Sentence examples for bias approximation from inspiring English sources

In this paper, we tend to use another way to derive the bias approximation of JPDA.

A simpler approximation, one-term expected value normalized bias approximation, ENBA(1), bias ≈ E Ŝ x ( f ) − S x ( f ) E Ŝ x ( f ), (15). is also suggested.

Similarly, as above, the bias approximation bias ≈ E Ŝ x ( f ) − S x ( f ) E Ŝ x ( f ) + + 1 2 E Ŝ x ( f ) − S x ( f ) E Ŝ x ( f ) 2 + ψ ( K ) − log ( K ) (14). is referred to as the two-term expected value normalized bias approximation, ENBA(2).

A simpler approximation is proposed for comparison, referred to as one-term true spectrum normalized bias approximation, TNBA(1), bias ≈ E Ŝ x ( f ) − S x ( f ) S x ( f ).

The two first terms in a more thorough approximation are used, referred to as two-term true spectrum normalized bias approximation, TNBA(2), bias ≈ E Ŝ x ( f ) − S x ( f ) S x ( f ) − 1 2 E Ŝ x ( f ) − S x ( f ) S x ( f ) 2 + + ψ ( K ) − log ( K ).

For binary x, the proposed bias approximation is 7The simulation of Lin et al.

The simulations based on the real study illustrate that the bias approximations work well in practice.

A thorough discussion and evaluation are also made for different bias approximations for the log-spectrum of multitaper estimators.

In Figure 2b,c, the error between the different bias approximations compared to the true bias of the log-spectrum in Equation 9 is shown.

More formally, given a set of ordered gene expression values g j for genes j = 1, 2,... m, let x ij denote expression bias approximations for genes j = 1, 2,... m using window spans i = 25, 26, 27,... m/3 where n denotes the number of window spans examined.

To the extent that K s  ≫ V r  / τ a, K s might directly serve as an (negatively biased) approximation of K m.