Sentence examples for assumptions of error from inspiring English sources

Toward this end, we resort to the renewal theory [24], which was first introduced in [32] to analyze the throughput performance of a HARQ system, under the assumptions of error- and delay-free feedback channel and infinite-length buffer.

Assumptions of error normality, variance homogeneity and temporal independence were confirmed for the models presented in Table 1 and Equations (1) and (2).

In the case of MEMS IMUs, linearization becomes a source of errors as these errors are nonlinear and highly correlated which violate the KF stationary and whitening assumptions of errors.

Heterogeneity and similarity problems are directly related to the assumption of error terms in model.

IIA property is generated from IID assumption of error term (The error term satisfies independent and identical type I extreme value distribution).

This complexity of adequately quantifying uncertainty is the result of the number of equations involved, the various sources of uncertainty (e.g. measurement vs. model error), and the questionable assumption of error independence among the equations.

Furthermore, while ordinary least squares (OLS) regressions are based on the hypothesis that financial access variables and error terms are normally distributed, such an assumption of error terms that are normally distributed does not hold with quantile regressions.

However, it may be expected that the PROC GLM procedure still produces valid results when the assumption of error normality is mildly violated [ 15].

Under the normality assumption of errors, the least-squares estimates equal the maximum likelihood estimates.

The asymptotic distribution of these tests has only been studied under the restrictive assumption of errors with known scale or symmetric distribution.

A generalized likelihood ratio is derived as a quantitative validation metric based on Bayes' theorem and Gaussian distribution assumption of errors of the wavelet packet component energy between validation data and model prediction.