s-1 of a given value
. This definition
makes
(
)
insensitive to the values of
TF
and
v
(because
the
m,i
are themselves normalized using their maximum likelihood values for each
I),
but sensitive to the residual correlations that signal a poor fit.
In Figure 17, we
plot (
)
versus
for the IRAS plus quadrupole models, with
I
= 0.5, 0.1, and 1.0, as well as
the
I
= 0.6, no-quadrupole model. The error bars are described below. The model
that fits best according to the likelihood statistic,
I
= 0.5 plus quadrupole, shows no significant residual correlations
on any scale. The correlation function is
everywhere consistent with zero, as we would expect if the IRAS
velocity field plus the quadrupole is indeed a good fit to the data.
Indeed, the absence of residual correlations is the basis for a statement
made in Section 2.2.1, namely, that the
individual galaxy probabilities
P(m
,
cz) are independent, and thus validates the VELMOD likelihood
statistic
forw.
The other models shown in
Figure 17 all exhibit significant residual
correlations.
The I
= 0.6, no-quadrupole model has noticeable correlations on small and large
scales, as does
the
I
= 0.1 plus quadrupole model. Indeed, several of the values of
(
) for
I =
0.1 are so large that they are off-scale on the plot.
The
I
= 1.0 plus quadrupole model exhibits strong correlations for
2000
km s-1, although it is well behaved on large scales.