I derive, using the effective field theory of biased tracers,
the conditional likelihood for observing a specific tracer field
given an underlying matter field. This likelihood is necessary for
Bayesianinference methods. I start from the assumption of Gaussian
noise for the tracer field, and then discuss the impact of nonGaussian
noise (which includes the stochastic corrections to the tracer
bispectrum) and of higherderivative terms. I comment on how
these corrections can affect the results of current applications
of Bayesian inference. I also comment on possible extensions, with a
particular eye towards the inclusion of primordial nonGaussianity.
