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Observation Window (observation + window)

Distribution by Scientific Domains
Mathematics and Statistics40%

Selected Abstracts

Description of earthquake aftershock sequences using prototype point patterns

ENVIRONMETRICS, Issue 3 2008
Frederic Paik Schoenberg
Abstract We introduce the use of prototype point patterns to characterize the behavior of a typical aftershock sequence from the global Harvard earthquake catalog. These prototypes are used not only for data description and summary but also to identify outliers and to classify sequences into groups exhibiting similar aftershock behavior. We find that a typical shallow earthquake of magnitude between 7.5 and 8.0 has approximately five aftershocks of magnitude at least 5.5, and that within an observation window of 0.113 days to 2.0 years after the mainshock, these aftershocks are roughly evenly distributed in log-time. The relative magnitudes and distances from the mainshock for the typical aftershock sequence are characterized as well. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Habitat associations of Atlantic herring in the Shetland area: influence of spatial scale and geographic segmentation

FISHERIES OCEANOGRAPHY, Issue 3 2001
CHRISTOS D. Maravelias
This study considers the habitat associations of a pelagic species with a range of biotic and abiotic factors at three different spatial scales. Generalized additive models (GAM) are used to analyse trends in the distributional abundance of Atlantic herring (Clupea harengus) in relation to thermocline and water depth, seabed roughness and hardness, sea surface salinity and temperature, zooplankton abundance and spatial location. Two geographical segments of the population, those east and west of the Shetland Islands (northern North Sea, ICES Div IVa), are examined. The differences in the ecological preferences of the species in these two distinct geographical areas are elucidated and the degree that these environmental relationships might be modulated by the change of support of the data is also considered. Part of the observed variability of the pre-spawning distribution of herring was explained by different parameters in these two regions. Notwithstanding this, key determinants of the species' spatial aggregation in both areas were zooplankton abundance and the nature of the seabed substrate. The relative importance of the variables examined did not change significantly at different spatial scales of the observation window. The diverse significance of various environmental factors on herring distribution was attributed mainly to the interaction of species' dynamics with the different characteristics of the ecosystem, east and west of the Shetland Islands. Results suggest that the current 2.5 nautical miles as elementary sampling distance unit (ESDU) is a reasonable sampling scheme that combines the need to reduce the data volume while maintaining spatial resolution to distinguish the species/environment relationships. [source]

Cluster Pattern Detection in Spatial Data Based on Monte Carlo Inference

BIOMETRICAL JOURNAL, Issue 4 2007
Radu Stefan Stoica
Abstract Clusters in a data point field exhibit spatially specified regions in the observation window. The method proposed in this paper addresses the cluster detection problem from the perspective of detection of these spatial regions. These regions are supposed to be formed of overlapping random disks driven by a marked point process. The distribution of such a process has two components. The first is related to the location of the disks in the field of observation and is defined as an inhomogeneous Poisson process. The second one is related to the interaction between disks and is constructed by the superposition of an area-interaction and a pairwise interaction processes. The model is applied on spatial data coming from animal epidemiology. The proposed method tackles several aspects related to cluster pattern detection: heterogeneity of data, smoothing effects, statistical descriptors, probability of cluster presence, testing for the cluster presence. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]

Stimulation, Monitoring, and Analysis of Pathway Dynamics by Metabolic Profiling in the Aromatic Amino Acid Pathway

BIOTECHNOLOGY PROGRESS, Issue 6 2004
M. Oldiges
Using a concerted approach of biochemical standard preparation, analytical access via LC-MS/MS, glucose pulse, metabolic profiling, and statistical data analysis, the metabolism dynamics in the aromatic amino acid pathway has been stimulated, monitored, and analyzed in different tyrosine-auxotrophic l -phenylalanine-producing Escherichiacoli strains. During the observation window from ,4 s (before) up to 27 s after the glucose pulse, the dynamics of the first five enzymatic reactions in the aromatic amino acid pathway was observed by measuring intracellular concentrations of 3-deoxy- d -arabino-heptulosonate 7-phosphate DAH(P), 3-dehydroquinate (3-DHQ), 3-dehydroshikimate (3-DHS), shikimate 3-phosphate (S3P), and shikimate (SHI), together with the pathway precursors phosphoenolpyruvate (PEP) and P5P, the lumped pentose phosphate pool as an alternative to the nondetectable erythrose 4-phosphate (E4P). Provided that a sufficient fortification of the carbon flux into the pathway of interest is ensured, respective metabolism dynamics can be observed. On the basis of the intracellular pool measurements, the standardized pool velocities were calculated, and a simple, data-driven criterion-called "pool efflux capacity" (PEC)-is derived. Despite its simplifying system description, the criterion managed to identify the well-known AroB limitation in the E. coli strain A (genotype ,( pheA tyrA aroF)/pJF119EH aroFfbrpheAfbramp) and it also succeeded to identify AroL and AroA (in strain B, genotype ,( pheA tyrA aroF)/pJF119EH aroFfbrpheAfbraroB amp) as promising metabolic engineering targets to alleviate respective flux control in subsequent l -Phe producing strains. Furthermore, using of a simple correlation analysis, the reconstruction of the metabolite sequence of the observed pathway was enabled. The results underline the necessity to extend the focus of glucose pulse experiments by studying not only the central metabolism but also anabolic pathways. [source]

IMPROVING FORECAST ACCURACY BY COMBINING RECURSIVE AND ROLLING FORECASTS,

INTERNATIONAL ECONOMIC REVIEW, Issue 2 2009
Todd E. Clark
This article presents analytical, Monte Carlo, and empirical evidence on combining recursive and rolling forecasts when linear predictive models are subject to structural change. Using a characterization of the bias,variance trade-off faced when choosing between either the recursive and rolling schemes or a scalar convex combination of the two, we derive optimal observation windows and combining weights designed to minimize mean square forecast error. Monte Carlo experiments and several empirical examples indicate that combination can often provide improvements in forecast accuracy relative to forecasts made using the recursive scheme or the rolling scheme with a fixed window width. [source]