[Mne_analysis] Goodness of fit statistic for TF-MxNE solution?

[Alexandre Gramfort]

hi Per,

compute the R2 at each time point or globally after vectorizing the output
to one vector of size n_sensors x n_times

ok?

A

On Fri, Oct 3, 2014 at 5:41 PM, Per Arnold Lysne <lysne at unm.edu> wrote:
> Hi Alex,
>
>     R^2 would be perfect, since it is easy to interpret and has the accompanying F-test. However, R^2 only applies to a single outcome variable, being calculated as SS_reg/SS_total. This is where I turned to Wilk's Lambda, being the multivariate extension of R^2, or det(SSCP_res)/det(SSCP_total). Unfortunately the determinants cannot be calculated on data that is not full rank, which leads to the questions I am asking about PCA in the other thread.
>
>     Am I missing something? I am not operating on the whitened data.
>
>     Agreed that butterfly plots are an excellent visual verification of fit, and I am already producing them.
>
>     Thanks again,
>
> -Per
>
> ________________________________________
> From: mne_analysis-bounces at nmr.mgh.harvard.edu <mne_analysis-bounces at nmr.mgh.harvard.edu> on behalf of Alexandre Gramfort <alexandre.gramfort at telecom-paristech.fr>
> Sent: Friday, October 3, 2014 3:30 AM
> To: Discussion and support forum for the users of MNE Software
> Subject: Re: [Mne_analysis] Goodness of fit statistic for TF-MxNE solution?
>
> hi Per,
>
>>     Sorry for the delay on this question. I would like to report a goodness of fit between the evoked response (at the sensors) derived from my experimental data, and the evoked field (at the sensors) as modeled by the tf-mxne solution. I often see this associated with dipole fits (on the mne_analyze dipole list?) and it is usually reported at "Goodness of Fit" as a percentage. Is this the Chi-Sq you mention, and do you know of a useful reference to it?
>
> maybe somebody else can point you to some refs when using dipole fits.
>
> for tf-mxne GOF makes sense on whitened data unless you have one
> sensor type (eg. gradiometers). I am not even sure how neuromag graph
> reports GOF for combined sensors.
> Any hint from somebody?
>
> so option one is to report GOF or R2 coef of determination on let's
> say only gradiometers.
> or compute these metrics on whitened data. I'd also recommend you show
> the butterfly
> plots of explained data. It is a nice way to visually demonstrate that
> your sources
> explain the data correctly.
>
> HTH
> Alex
>
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