Fast Ensemble Smoothing

Smoothing is essential to many oceanographic, meteorological and hydrological applications. The interval smoothing problem updates all desired states within a time interval using all available observations. The fixed-lag smoothing problem updates only a fixed number of states prior to the observation at current time. The fixed-lag smoothing problem is, in general, thought to be computationally faster than a fixed-interval smoother, and can be an appropriate approximation for long interval-smoothing problems. In this paper, we use an ensemble-based approach to fixed-interval and fixed-lag smoothing, and synthesize two algorithms. The first algorithm produces a linear time solution to the interval smoothing problem with a fixed factor, and the second one produces a fixed-lag solution that is independent of the lag length. Identical-twin experiments conducted with the Lorenz-95 model show that for lag lengths approximately equal to the error doubling time, or for long intervals the proposed methods can provide significant computational savings. These results suggest that ensemble methods yield both fixed-interval and fixed-lag smoothing solutions that cost little additional effort over filtering and model propagation, in the sense that in practical ensemble application the additional increment is a small fraction of either filtering or model propagation costs. We also show that fixed-interval smoothing can perform as fast as fixed-lag smoothing and may be advantageous when memory is not an issue

Pengaruh Rasio Profitabilitas, Ukuran Perusahaan, Nilai Perusahaan, Dan Financial Leverage Terhadap Praktek Perataan Laba

This study aimed to examine the effect of profitability ratios, firm size, firm value and financial leverage on income smoothing practices. Income smoothing is one pattern of earnings management. This study aims to analyze the factors that influence the practice of income smoothing using a sample of 76 companies listed on the Stock Exchange within a period of three years from 2009 to 2011 with the selection method of purposive sampling. This study uses Eckel index to classify a company that does or does not practice income smoothing. The statistical analysis used in this study was to test the descriptive statistics and multivariate logistic regression through testing with SPSS ver. 17.0. The results show that the first hypothesis (H1) which states that affect the profitability of the practice of income smoothing, rejected. The second hypothesis (H2) which states that the size of the company influence the practice of income smoothing, rejected. The third hypothesis (H3) which states that the value of the company influence the practice of income smoothing, rejected. The fourth hypothesis (H4) stating financial leverage effect on the practice of income smoothing, rejected

Probability smoothing

Contains fulltext : 227633.pdf (publisher's version ) (Open Access

The Modified Direct Method: an Approach for Smoothing Planar and Surface Meshes

The Modified Direct Method (MDM) is an iterative mesh smoothing method for smoothing planar and surface meshes, which is developed from the non-iterative smoothing method originated by Balendran [1]. When smooth planar meshes, the performance of the MDM is effectively identical to that of Laplacian smoothing, for triangular and quadrilateral meshes; however, the MDM outperforms Laplacian smoothing for tri-quad meshes. When smooth surface meshes, for trian-gular, quadrilateral and quad-dominant mixed meshes, the mean quality(MQ) of all mesh elements always increases and the mean square error (MSE) decreases during smoothing; For tri-dominant mixed mesh, the quality of triangles always descends while that of quads ascends. Test examples show that the MDM is convergent for both planar and surface triangular, quadrilateral and tri-quad meshes.Comment: 18 page