4,120 research outputs found
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
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