  In this paper we apply to gravitational waves from non-spinning binary
systems a recently intro- duced frequentist methodology to calculate
analytically the error for a maximum likelihood estimate (MLE) of physical
parameters. While existing literature focuses on using the Cramer Rao Lower
bound (CRLB) and Monte Carlo simulations, we use a power expansion of the bias
and covariance in inverse powers of the signal to noise ratio. The use of
higher order derivatives of the likelihood function in the expansions makes the
prediction also sensitive to the secondary lobes of the MLE probability
distribution. We discuss conditions for validity of the CRLB and predict new
features in regions of the parameter space currently not explored. For example,
we see how the bias can become the most important contributor to the
parameters' errors for high mass systems (200M and above).
