Had similar problem to John Finan above and used same fix. However have other problem with fit_mix_gaussian: it seems to be sensitive to magnitude to data. Using data scaled from appr. -0.7 to 5 it gives me a fit which is incorrect (data is skewed in some manner I have not identified). Changing the magnitude of the input vector via multiplication by some constants causes it to not converge for > 50k iterations.
Rather than systematically determine the failure modes, is there any info on requirements on input vector, such as normalization, etc.? I see normalization required for LSE's but for gaussian?