Sentence examples for unconditional error from inspiring English sources

The unconditional error probability is obtained by averaging over all the conditional error probabilities corresponding to the channel realizations.

For a proposed RM coded-cooperative scheme, the unconditional error probability is as follows: begin{array}{l}{P}_b(E =frac{1}{pi }{displaystyle underset{0}{overset{pi /2}{int }}}{left(1+frac{{overline{gamma}}_{SD}}{2{ sin}^2phi}right)}^{-{w}_1}{overline{gamma}erline{gamma}}_{RD}}{2{ sin}^2phi}right)}^{-{w}_2}dphi end{array} (18).

To calculate the final bit error performance in the Monte Carlo simulations, a minimum of 400 errors were taken into account for each point; for the method presented in this paper, 5,000 independent channel realizations were used to obtain the unconditional error probability.

In [18], based on a splitting of the error into two parts: the error from the time discretization of the PDEs and the error from the finite element approximation of corresponding iterated time-discrete PDEs, the authors carried on unconditional error estimates for time-dependent viscoelastic fluid flow.

At first, we consider a non-cooperative scheme, and using the techniques outlined in the available literature [10,36], the unconditional error probability is as follows: {P}_b(E =frac{1}{pi }{displaystyle underset{0}{overset{pi /2}{int }}}{left(1+frac{{overline{gamma}}_{SD}}{{ sin}^2phi}right)}^{-mathrm{wt}left left|mathbf{u}Big|mathbf{u}+mathbf{v}right|right)}dphi (17).

Interestingly, none of the studies cited above explicitly addressed the unconditional error rates of the two-stage procedure as a whole.

Likelihoods and conditional and unconditional prediction error rates are used as complementary measures of the quality of each of the proposed chord representations.

The package 'AICcmodavg' (Mazerolle, 2013) was used to estimate model-averaged fixed effects, unconditional standard errors, and 95% CIs.

We calculated the mean of the predictor estimators, their unconditional standard errors (SE) and confidence intervals (CIs), and the relative importance of each variable in the final averaged model (Σ ωi, the sum of Akaike weights of models with ΔAICc ≤ 2 in which the variable was included).

Table 3 outlines the estimated unconditional Type I error rates.

The inference is considered with respect to minimising both the conditional and unconditional mean-square error (MSE).