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Classical categorical regression models such as the multinomial logit and proportional odds models are shown to be readily handled by the vector generalized linear and additive model (VGLM/VGAM) framework. Additionally, there are natural extensions, such as reduced-rank VGLMs for dimension reduction, and allowing covariates that have values specific to each(More)
In order to obtain adequate signal to noise ratio (SNR), stimulus-evoked brain signals are averaged over a large number of trials. However, in certain applications, e.g. fetal magnetoencephalography (MEG), this approach fails due to underlying conditions (inherently small signals, non-stationary/poorly characterized signals, or limited number of trials).(More)
Flash-evoked responses can be recorded from the fetus in utero. However, a standard analysis approach based on orthogonal projection (OP) to attenuate maternal and fetal cardiac signals leads to a spatial redistribution of the signal. This effect prevents the correlation of source location with a known fetal head location in some cases and the(More)
It is well known that using individual covariate information (such as body weight or gender) to model heterogeneity in capture–recapture (CR) experiments can greatly enhance inferences on the size of a closed population. Since individual covariates are only observable for captured individuals, complex conditional likelihood methods are usually required and(More)