In this paper we apply to gravitational waves from nonspinning binary systems a recently introduced frequentist methodology to calculate analytically the error for a maximum likelihood estimate of physical parameters. While existing literature focuses on using the Cramer Rao Lower bound 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 maximum likelihood estimate probability distribution. We discuss conditions for validity of the Cramer Rao Lower bound 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 ($200M_{\odot }$ and above).

• Received 1 July 2010

DOI:https://doi.org/10.1103/PhysRevD.82.124065