The dual response surface methodology is a widely used technique in industrial engineering for simultaneously optimizing both the process mean and standard deviation functions of variables. Many optimization techniques have been proposed to optimize two fitted that include penalty function method (PM). PM has shown be more efficient than some existing methods. However, drawback it does not spec...

In most clinical and experimental studies, the standard deviation (SD) and the estimated standard error of the mean (SEM) are used to present the characteristics of sample data and to explain statistical analysis results. However, some authors occasionally muddle the distinctive usage between the SD and SEM in medical literature. Because the process of calculating the SD and SEM includes differ...

BACKGROUND In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard...

A variance reduction scheme is presented for nonparametric transfer function estimators based on the use of wavelets as an alternative to the traditional spectral windowing. The latter can be generalized into a variance reduction method based on thresholding (omitting or altering) the coefficients of an orthogonal series expansion of the estimator to be smoothed. Crucial is the choice of thresh...

Twenty ten-minute oral presentations made by Swedish students speaking English have been analyzed with respect to the standard deviation of F0 over long stretches of speech. Values have been normalized by division with the mean. Results show a strong correlation between proficiency in English and pitch variation for male speakers but not for females. The results also identify monotone and disfl...

Assume that we observe a small set of entries or linear combinations of entries of an unknown matrix A0 corrupted by noise. We propose a new method for estimating A0 which does not rely on the knowledge or an estimation of the standard deviation of the noise σ. Our estimator achieves, up to a logarithmic factor, optimal rates of convergence under the Frobenius risk and, thus, has the same predi...

Accuracy of measurements is defined as the sum of precision (standard deviation) and bias. Unfortunately, this definition is of little use unless bias is independently assessed. In this article, we extend this classical definition of accuracy of measurements to one of estimators obtained through data reconciliation techniques. Connection to gross error robustness measures, defined earlier by th...