884 research outputs found
CVTresh: R Package for Level-Dependent Cross-Validation Thresholding
The core of the wavelet approach to nonparametric regression is thresholding of wavelet coefficients. This paper reviews a cross-validation method for the selection of the thresholding value in wavelet shrinkage of Oh, Kim, and Lee (2006), and introduces the R package CVThresh implementing details of the calculations for the procedures. This procedure is implemented by coupling a conventional cross-validation with a fast imputation method, so that it overcomes a limitation of data length, a power of 2. It can be easily applied to the classical leave-one-out cross-validation and K-fold cross-validation. Since the procedure is computationally fast, a level-dependent cross-validation can be developed for wavelet shrinkage of data with various sparseness according to levels.
A survey of measurement-based spectrum occupancy modeling for cognitive radios
Spectrum occupancy models are very useful in cognitive radio designs. They can be used to increase spectrum sensing accuracy for more reliable operation, to remove spectrum sensing for higher resource usage efficiency, or to select channels for better opportunistic access, among other applications. In this survey, various spectrum occupancy models from measurement campaigns taken around the world are investigated. These models extract different statistical properties of the spectrum occupancy from the measured data. In addition to these models, spectrum occupancy prediction is also discussed, where autoregressive and/or moving-average models are used to predict the channel status at future time instants. After comparing these different methods and models, several challenges are also summarized based on this survey
Moving sum procedure for change point detection under piecewise linearity
We propose a computationally and statistically efficient procedure for
segmenting univariate data under piecewise linearity. The proposed moving sum
(MOSUM) methodology detects multiple change points where the underlying signal
undergoes discontinuous jumps and/or slope changes. Theoretically, it controls
the family-wise error rate at a given significance level asymptotically and
achieves consistency in multiple change point detection, as well as matching
the minimax optimal rate of estimation when the signal is piecewise linear and
continuous, all under weak assumptions permitting serial dependence and
heavy-tailedness. Computationally, the complexity of the MOSUM procedure is
which, combined with its good performance on simulated datasets, making
it highly attractive in comparison with the existing methods. We further
demonstrate its good performance on a real data example on rolling
element-bearing prognostics
Moving sum procedure for change point detection under piecewise linearity
We propose a computationally and statistically efficient procedure for
segmenting univariate data under piecewise linearity. The proposed moving sum
(MOSUM) methodology detects multiple change points where the underlying signal
undergoes discontinuous jumps and/or slope changes. Theoretically, it controls
the family-wise error rate at a given significance level asymptotically and
achieves consistency in multiple change point detection, as well as matching
the minimax optimal rate of estimation when the signal is piecewise linear and
continuous, all under weak assumptions permitting serial dependence and
heavy-tailedness. Computationally, the complexity of the MOSUM procedure is
which, combined with its good performance on simulated datasets, making
it highly attractive in comparison with the existing methods. We further
demonstrate its good performance on a real data example on rolling
element-bearing prognostics
Robust coherence analysis for long-memory processes
This paper investigates the linear relationships between two time-series in the frequency domain, termed coherence analysis. It is widely used in various fields, including signal processing, engineering, and meteorology. However, conventional coherence analysis tends to be sensitive to outliers. Laplace cross-periodogram and a corresponding robust coherence analysis based on the least-absolute deviation (LAD) regression have recently been developed to improve this shortcoming. In this paper, to extend the scope of Laplace cross-periodogram, we study a robust cross periodogram for long-memory processes and derive its asymptotic distribution. Through numerical studies, we demonstrate the usefulness of the proposed robust coherence analysis for long-memory processes.N
Upper Gastrointestinal Tract Foreign Bodies
Foreign body ingestion, a common emergency encountered in clinical practice, is a potentially serious condition. Most foreign bodies in the gastrointestinal tract pass spontaneously. However, objects that are relatively long or large may lodge in the upper gastrointestinal tract, potentially causing perforation, bleeding, and obstruction. This literature review summarizes the natural history and clinical aspects of these types of foreign bodies in adults as well as the various methods for their removal. Endoscopic removal is a relatively safe and effective procedure for removing these types of foreign bodies. The development of endoscopic techniques and devices has resulted in their widespread use, with good results, as the primary treatment
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