Robust correlators

Radio frequency interference (RFI) already limits the sensitivity of existing radio telescopes in several frequency bands and may prove to be an even greater obstacle for future generation instruments to overcome. I aim to create a structure of radio astronomy correlators which will be statistically stable (robust) in the presence of interference. A statistical analysis of the mixture of system noise + signal noise + RFI is proposed here which could be incorporated into the block diagram of a correlator. Order and rank statistics are especially useful when calculated in both temporal and frequency domains. Several new algorithms of robust correlators are proposed and investigated here. Computer simulations and processing of real data demonstrate the efficacy of the proposed algorithms

Methods and Algorithms for Robust Filtering

We discuss filtering procedures for robust extraction of a signal from noisy time series. Moving averages and running medians are standard methods for this, but they have shortcomings when large spikes (outliers) respectively trends occur. Modified trimmed means and linear median hybrid filters combine advantages of both approaches, but they do not completely overcome the difficulties. Improvements can be achieved by using robust regression methods, which work even in real time because of increased computational power and faster algorithms. Extending recent work we present filters for robust online signal extraction and discuss their merits for preserving trends, abrupt shifts and extremes and for the removal of spikes

Dynamic debt runs and financial fragility: Evidence from the 2007 ABCP crisis

We use the 2007 asset-backed commercial paper (ABCP) crisis as a laboratory to study the determinants of debt runs. Our model features dilution risk: maturing short-term lenders demand higher yields in compensation for being diluted by future lenders, making runs more likely. The model explains the observed tenfold increase in yield spreads leading to runs and the positive relation between yield spreads and future runs. Results from structural estimation show that runs are very sensitive to leverage, asset values, and asset liquidity, but less sensitive to the degree of maturity mismatch, the strength of guarantees, and asset volatility

Detection of inconsistencies in geospatial data with geostatistics

Almost every researcher has come through observations that “drift” from the rest of the sample, suggesting some inconsistency. The aim of this paper is to propose a new inconsistent data detection method for continuous geospatial data based in Geostatistics, independently from the generative cause (measuring and execution errors and inherent variability data). The choice of Geostatistics is based in its ideal characteristics, as avoiding systematic errors, for example. The importance of a new inconsistent detection method proposal is in the fact that some existing methods used in geospatial data consider theoretical assumptions hardly attended. Equally, the choice of the data set is related to the importance of the LiDAR technology (Light Detection and Ranging) in the production of Digital Elevation Models (DEM). Thus, with the new methodology it was possible to detect and map discrepant data. Comparing it to a much utilized detections method, BoxPlot, the importance and functionality of the new method was verified, since the BoxPlot did not detect any data classified as discrepant. The proposed method pointed that, in average, 1,2% of the data of possible regionalized inferior outliers and, in average, 1,4% of possible regionalized superior outliers, in relation to the set of data used in the study

Coupling planktonic and benthic shifts during a bloom of Alexandrium catenella in southern Chile:Implications for bloom dynamics and recurrence

Cell abundances and distributions of Alexandrium catenella resting cysts in recent sediments were studied along time at two locations in the Chilean Inland Sea exposed to different oceanographic conditions: Low Bay, which is much more open to the ocean than the more interior and protected Ovalada Island. The bloom began in interior areas but maximum cyst concentrations were recorded in locations more open to the ocean, at the end of the Moraleda channel. Our results showed a time lapse of around 3 months from the bloom peak (planktonic population) until the number of resting cysts in the sediments reached a maximum. Three months later, less than 10% of the A. catenella cysts remained in the sediments. Maximum cyst numbers in the water column occurred one month after the planktonic peak, when no cells were present. The dinoflagellate assemblage at both study sites was dominated by heterotrophic cysts, except during the A. catenella bloom. CCA analyses of species composition and environmental factors indicated that the frequency of A. catenella blooms was associated with low temperatures, but not with salinity, chlorophyll a concentration, and predator presence (measured as clam biomass). However, resting cyst distribution was only related to cell abundance and location. The occurrence of A. catenella cysts was also associated with that of cysts from the toxic species Protoceratium reticulatum. By shedding light on the ecological requirements of A. catenella blooms, our observations support the relevance of encystment as a mechanism of bloom termination and show a very fast depletion of cysts from the sediments (<3 months), which suggest a small role for resting cyst deposits in the recurrence of A. catenella blooms in this area.Postprin