Exponential smoothing technique is one of the most important quantitative techniques in forecasting. The accuracy of forecasting of this technique depends on exponential smoothing constant. Choosing an appropriate value of exponential smoothing constant is very crucial to minimize the error in forecasting. This paper addresses the selection of optimal value of exponential smoothing constant to ...

This paper is concerned with solving single CVaR and mixed CVaR minimization problems. A CHKS-type smoothing sample average approximation (SAA) method is proposed for solving these two problems, which retains the convexity and smoothness of the original problem and is easy to implement. For any fixed smoothing constant 2, this method produces a sequence whose cluster points are weak stationary ...

Managers engage in income smoothing either to communicate private information about future earnings to investors (informativeness hypothesis) or to distort financial performance for opportunistic purposes (opportunism hypothesis). Business cycles and the monitoring role of institutional ownership may affect the earnings informativeness of income smoothing. The purpose of this research is to exa...

Penalized spline criteria involve the function of goodness of fit and penalty, which in the penalty function contains smoothing parameters. It serves to control the smoothness of the curve that works simultaneously with point knots and spline degree. The regression function with two predictors in the non-parametric model will have two different non-parametric regression functions. Therefore, we...

Kneser-Ney (1995) smoothing and its variants are generally recognized as having the best perplexity of any known method for estimating N-gram language models. Kneser-Ney smoothing, however, requires nonstandard N-gram counts for the lowerorder models used to smooth the highestorder model. For some applications, this makes Kneser-Ney smoothing inappropriate or inconvenient. In this paper, we int...

This paper has a focus on non-stationary time series formed from small non-negative integer values which may contain many zeros and may be over-dispersed. It describes a study undertaken to compare various suitable adaptations of the simple exponential smoothing method of forecasting on a database of demand series for slow moving car parts. The methods considered include simple exponential smoo...

We present an effective and easy-to-implement angle-based smoothing scheme for triangular, quadrilateral and tri-quad mixed meshes. For each mesh node our algorithm compares all the pairs of adjacent angles incident to the node and adjusts these angles so that they become equal in the case of a triangular mesh and a quadrilateral mesh, or they form the ideal ratio in the case of a tri-quad mixe...

We present a residual smoothing algorithm for the complex symmetric conjugate gradients method. As in the real case, the residual smoothing method reproduces the (quasi-minimising) QMR method, and is considerably simpler to compute.

BACKGROUND CT perfusion images have a high contrast ratio between voxels representing different anatomy, such as tissue or vessels, which makes image segmentation of tissue and vascular regions relatively easy. However, grey and white matter tissue regions have relatively low values and can suffer from poor signal to noise ratios. While smoothing can improve the image quality of the tissue regi...