\langle{{\mbox{\boldmath $d$}}}\rangle_{{{\mit \Theta}}}\right)
   \right],
\label{eq2-2}$$ where ${{\mbox{\boldmath $d$}}}$ is the data vector ${{\mbox{\boldmath $d$}}} = (d_1, d_2, \cdots,
d_N)^{\rm T}$ and $R$ is the $N\times N$ correlation matrix given by $$R({{\mit \Theta}}) =
    \left\langle
      \left({{\mbox{\boldmath $d$}}} - \left\langle {{\mbox{\boldmath $d$}}}
        \right\rangle_{{\mit \Theta}}\right) 
      \left({{\mbox{\boldmath $d$}}} - \left\langle {{\mbox{\boldmath $d$}}}
        \right\rangle_{{\mit \Theta}}\right)^{\rm T}
    \right\rangle_{{{\mit \Theta}}} =
    \left\langle {{\mbox{\boldmath $d$}}} {{\mbox{\boldmath $d$}}}^{\rm T} \right\rangle_{{{\mit \Theta}}} -
    \left\langle {{\mbox{\boldmath $d$}}} \right\rangle_{{{\mit \Theta}}}
    \left\langle {{\mbox{\boldmath $d$}}}^{\rm T} \right\rangle_{{{\mit \Theta}}}.
\label{eq2-3}$$ In the above notations, $\langle\cdots\rangle_{{\mit \Theta}}$ indicates the ensemble average over the statistical realizations of the universe [see, e.g., @pee80] for an assumed set of model parameters ${{\mit \Theta}}$. The correlation matrix therefore explicitly depends on the model parameters.

In the analysis of redshift surveys, the observed set of data is primarily a set of the positions of galaxies in redshift space. The density field is derived from this primary data, which is one of the most fundamental information of our universe in redshift surveys. Therefore, it is natural that the data $D$ is identified as the number density field of galaxies in redshift space. For this purpose, the redshift space is pixelized to obtain a discretized set of galaxy counts. Thus, the set of 