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Statistics; *Sampling
"... Two bootstrapping or resampling strategies were investigated to determine their applicability to estimating standard errors and ensuing confidence intervals on iariance components in twofactor random analysis of variance models. In light of prior negative findings regarding the application of boots ..."
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Two bootstrapping or resampling strategies were investigated to determine their applicability to estimating standard errors and ensuing confidence intervals on iariance components in twofactor random analysis of variance models. In light of prior negative findings regarding the application of bootstrapping to this particular problem, a recommendation of an "optimal " approach to resampling was sought. The study used Monte Carlo simulations to test the variance component estimati,n accuracy under simultaneous resampling of all effect factors in a random model versus resampling a single factor. Results indicate that singlefactor was a preferable method of resampling and produced reasonable estimates of both standard errors and confidence intervals (parametric and nonparametric). Suggestions for the appropriate application of the technique to educational measurement are discussed. (Author/TJH) ***2******************************************************************* Reproductions supplied by EDRS are the best that can be made from the original document. ******1c**************************************************************** No.
Compressive sampling
, 2006
"... Conventional wisdom and common practice in acquisition and reconstruction of images from frequency data follow the basic principle of the Nyquist density sampling theory. This principle states that to reconstruct an image, the number of Fourier samples we need to acquire must match the desired res ..."
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Cited by 1427 (15 self)
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mathematical insights underlying this new theory, and explain some of the interactions between compressive sampling and other fields such as statistics, information theory, coding theory, and theoretical computer science.
Exact Sampling with Coupled Markov Chains and Applications to Statistical Mechanics
, 1996
"... For many applications it is useful to sample from a finite set of objects in accordance with some particular distribution. One approach is to run an ergodic (i.e., irreducible aperiodic) Markov chain whose stationary distribution is the desired distribution on this set; after the Markov chain has ..."
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Cited by 548 (13 self)
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For many applications it is useful to sample from a finite set of objects in accordance with some particular distribution. One approach is to run an ergodic (i.e., irreducible aperiodic) Markov chain whose stationary distribution is the desired distribution on this set; after the Markov chain
Active Learning with Statistical Models
, 1995
"... For manytypes of learners one can compute the statistically "optimal" way to select data. We review how these techniques have been used with feedforward neural networks [MacKay, 1992# Cohn, 1994]. We then showhow the same principles may be used to select data for two alternative, statist ..."
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Cited by 677 (12 self)
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For manytypes of learners one can compute the statistically "optimal" way to select data. We review how these techniques have been used with feedforward neural networks [MacKay, 1992# Cohn, 1994]. We then showhow the same principles may be used to select data for two alternative
Directional Statistics and Shape Analysis
, 1995
"... There have been various developments in shape analysis in the last decade. We describe here some relationships of shape analysis with directional statistics. For shape, rotations are to be integrated out or to be optimized over whilst they are the basis for directional statistics. However, various c ..."
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Cited by 775 (31 self)
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There have been various developments in shape analysis in the last decade. We describe here some relationships of shape analysis with directional statistics. For shape, rotations are to be integrated out or to be optimized over whilst they are the basis for directional statistics. However, various
Texture Synthesis by Nonparametric Sampling
 In International Conference on Computer Vision
, 1999
"... A nonparametric method for texture synthesis is proposed. The texture synthesis process grows a new image outward from an initial seed, one pixel at a time. A Markov random field model is assumed, and the conditional distribution of a pixel given all its neighbors synthesized so far is estimated by ..."
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Cited by 1014 (7 self)
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by querying the sample image and finding all similar neighborhoods. The degree of randomness is controlled by a single perceptually intuitive parameter. The method aims at preserving as much local structure as possible and produces good results for a wide variety of synthetic and realworld textures. 1
On the statistical analysis of dirty pictures
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY B
, 1986
"... ..."
Statistical mechanics of complex networks
 Rev. Mod. Phys
"... Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as ra ..."
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Cited by 2083 (10 self)
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Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real
SMARTS: Accelerating Microarchitecture Simulation via Rigorous Statistical Sampling
 in Proceedings of the 30th annual international symposium on Computer architecture
, 2003
"... Current softwarebased microarchitecture simulators are many orders of magnitude slower than the hardware they simulate. Hence, most microarchitecture design studies draw their conclusions from drastically truncated benchmark simulations that are often inaccurate and misleading. This paper presents ..."
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Cited by 258 (26 self)
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the Sampling Microarchitecture Simulation (SMARTS) framework as an approach to enable fast and accurate performance measurements of fulllength benchmarks. SMARTS accelerates simulation by selectively measuring in detail only an appropriate benchmark subset. SMARTS prescribes a statistically sound procedure
Accurate Methods for the Statistics of Surprise and Coincidence
 COMPUTATIONAL LINGUISTICS
, 1993
"... Much work has been done on the statistical analysis of text. In some cases reported in the literature, inappropriate statistical methods have been used, and statistical significance of results have not been addressed. In particular, asymptotic normality assumptions have often been used unjustifiably ..."
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Cited by 1042 (1 self)
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Much work has been done on the statistical analysis of text. In some cases reported in the literature, inappropriate statistical methods have been used, and statistical significance of results have not been addressed. In particular, asymptotic normality assumptions have often been used
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