SiZer for time series: A new approach to the analysis of trends

Smoothing methods and SiZer are a useful statistical tool for discovering statistically significant structure in data. Based on scale space ideas originally developed in the computer vision literature, SiZer (SIgnificant ZERo crossing of the derivatives) is a graphical device to assess which observed features are `really there' and which are just spurious sampling artifacts. In this paper, we develop SiZer like ideas in time series analysis to address the important issue of significance of trends. This is not a straightforward extension, since one data set does not contain the information needed to distinguish `trend' from `dependence'. A new visualization is proposed, which shows the statistician the range of trade-offs that are available. Simulation and real data results illustrate the effectiveness of the method.Comment: Published at http://dx.doi.org/10.1214/07-EJS006 in the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org

Third Interger Resonance Slow Extraction Using RFKO at High Space Charge

A proposal to search for direct {\mu}-->e conversion at Fermilab requires slow, resonant extraction of an intense proton beam. Large space charge forces will present challenges, partly due to the substantial betatron tune spread. The main challenges will be maintaining a uniform spill profile and moderate losses at the septum. We propose to use "radio frequency knockout" (RFKO) for fine tuning the extraction. Strategies for the use of the RFKO method will be discussed here in the context of the Mu2e experiment. The feasibility of this method has been demonstrated in simulations.Comment: 3 pp. 2nd International Particle Accelerator Conference: IPAC 2011. 4-9 Sep 2011. San Sebastian, Spai