The competence of the model was computed by employing ANOVA.
AICc score, a corrected value of AIC for small sample size, and Akaike weight for each model was computed to determine the best model for dose prediction.
The deformation of the mirror surface was calculated using the Finite Element method and a mathematical model was computed using the Multiple Model approach.
An ANOVA model was computed for group, stimulus domain and perceptibility, including the perceptible and imperceptible stimuli for the object features, scenes and weather/astral phenomena (Figs. 2a and 5e; comparing dark red and dark blue three left-most columns in Fig. 1a).
(The most superior part of cortex was not covered in the two 953b subjects.) Using SPM99, a general linear model was computed at each voxel with variables coding for diagnosis (mood fluctuations vs motor fluctuations only), drug status (baseline vs on-levodopa), and individual (a Boolean variable for each subject).
At last, a linear regression model was computed.
The adjusted model was computed over all oceanic areas and retained for our WDMAM candidate in oceanic regions lacking data.
Three reference points were selected, and the point-to-point distance between each point on the intraoral scan and the corresponding laser-scanned model was computed.
Since the parent model was computed for the epoch 2014.3, we advanced the main field coefficients to 2015.0 using the linear secular variation.
A starting low-frequency acoustic impedance model was computed from P-wave impedance log utilizing geological constraints after picking major horizons on the stacked section.
Finally this type of score with respect to every model was computed and the origin of the sound sample was identified by selecting the model with the maximum log-likelihood.
