Sentence examples for mean functions and from inspiring English sources

The GP is then fully defined by its covariance and mean functions and their parameters.

We apply this result to the family of weighted power mean functions, and characterize the exponential convergence properties of the resulting algorithms.

The first one replaces all objective functions by their mean functions, and robust solution is defined as the efficient solution to the resulting deterministic optimization problem.

This model is characterised by mean functions and a parameter that models the correlation between repeated observations per subject (33 foods) and overdispersion (when the observed variance is higher that the variance of the theoretical model), which is common in count data.

This model has previously been used to capture patterns of skeletal morbidity during bone-targeted therapy[ 16, 19] All SREs at each respective site were included in the cumulative mean functions, and no event window was applied to the SREs because all SREs contribute to the overall burden of skeletal morbidity, even if they are related events.

In this model the conditional mean function and the conditional variance function are unknown curves.

In the stationary Gaussian case, a mean function and a covariance function fully specify the process.

A Gaussian process is completely specified by its mean function and a covariance function.

In order to introduce the generalized convexity, we first recall the definition of mean function and several classical means.

Spatial modeling is typically composed of a specification of a mean function and a model for the correlation structure.

Here each objective function is replaced by their mean function and an efficient solution of the resulting multi-objective optimization problem is called a robust solution.