result since at high redshift quasar clustering would be little affected by non-linear physics. Finally, for the sake of completeness, the likelihood analysis was extended to other well-known approaches, such as jackknife and bootstrap methods. In this way we compared the outcomes of diverse error estimators, confirming that jackknife and bootstrap resampling methods overestimate the 2PACF error bars while pure random catalogues approach underestimate them. These analyses are presented in the Appendix section.

Acknowledgements {#acknowledgements .unnumbered}
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We are grateful to Joel C. Carvalho for his support in numerical programming, and to him and Jailson Alcaniz for insightful discussions. The authors thank the CAPES PVE project 88881.064966/2014-01, within the [*Science without Borders Program*]{}. CPN, GCC, and HSX also acknowledge the Brazilian funding agencies FAPERJ (Pós-doc Nota 10), CNPq, and FAPESP, respectively, for the financial support.

The jackknife and bootstrap error estimators
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We estimate the error bars of the 2PACF using the well-known jackknife and bootstrap resampling methods [@Myers; @Ross; @Shanks; @Norberg].

For the jackknife procedure, we first create 35 quasars jackknifed samples using the original DR12Q studied here, and then we measure the 2PACF in each one of them. The error bars are calculated using the covariance matrix, which 