  Mode fitting or "peak-bagging" is an important procedure in helioseismology
allowing one to determine the various mode parameters of solar oscillations.
Here we describe a way of reducing the systematic bias in the fits of certain
mode parameters that are seen when using "local" fitting techniques to analyse
the sun-as-a-star p-mode power spectrum. To do this we have developed a new
"pseudo-global" fitting algorithm designed to gain the advantages of fitting
the entire power spectrum, but without the problems involved in fitting a model
incorporating many hundreds of parameters.
  We have performed a comparative analysis between the local and pseudo-global
peak-bagging techniques by fitting the "limit" profiles of simulated
helioseismic data. Results show that for asymmetric modes the traditional
fitting technique returns systematically biased estimates of the central
frequency parameter. This bias is significantly reduced when employing the
pseudo-global routine. Similarly, we show that estimates of the background
returned from the pseudo-global routine match the input values much more
closely than the estimates from the local fitting method.
  We have also used the two fitting techniques to analyse a set of real solar
data collected by the Global Oscillations at Low Frequencies (GOLF) instrument
on board the ESA/NASA Solar and Heliospheric Observatory (SOHO) spacecraft.
Similar differences between the estimated frequencies returned by the two
techniques are seen when fitting both the real and simulated data. We show that
the background fits returned by the pseudo-global routine more closely match
the estimate of the background one can infer from interpolating between fits to
the high and low frequency ends of the p-mode power spectrum.
