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How to find the dependencies of a table in redshift? 

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However, we find that for the data used the inclusion of morphological information does not have a statistically significant benefit for photometric redshift estimation with the techniques employed here.
These results have strong implications for the analysis of redshift surveys at intermediate redshift.
We present a simple and powerful empirical method to constrain photometric redshift uncertainties in the absence of spectroscopic redshifts.
The methods that we develop are applicable to general photometric redshift surveys.
We show that the redshift distribution of our sample is in excellent agreement with smaller and much deeper photometric and spectroscopic redshift surveys.
Finally, reconstruction can improve the determination of Ω and b from joint analyses of redshift and peculiar velocity surveys because it provides a fully nonlinear prediction of the peculiar velocity distribution at each point in redshift space.
The new high signal-to-noise ratio spectra therefore allow us to measure the redshift of 18 sources.
Our analysis proves that photometric redshift techniques can and must be used to extend the range of applicability of the spectroscopic redshift measurements.

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