The article[14] examined the error of estimating autocorrelation and the article[15] linked the variation with sampling rate and refined it in the form of mean-square error.
A real-world data performance analysis is provided to examine the error rates of the proposed models.
Using highly accurate locational data for both place of injury and place of residence, this analysis examines the error in using place of residence as a proxy for place of injury.
We first examine the angular error of normal maps recovered by different methods on both synthesized and real datasets.
Therefore, a laboratory experiment was designed to examine the measurement error of the proposed technique against direct manual measurements based on a simplified model of the rigging system in reduced scale.
Three simulations are conducted to examine the sampling errors of the maximum likelihood estimates (MLEs) and the type-I and type-II errors of the LRT.
To assess the variability of each IAA, we examined the standard error of the mean for each IAA measurement on a plant-based food in the USDA sr22 database.
The degree of nonlinearity in signal response was assessed by examining the standard error of the regression and selecting the higher-order (nonlinear) polynomial model with the best fit.
To assess the quality of the test under finite sample sizes, we examine the familywise error rate of the test under homoscedasticity as well as under heteroscedasticity for different error distributions in simulations and show that the familywise error rate is controlled.
In this paper, we examine the soft error vulnerabilities of shared data in parallel Java applications.
