924 resultados para Multivariate statistics


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Gulf of Mexico, white shrimp, Litopenaeus setiferus, catch statistics have been collected by NOAA’s National Marine Fisheries Service for over 50 years. Recent occurrences such as natural and manmade disasters have raised awareness for the need to publish these types of data. Here we report shrimp data collected from 1984 to 2011. These 28 years of catch history are the time series used in the most recent Gulf of Mexico white shrimp stock assessment. Fishing effort for this stock has fluctuated over the period reported, ranging from 54,675 to 162,952 days fished. Catch averaged 55.7 million pounds per year, increasing significantly over the times series. In addition, catch rates have been increasing in recent years, with CPUE levels ranging from 315 lb/day fished in 2002, to 1,175 lb/ day fished in 2008. The high CPUE’s we have measured is one indication that the stock was not in decline during this time period. Consequently, we believe the decline in effort levels is due purely to economic factors. Current stock assessments are now using these baseline data to provide managers with further insights into the Gulf L. setiferus stocks.

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Humans use their arms to engage in a wide variety of motor tasks during everyday life. However, little is known about the statistics of these natural arm movements. Studies of the sensory system have shown that the statistics of sensory inputs are key to determining sensory processing. We hypothesized that the statistics of natural everyday movements may, in a similar way, influence motor performance as measured in laboratory-based tasks. We developed a portable motion-tracking system that could be worn by subjects as they went about their daily routine outside of a laboratory setting. We found that the well-documented symmetry bias is reflected in the relative incidence of movements made during everyday tasks. Specifically, symmetric and antisymmetric movements are predominant at low frequencies, whereas only symmetric movements are predominant at high frequencies. Moreover, the statistics of natural movements, that is, their relative incidence, correlated with subjects' performance on a laboratory-based phase-tracking task. These results provide a link between natural movement statistics and motor performance and confirm that the symmetry bias documented in laboratory studies is a natural feature of human movement.

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The band-by-band vicarious calibration of on-orbit satellite ocean color instruments, such as SeaWiFS and MODIS, using ground-based measurements has significant residual uncertainties. This paper applies spectral shape and population statistics to tune the calibration of the blue bands against each other to allow examination of the interband calibration and potentially provide an analysis of calibration trends. This adjustment does not require simultaneous matches of ground and satellite observations. The method demonstrates the spectral stability of the SeaWiFS calibration and identifies a drift in the MODIS instrument onboard Aqua that falls within its current calibration uncertainties.

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Comparison between past changes in pollen assemblages and stable isotope ratios (deuterium and carbon) analyzed in the same peat core from Tierra del Fuego at latitude 55°S permitted identification of the relative contribution of precipitation versus temperature responsible for the respective change. Major steps in the sequence of paleoenvironmental changes, such as at 12700, 9000, 5000, and 4000 years ago are apparently related only to increase in precipitation, reflecting the latitudinal location and intensity of the westerly storm tracks. On the other hand, high paleoenvironmental variability, which is characteristic for the late-glacial and the latest Holocene, is related to temperature variability, which affects the relative moisture content. Comparison with other paleoenvironmental records suggests that the late-glacial temperature variability is probably related to variability in the extent of Antarctic sea-ice, which in turn appears to be related to the intensity of Atlantic deep-water circulation. Temperature variability during the latest Holocene, on the other hand, is probably related to the dynamics of the El Niño/Southern Oscillation.

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The personal computer has become commonplace on the desk of most scientists. As hardware costs have plummeted, software capabilities have expanded enormously, permitting the scientist to examine extremely large datasets in novel ways. Advances in networking now permit rapid transfer of large datasets, which can often be used unchanged from one machine to the next. In spite of these significant advances, many scientists still use their personal computers only for word processing or e-mail, or as "dumb terminals". Many are simply unaware of the richness of software now available to statistically analyze and display scientific data in highly innovative ways. This paper presents several examples drawn from actual climate data analysis that illustrate some novel and practical features of several widely-used software packages for Macintosh computers.

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A study of planktonic foraminiferal assemblages from 19 stations in the neritic and oceanic regions off the Coromandel Coast, Bay of Bengal has been made using a multivariate statistical method termed as factor analysis. On the basis of abundance, 17 foraminiferal species, species were clustered into 5 groups with row normalisation and varimax rotation for Q-mode factor analysis. The 19 stations were also grouped into 5 groups with only 2 groups statistically significant using column normalisation and varimax rotation for R-mode analysis. This assemblage grouping method is suitable because groups of species/stations can explain the maximum amount of variation in them in relation to prevailing environmental conditions in the area of study.

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Given a spectral density matrix or, equivalently, a real autocovariance sequence, the author seeks to determine a finite-dimensional linear time-invariant system which, when driven by white noise, will produce an output whose spectral density is approximately PHI ( omega ), and an approximate spectral factor of PHI ( omega ). The author employs the Anderson-Faurre theory in his analysis.