Most non-normal response variables are not linear with respect to model parameters and, unlike normal responses, the variance of the phenotypes is dependent on the mean.
To assess the relative explanatory value of the fixed effects and random intercepts, we evaluated the total variance of the observed response, logAGR, the variance of the random slopes and the residual variance (Table 2).
The experiments on a spark ignition gasoline engine at various operating conditions show that the hypothesis test based controller is able to regulate LPP close to set point while maintaining the rapid transient response, and the variance of LPP is also well constrained.
The average response waveform was scaled to the peak of individual responses, and the variance of the fluctuation of the decays around the mean was calculated.
For γ R and γ B such that the adapted receptor activity is in the steep region of dose-response curves, the variance of transmitted noise is largest.
While the mean light levels and mean light derivatives were matched for the white-noise and step-response experiments, the variance of the signals was much greater for the white-noise experiments.
Does the distribution of this item's responses have enough variance (if the vast majority of respondents use the same response category then the variance of the responses is low and so is its covariance, correlation and homogeneity assessment against other items)?
The large eigenvalue corresponds to the fact that two nearly opposing pathways contribute to the response, which makes the variance of the spike-triggered stimulus ensemble along this direction particularly large.
Closed-form time-dependent response statistics such as (i) the variance of displacement response and variance of velocity response, (ii) the covariance of displacement and velocity responses, and (iii) covariances of displacement responses and velocity responses of structures, discretized by the finite element method, subjected to a wide class of non-stationary random excitations are presented.
The present contribution quantifies the relative importance of climate modeling factors and chosen response variables upon controlling the variance of streamflow forecasted with global climate model (GCM) projections, which has not been attempted in previous literature to our knowledge.
