Sentence examples for moving error from inspiring English sources
These objectives are hydromechanical performance, aesthetic performance, kinetic performance, toughness, other performance, fairing, machinability, machining efficiency, surface quality, load of tools, processing cost, processing deformation, collision and interference, machining error, geometric moving error, program calculation error and calculation principal error.
As they moved, errors could occur.
One-factor ANOVA was performed with adjustment of error variances for individual genes so that it did not fall below the moving average error variance for genes with similar intensity, and with FDR method for assessing statistical significance [ 81].
In particular, classes of moving average error processes are studied.
It is demonstrated that improving manufacturing and assembly techniques can greatly reduce the moving platform error.
These results thus generalize some of the results of Robinson to heteroscedastic regression models with long memory moving average errors.
Koul and Surgailis [14] established the asymptotic normality of the Whittle estimator in linear regression models with non-Gaussian long memory moving average errors.
This paper discusses the estimation of regression and variance functions in nonparametric heteroscedastic regression models with long memory moving average errors and uniform nonrandom design on the unit interval.
An application of these results to linear regression models with moving average errors of the above type yields that a large class of M-estimators of regression parameters are asymptotically equivalent to the least-squares estimator and α-stable.
This paper discusses the asymptotic behavior of Koul's minimum distance estimators of the regression parameter vector in linear regression models with long memory moving average errors, when the design variables are known constants.
The semi-parametric method corrects the estimator for both autoregressive and moving average errors, and this implies that it is possible to determine the significance of these parameters via conventional inference as long as the regressors are I(1) except for series that are truly exogenous.
