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We explore different estimators of the local non-linear coupling parameter,fNL, based on the binned bispectrum presented in Bucher et al. Usingsimulations of Wilkinson Microwave Anisotropy Probe (WMAP)-7yr data, we comparethe performance of a regression neural network with a \chi^2-minimization andstudy the dependence of the results on the presence of the linear term in theanalysis and on the use of inpainting for masked regions. Both methods obtainsimilar results and are robust to the use of inpainting, but the neural networkestimator converges considerably faster. We also examine the performance of asimplified \chi^2 estimator that assumes a diagonal matrix and has the linearterm subtracted, which considerably reduces the computational time; in thiscase inpainting is found to be crucial. The estimators are also applied to realWMAP-7yr data, yielding constraints at 95% confidence level of -3< fNL <83.

Exploring local fNL estimators based on the binned bispectrum