Sentence examples for models the variance from inspiring English sources

In both models the variance of the irregular component σ w 2 is different from zero.

Since the textural random variable models the variance of the signal rather than its amplitude, it is introduced as a square root term in the data vector (described in [8]).

Unlike the first-order difference models, the variance and auto-covariance equations here are fully derivable, making the second-order difference models more convenient than the first-order difference models.

Under such models, the variance of Y consists of two additive components, one representing the variance part due to the variability of θ and one due to the inherent variability of Y if θ did not vary, i.e., V(Y) = V(E(Y|θ)) + E(V(Y|θ)).

In all three variance models the variance parameters σ ^ ⋅ 2 are estimated by maximum likelihood.

In all models the Variance Inflation Factor was < 5, indicating the absence of multicolinearity.

Under this approach repeatability is quantified by a specific parameter in the model; the variance of the random effect.

For example, instead of modeling the intensity of a Poisson, we could assume conditionally Gaussian observations and model the variance.

In particular, we modeled the variance for the above three mean equations using GARCH, APARCH, EGARCH, TGARCH, and IGARCH models.

However, a notable limit is that it does not model the variance associated to a BG value.

For this simplest SAD(1) model, the variance and correlation functions are non-stationary.