Sentence examples for model of normality from inspiring English sources

Rather, the published literature has focussed on two topics in relation to visual surveillance: first, creating low-level vision techniques to detect and classify activities, generally on the basis of the statistics of trajectory information; second, detecting unusual, or inexplicable activity as defined in relation to some model of normality.

Residuals analysis assured that the assumptions of the model of normality, linearity, independence and homogeneity of the variances were respected.

We show how the correlations between vital signs, captured in a data fusion index based on a probabilistic model of normality [ 2], change during times of cardiorespiratory instability.

As phenotypic descriptions are often comparative statements with respect to a reference model, either a model of normality, a control group, another organism or similar, we can exploit these descriptions to record phenes that characterize deviations from such a reference model.

The results of the Kolmogorov-Smirnov and Shapiro Wilks tests (KStest = 0.095, df =164, p <.001; SWtest = 0.096, df = 164, p = 0.004) indicated that the study phenomenon did not fit a normal distribution, and therefore any norms should not be based on a model of normality.

He has described the Presidential race between Hillary Clinton and Donald Trump as a choice "between two helplessly gesticulating models of normality, one of which appeared to be delegitimatized, the other unproven," and is unsurprised that so many people preferred the latter.

This paper presents a recurrent neural network based novelty filter where a Scitos G5 mobile robot explored the environment and built dynamic models of observed sensory motor values, then the acquired models of normality are used to predict the expected future values of sensory motor inputs during patrol.

As expected, the distribution of U-Hg was log-normal; we tested model assumptions of normality, equal variance, and the linearity of continuous exposures using residual diagnostics.

The mixed model assumption of normality of residual and BLUPs was checked after model fitting by quantile-quantile plot comparing the distribution of residual and random effect predictors to a theoretical normal distribution (Additional file 2).

The linear regression model assumptions of normality, linearity and homoscedasticity were assessed using residual plots.

All leaf and climate traits except 'Margin untoothed' (see below) were log10-transformed prior to analysis in order to meet model assumptions of normality.