Nonlinear regression with a complex-valued model function
- To: mathgroup at smc.vnet.net
- Subject: [mg29889] Nonlinear regression with a complex-valued model function
- From: mike.trefry at csiro.au (Mike Trefry)
- Date: Tue, 17 Jul 2001 01:00:34 -0400 (EDT)
- Sender: owner-wri-mathgroup at wolfram.com
Hi Everyone, I have an application where I am trying to fit a trajectory in the complex plane to a set of complex data points. The trajectory is parameterised by several real parameters. I can find MLE values for the parameters easily by least-squares, i.e. minimising the squares of the distances between the data points and the matching points on the trajectory, but I am uncertain about how to generate confidence intervals for the parameters. These are usually calculated using gradients of the model (trajectory) function, which is complex in this case. Can anyone point me to a succinct generalisation of the linear confidence interval theory to complex-valued model functions? Thanks, Mike Trefry <mike.trefry at csiro.au> CSIRO Land and Water Australia