Sentence examples for optimal variance of from inspiring English sources

The results are used to derive the optimal variance of the best linear estimator in the continuous time model and to construct efficient estimators and corresponding optimal designs for finite samples.

This is a three-dimensional mean-variance frontier as the optimal variance now depends on the choice of both a deterministic drift m and a random drift d.

Local estimates [ 14- 16] of the mean-variance relationship are likely best, but further research is needed to understand the optimal variance estimation strategy.

The authors in [2] exploited the relationship between linear diffusion and Gaussian scale space to estimate optimal variances and window size of the Gaussian.

A trajectory of (33) is simulated and a KF is used to compute the optimal variances P k|k.

Our data shows that even though under optimal conditions the variance of real-time QPCR is considerable across large sample numbers, however it still may have a place as purely a confirmatory assay for sequencing projects or MLPA and PRT data sets.

In loop design, using the optimal weighting, the variance of the contrast between adjacent treatments is σ i ε 2 + σ i a 2 σ i ε 2 / 2 (σ i a 2 + σ i ε 2 ) while the variance of the contrast between diagonally opposite treatments is σ i ε 2 + σ i a 2 σ i ε 2 / (σ i a 2 + σ i ε 2 ).

We chose the optimal tradeoff between bias and variance of the smooth (the optimal span size) by minimizing the AIC.

Given the noisy MP coefficients α k ( m ) at the m th frame, the optimal estimate of the variance of the noise MP coefficients λ n, k ( m ) under MMSE is given by λ ^ n, k ( m ) = E ( λ n, k ( m ) | α k ( m ) ) = E ( λ n, k ( m ) | H 0 ) P ( H 0 | α k ( m ) ) + E ( λ n, k ( m ) | H 1 ) P ( H 1 | α k ( m ) ) (17).

Thus, the data structure that is optimal for estimating the variance of IGEs that do not depend on kin renders the estimation of kin-dependent IGEs impossible.

Let us consider the D-optimal design, which maximizes the determinant of the FIM, and therefore minimizes the generalized variance of the optimal location estimate vector, x ̂ t [8].