A simple shift algorithm is described enabling the exact determination of power functions and sample size distributions for a large variety of closed sequential two-sample designs with a binary outcome variable. The t...
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A simple shift algorithm is described enabling the exact determination of power functions and sample size distributions for a large variety of closed sequential two-sample designs with a binary outcome variable. The test statistics are assumed to be based on relative frequencies of successes or failures, but the number of interim analyses, the monitoring times, and the continuation regions may be specified as desired. To give examples, exact properties of designs proposed by the program package EaSt (CYTEL. 1992) are determined, and plans with interim analyses are considered where decisions are based on the conditional power given the observations obtained so far.
In this article an algorithm is presented to compute the exact permutation distribution of the nonparametric Friedman test for the two-way layout with possible stochastic dependencies within rows. Apart from regular c...
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In this article an algorithm is presented to compute the exact permutation distribution of the nonparametric Friedman test for the two-way layout with possible stochastic dependencies within rows. Apart from regular convolution methods this algorithm uses the rich algebraic structure of the full permutation group. This leads to a substantial reduction of the computational workload. The algorithm makes use of some mathematical operators on k-dimentional arrays which all are available in the computer language APL (take, transpose and ravel). However, these operators are explained in detail in this article to facilitate understanding without knowledge of APL. APL programs are provided. (C) 1997 Elsevier Science B.V.
The construction of simple classification rules is a frequent problem in medical research. Maximally selected rank statistics allow the evaluation of cutpoints, which provide the classification of observations into tw...
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The construction of simple classification rules is a frequent problem in medical research. Maximally selected rank statistics allow the evaluation of cutpoints, which provide the classification of observations into two groups by a continuous or ordinal predictor variable. The computation of the exact distribution of a maximally selected rank statistic is discussed and a new lower bound of the distribution is derived based on an extension of an algorithm for the exact distribution of a linear rank statistic. Therefore, the test based on the upper bound of the P-value is of level alpha. For small to moderate sample sizes the lower bound of the exact distribution is a substantial improvement compared to approximations based on an improved Bonferroni inequality or based on the asymptotic Gaussian process. The lower bound of the distribution is compared to the exact distribution by means of a simulation study and the proposal is illustrated by three clinical studies. (C) 2003 Elsevier Science B.V. All rights reserved.
An exact rank test for two dependent samples based on overall mid-ranks is discussed which can be applied to metric as well as to ordinal data. The exact conditional distribution of the test statistic given the observ...
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An exact rank test for two dependent samples based on overall mid-ranks is discussed which can be applied to metric as well as to ordinal data. The exact conditional distribution of the test statistic given the observed vector of rank differences is determined. A recursion formula is given as well as a fast shift algorithm in SAS/IML code. Moreover, it is demonstrated that the paired rank test can be more powerful than other tests for paired samples by means of a simulation study. Finally, the test is applied to a psychiatric trial with longitudinal ordinal data.
Traditional geometry-based approach can maintain the characteristics of vector data. However, complex interpolation calculations limit its applications in high resolution and multi-source spatial data integration at s...
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ISBN:
(纸本)9781629935201
Traditional geometry-based approach can maintain the characteristics of vector data. However, complex interpolation calculations limit its applications in high resolution and multi-source spatial data integration at spherical scale in digital earth systems. To overcome this deficiency, an adaptive integration model of vector polyline and spherical DEM is presented. Firstly, Degenerate Quadtree Grid (DQG) which is one of the partition models for global discrete grids, is selected as a basic framework for the adaptive integration model. Secondly, a novel shift algorithm is put forward based on DQG proximity search. The main idea of shift algorithm is that the vector node in a DQG cell moves to the cell corner-point when the displayed area of the cell is smaller or equal to a pixel of screen in order to find a new vector polyline approximate to the original one, which avoids lots of interpolation calculations and achieves seamless integration. Detailed operation steps are elaborated and the complexity of algorithm is analyzed. Thirdly, a prototype system has been developed by using VC++ language and OpenGL 3D API. ASTER GDEM data and DCW roads data sets of Jiangxi province in China are selected to evaluate the performance. The result shows that time consumption of shift algorithm decreased about 76% than that of geometry-based approach. Analysis on the mean shift error from different dimensions has been implemented. In the end, the conclusions and future works in the integration of vector data and DEM based on discrete global grids are also given.
Upper gastrointestinal endoscopies are primarily performed to observe the pathologies of the esophagus, stomach, and duodenum. However, when an endoscope is pushed into the esophagus or stomach by the physician, the o...
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ISBN:
(纸本)9780819495679
Upper gastrointestinal endoscopies are primarily performed to observe the pathologies of the esophagus, stomach, and duodenum. However, when an endoscope is pushed into the esophagus or stomach by the physician, the organs behave similar to a balloon being gradually inflated. Consequently, their shapes and depth-of-field of images change continually, preventing thorough examination of the inflammation or anabrosis position, which delays the curing period. In this study, a 2.9-mm image-capturing module and a convoluted mechanism was incorporated into the tube like a standard 10-mm upper gastrointestinal endoscope. The scale-invariant feature transform (SIFT) algorithm was adopted to implement disease feature extraction on a koala doll. Following feature extraction, the smoothly varying affine stitching (SVAS) method was employed to resolve stitching distortion problems. Subsequently, the real-time splice software developed in this study was embedded in an upper gastrointestinal endoscope to obtain a panoramic view of stomach inflammation in the captured images. The results showed that the 2.9-mm image-capturing module can provide approximately 50 verified images in one spin cycle, a viewing angle of 120 degrees can be attained, and less than 10% distortion can be achieved in each image. Therefore, these methods can solve the problems encountered when using a standard 10-mm upper gastrointestinal endoscope with a single camera, such as image distortion, and partial inflammation displays. The results also showed that the SIFT algorithm provides the highest correct matching rate, and the SVAS method can be employed to resolve the parallax problems caused by stitching together images of different flat surfaces.
The curvilinear coordinate method (C-method) is an exact method for analysing of electromagnetic waves scattering from rough surfaces. It is based on Maxwell's equations under covariant form written in a non-ortho...
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ISBN:
(纸本)9781510801011
The curvilinear coordinate method (C-method) is an exact method for analysing of electromagnetic waves scattering from rough surfaces. It is based on Maxwell's equations under covariant form written in a non-orthogonal coordinate system. This method leads to an eigenvalue system. All the eigenvalues and eigenvectors of the scattering matrix are required. The QR algorithm seems to be a suitable solution for this high dimension, dense, non-symmetric and complex scattering matrix. In this paper, we present the parallel QR algorithm that is specifically designed for the C-method. We define the "early shift" for the scattering matrix according to the property that we have observed. We mixed the "early shift", Wilkinson's shift and exceptional shift together to accelerate the convergence. Especially, we use the "early shift" first in order to have quick deflation of the real eigenvalues of the scattering matrix. The multi-window bulge chain chasing and parallel aggressive early deflation are used. The multi-window bulge chain chasing approach ensures that most computations are performed in 3 BLAS operations. The aggressive early deflation approach can detect deflation much quicker and thus accelerate convergence. Mixed MPI-OpenMP techniques are utilized for performing the codes to distributed memory platforms. Numerical experiments are performed and applications of this parallel QR algorithm are applied to a real physical problem of diffraction.
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