Journeys Of A Lifetime: CILA Memories

St. Petersburgl998 was my first overseas trip ever! And I wouldn\u27t have missed it! My husband and I were based at St. Petersburg Christian University, where my work involved cataloging and helping with other assorted library matters. Our original four-month stint evolved into a seven-month stay

Spectroscopy in the 10 keV to 10 MeV range

Spectral lines in the 10 keV to 1 MeV range carry information of fundamental importance on many astronomical objects. Since the lines are directly related to specific physical processes this information is model independent and gives the physical conditions in the objects. At the sensitivities achieved to date, approximately 0.0001 to 0.001 phsq cm. sec for steady sources and approximately 0.01 to 1 ph/sq cm sec for transient sources, lines were detected from the galactic center, gamma-ray bursts and transients, X-ray pulsators, the Crab pulsar and solar flares. Future instruments with a factor of approximately 100 sensitivity improvement will allow detailed spectroscopic study of these classes of objects as well as supernova remnants, active galaxies and the interstellar medium. This sensitivity improvement can be obtained through the use of detector technology already proven in balloon and satellite instruments

Pruning and Nonparametric Multiple Change Point Detection

Change point analysis is a statistical tool to identify homogeneity within time series data. We propose a pruning approach for approximate nonparametric estimation of multiple change points. This general purpose change point detection procedure `cp3o' applies a pruning routine within a dynamic program to greatly reduce the search space and computational costs. Existing goodness-of-fit change point objectives can immediately be utilized within the framework. We further propose novel change point algorithms by applying cp3o to two popular nonparametric goodness of fit measures: `e-cp3o' uses E-statistics, and `ks-cp3o' uses Kolmogorov-Smirnov statistics. Simulation studies highlight the performance of these algorithms in comparison with parametric and other nonparametric change point methods. Finally, we illustrate these approaches with climatological and financial applications.Comment: 9 pages. arXiv admin note: text overlap with arXiv:1505.0430

ecp: An R Package for Nonparametric Multiple Change Point Analysis of Multivariate Data

There are many different ways in which change point analysis can be performed, from purely parametric methods to those that are distribution free. The ecp package is designed to perform multiple change point analysis while making as few assumptions as possible. While many other change point methods are applicable only for univariate data, this R package is suitable for both univariate and multivariate observations. Estimation can be based upon either a hierarchical divisive or agglomerative algorithm. Divisive estimation sequentially identifies change points via a bisection algorithm. The agglomerative algorithm estimates change point locations by determining an optimal segmentation. Both approaches are able to detect any type of distributional change within the data. This provides an advantage over many existing change point algorithms which are only able to detect changes within the marginal distributions