We have compared various methods of in vivo NMR spectral parameter estimation, namely a nonlinear fit of the free induction decay signal in the time domain (NLTD), a nonlinear fit of the fast Fourier transform of the FID data in the frequency domain using either a continuous Lorentzian model (NLLM) or a Fourier-sampled model (NLFM), and a time-domain linear prediction method using singular value decomposition (LPSVD). Monte Carlo simulations of 31P and 13C in vivo experiments were used to assess the bias and statistical uncertainties of spectral parameters obtained with each method. In the 31P case, all methods appear to be equivalent except the LPSVD method that led to significantly biased peak amplitudes (up to 28%). In the 13C case, the only methods able to recover the glycogen peak were the NLTD method and its equivalent in the frequency domain (NLFM). In both the 31P and the 13C cases simulations demonstrated that 256 data points were sufficient. These results demonstrate the feasibility and the robustness of a nonlinear fit of the FID data in the time domain, and we illustrate this on 31P and 13C data sets obtained in humans.