Schutter, "Comment on "A new method for the nonlinear transformation of means and covariances
in filters and estimators" (with authors' reply)," IEEE Transactions on Automatic Control, vol.
The UKF is a deterministic filter where a series of sigma points are selected according to the certain criteria and the a posteriori mean and covariance
are approximated using nonlinear propagation of these sigma points .
can be conveniently computed in terms of the inverse covariance
of the whole set of variables [mathematical expression not reproducible] (see Appendix C).
The unscented transformations (5) and (6) are more accurate than the linearization method for propagating means and covariances
of nonlinear functions, which is summarized in the following proposition.
Given their influence on further refinement of the STCS, it is important to note that these respecified models included 6 error covariances
and one cross-loading, which is not surprising given the total number of items comprising this assessment scale.
To obtain the multivariate normal samples used in the calculations of the type I error rates of the LRT for the independence between two groups of variables under the null hypothesis, matrices with zero covariances
and real variances and means were used.
Direct and maternal variancesand covariances
and maternal phenotypic effects on pre-weaninggrowth of beef cattle.
Therefore, the correlated signals and the covariance
matrix which is calculated from experimental covariances
should be included in the adjustment.
Equation (5) shows the market risk premium as computed by ex-ante population parameters; the expected rates of return and the covariances
among the stochastic rate of returns.
matrix (14) is diagonal, thus it is assumed that the components of vector [X.sub.ij] are independent.
And this is of significant practical interest, since the occurrence of adaptive constraints applyed to functionally relevant parameters is often difficult to detect and identify directly, while the patterns of covariances
between growth-based parameters are far more easily recorded.
The Regulation of the Ranges of Variation of Functionally Relevant Parameters via Appropriate Covariances
between the Growth-Based Parameters.
Then, the covariance
matrices of normal and abnormal traffic are calculated.
This requires the modeling of a covariance
structure to capture and accommodate the variability of the longitudinal data.
It has assumed that the distributions of the cyclic auto-correlation estimations under the null hypothesis and the alternative hypothesis have the same asymptotic covariance
and differ only in mean.