Orthogonal projections and bootstrap resampling procedures in the study of infraspecific variation
Directory of Open Access Journals (Sweden)
Luiza Carla Duarte
1998-12-01
Full Text Available The effect of an increase in quantitative continuous characters resulting from indeterminate growth upon the analysis of population differentiation was investigated using, as an example, a set of continuous characters measured as distance variables in 10 populations of a rodent species. The data before and after correction for allometric size effects using orthogonal projections were analyzed with a parametric bootstrap resampling procedure applied to canonical variate analysis. The variance component of the distance measures attributable to indeterminate growth within the populations was found to be substantial, although the ordination of the populations was not affected, as evidenced by the relative and absolute positions of the centroids. The covariance pattern of the distance variables used to infer the nature of the morphological differences was strongly influenced by indeterminate growth. The uncorrected data produced a misleading picture of morphological differentiation by indicating that groups of populations differed in size. However, the data corrected for allometric effects clearly demonstrated that populations differed morphologically both in size and shape. These results are discussed in terms of the analysis of morphological differentiation among populations and the definition of infraspecific geographic units.A influência do aumento em caracteres quantitativos contínuos devido ao crescimento indeterminado sobre a análise de diferenciação entre populações foi investigado utilizando como exemplo um conjunto de dados de variáveis craniométricas em 10 populações de uma espécie de roedor. Dois conjuntos de dados, um não corrigido para o efeito alométrico do tamanho e um outro corrigido para o efeito alométrico do tamanho utilizando um método de projeção ortogonal, foram analisados por um procedimento "bootstrap" de reamostragem aplicado à análise de variáveis canônicas. O componente de variância devido ao
Assessment of bootstrap resampling performance for PET data
International Nuclear Information System (INIS)
Bootstrap resampling has been successfully used for estimation of statistical uncertainty of parameters such as tissue metabolism, blood flow or displacement fields for image registration. The performance of bootstrap resampling as applied to PET list-mode data of the human brain and dedicated phantoms is assessed in a novel and systematic way such that: (1) the assessment is carried out in two resampling stages: the ‘real world’ stage where multiple reference datasets of varying statistical level are generated and the ‘bootstrap world’ stage where corresponding bootstrap replicates are generated from the reference datasets. (2) All resampled datasets were reconstructed yielding images from which multiple voxel and regions of interest (ROI) values were extracted to form corresponding distributions between the two stages. (3) The difference between the distributions from both stages was quantified using the Jensen–Shannon divergence and the first four moments. It was found that the bootstrap distributions are consistently different to the real world distributions across the statistical levels. The difference was explained by a shift in the mean (up to 33% for voxels and 14% for ROIs) being proportional to the inverse square root of the statistical level (number of counts). Other moments were well replicated by the bootstrap although for very low statistical levels the estimation of the variance was poor. Therefore, the bootstrap method should be used with care when estimating systematic errors (bias) and variance when very low statistical levels are present such as in early time frames of dynamic acquisitions, when the underlying population may not be sufficiently represented. (paper)
A nonparametric hypothesis test via the Bootstrap resampling
Temel, Tugrul
2011-01-01
This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to approximate errors involved in the asymptotic hypothesis test. The paper also develops a Mathematica Code for the test algorithm.
Application of a New Resampling Method to SEM: A Comparison of S-SMART with the Bootstrap
Bai, Haiyan; Sivo, Stephen A.; Pan, Wei; Fan, Xitao
2016-01-01
Among the commonly used resampling methods of dealing with small-sample problems, the bootstrap enjoys the widest applications because it often outperforms its counterparts. However, the bootstrap still has limitations when its operations are contemplated. Therefore, the purpose of this study is to examine an alternative, new resampling method…
Bootstrap re-sampling and cross-validation for neural network learning
Dupret, Georges; Koda, Masato
2000-01-01
A technical framework to assess the impact of re-sampling on the ability of a neural network is presented to correctly learn a classification problem.We use the bootstrap expression of the prediction error to identify the optimal re-sampling proportions in a numerical experiment with binary classes and propose a new,simple method to estimate this optimal proportion.An upper and a lower bounds for the optimal proportion are derived based on Bayes decision rule.The analytical considerations to ...
A new resampling method for sampling designs without replacement: the doubled half bootstrap
Antal, Erika; Tillé, Yves
2016-01-01
A new and very fast method of bootstrap for sampling without replacement from a finite population is proposed. This method can be used to estimate the variance in sampling with unequal inclusion probabilities and does not require artificial populations or utilization of bootstrap weights. The bootstrap samples are directly selected from the original sample. The bootstrap procedure contains two steps: in the first step, units are selected once with Poisson sampling using the same inclusion pro...
International Nuclear Information System (INIS)
We report on a broader evaluation of statistical bootstrap resampling methods as a tool for pixel-level calibration and imaging fidelity assessment in radio interferometry. Pixel-level imaging fidelity assessment is a challenging problem, important for the value it holds in robust scientific interpretation of interferometric images, enhancement of automated pipeline reduction systems needed to broaden the user community for these instruments, and understanding leading-edge direction-dependent calibration and imaging challenges for future telescopes such as the Square Kilometre Array. This new computational approach is now possible because of advances in statistical resampling for data with long-range dependence and the available performance of contemporary high-performance computing resources. We expand our earlier numerical evaluation to span a broader domain subset in simulated image fidelity and source brightness distribution morphologies. As before, we evaluate the statistical performance of the bootstrap resampling methods against direct Monte Carlo simulation. We find that both model-based and subsample bootstrap methods continue to show significant promise for the challenging problem of interferometric imaging fidelity assessment when evaluated over the broader domain subset. We report on their measured statistical performance and guidelines for their use and application in practice. We also examine the performance of the underlying polarization self-calibration algorithm used in this study over a range of parallactic angle coverage.
International Nuclear Information System (INIS)
Bootstrap resampling provides a versatile and reliable statistical method for estimating the accuracy of quantities which are calculated from experimental data. It is an empirically based method, in which large numbers of simulated datasets are generated by computer from existing measurements, so that approximate confidence intervals of the derived quantities may be obtained by direct numerical evaluation. A simple introduction to the method is given via a detailed example of estimating 95% confidence intervals for cumulated activity in the thyroid following injection of 99mTc-sodium pertechnetate using activity-time data from 23 subjects. The application of the approach to estimating confidence limits for the self-dose to the kidney following injection of 99mTc-DTPA organ imaging agent based on uptake data from 19 subjects is also illustrated. Results are then given for estimates of doses to the foetus following administration of 99mTc-sodium pertechnetate for clinical reasons during pregnancy, averaged over 25 subjects. The bootstrap method is well suited for applications in radiation dosimetry including uncertainty, reliability and sensitivity analysis of dose coefficients in biokinetic models, but it can also be applied in a wide range of other biomedical situations. (author)
Fingerprint resampling: A generic method for efficient resampling
Merijn Mestdagh; Stijn Verdonck; Kevin Duisters; Francis Tuerlinckx
2015-01-01
In resampling methods, such as bootstrapping or cross validation, a very similar computational problem (usually an optimization procedure) is solved over and over again for a set of very similar data sets. If it is computationally burdensome to solve this computational problem once, the whole resampling method can become unfeasible. However, because the computational problems and data sets are so similar, the speed of the resampling method may be increased by taking advantage of these similar...
Hilmer, Christiana E.; Holt, Matthew T.
2000-01-01
This paper compares the finite sample performance of subsample bootstrap and subsample jackknife techniques to the traditional bootstrap method when parameters are constrained to be on some boundary. To assess how these three methods perform in an empirical application, a negative semi-definite translog cost function is estimated using U.S. manufacturing data.
Unbiased Estimates of Variance Components with Bootstrap Procedures
Brennan, Robert L.
2007-01-01
This article provides general procedures for obtaining unbiased estimates of variance components for any random-model balanced design under any bootstrap sampling plan, with the focus on designs of the type typically used in generalizability theory. The results reported here are particularly helpful when the bootstrap is used to estimate standard…
Fingerprint resampling: A generic method for efficient resampling
Mestdagh, Merijn; Verdonck, Stijn; Duisters, Kevin; Tuerlinckx, Francis
2015-01-01
In resampling methods, such as bootstrapping or cross validation, a very similar computational problem (usually an optimization procedure) is solved over and over again for a set of very similar data sets. If it is computationally burdensome to solve this computational problem once, the whole resampling method can become unfeasible. However, because the computational problems and data sets are so similar, the speed of the resampling method may be increased by taking advantage of these similarities in method and data. As a generic solution, we propose to learn the relation between the resampled data sets and their corresponding optima. Using this learned knowledge, we are then able to predict the optima associated with new resampled data sets. First, these predicted optima are used as starting values for the optimization process. Once the predictions become accurate enough, the optimization process may even be omitted completely, thereby greatly decreasing the computational burden. The suggested method is validated using two simple problems (where the results can be verified analytically) and two real-life problems (i.e., the bootstrap of a mixed model and a generalized extreme value distribution). The proposed method led on average to a tenfold increase in speed of the resampling method. PMID:26597870
A Bootstrap Procedure of Propensity Score Estimation
Bai, Haiyan
2013-01-01
Propensity score estimation plays a fundamental role in propensity score matching for reducing group selection bias in observational data. To increase the accuracy of propensity score estimation, the author developed a bootstrap propensity score. The commonly used propensity score matching methods: nearest neighbor matching, caliper matching, and…
Institute of Scientific and Technical Information of China (English)
Fang-Ling Tao; Shi-Fan Min; Wei-Jian Wu; Guang-Wen Liang; Ling Zeng
2008-01-01
Taking a published natural population life table office leaf roller, Cnaphalocrocis medinalis (Lepidoptera: Pyralidae), as an example, we estimated the population trend index,I, via re-sampling methods (jackknife and bootstrap), determined its statistical properties and illustrated the application of these methods in determining the control effectiveness of bio-agents and chemical insecticides. Depending on the simulation outputs, the smoothed distribution pattern of the estimates of I by delete-1 jackknife is visually distinguishable from the normal density, but the smoothed pattern produced by delete-d jackknife, and logarithm-transformed smoothed patterns produced by both empirical and parametric bootstraps,matched well the corresponding normal density. Thus, the estimates of I produced by delete-1 jackknife were not used to determine the suppressive effect of wasps and insecticides. The 95% percent confidence intervals or the narrowest 95 percentiles and Z-test criterion were employed to compare the effectiveness of Trichogrammajaponicum Ashmead and insecti-cides (powder, 1.5% mevinphos + 3% alpha-hexachloro cyclohexane) against the rice leaf roller based on the estimates of I produced by delete-d jackknife and bootstrap techniques.At α= 0.05 level, there were statistical differences between wasp treatment and control, and between wasp and insecticide treatments, if the normality is ensured, or by the narrowest 95 percentiles. However, there is still no difference between insecticide treatment and control.By Z-test criterion, wasp treatment is better than control and insecticide treatment with P-value＜0.01. Insecticide treatment is similar to control with P-value ＞ 0.2 indicating that 95% confidence intervals procedure is more conservative. Although similar conclusions may be drawn by re-sampling techniques, such as the delta method, about the suppressive effect of trichogramma and insecticides, the normality of the estimates can be checked and guaranteed
USEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT
Directory of Open Access Journals (Sweden)
Boris Radovanov
2012-12-01
Full Text Available This paper contains a comparison of in-sample and out-of-sample performances between the resampled efficiency technique, patented by Richard Michaud and Robert Michaud (1999, and traditional Mean-Variance portfolio selection, presented by Harry Markowitz (1952. Based on the Monte Carlo simulation, data (samples generation process determines the algorithms by using both, parametric and nonparametric bootstrap techniques. Resampled efficiency provides the solution to use uncertain information without the need for constrains in portfolio optimization. Parametric bootstrap process starts with a parametric model specification, where we apply Capital Asset Pricing Model. After the estimation of specified model, the series of residuals are used for resampling process. On the other hand, nonparametric bootstrap divides series of price returns into the new series of blocks containing previous determined number of consecutive price returns. This procedure enables smooth resampling process and preserves the original structure of data series.
Bootstrap determination of the cointegration rank in heteroskedastic VAR models
DEFF Research Database (Denmark)
Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert
2014-01-01
In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio (PLR) co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates of...... the underlying vector autoregressive (VAR) model which obtain under the reduced rank null hypothesis. They propose methods based on an independent and individual distributed (i.i.d.) bootstrap resampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co......-integrated VAR model with i.i.d. innovations. In this paper we investigate the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap resampling scheme, when time-varying behavior is present in either the conditional or unconditional variance of the innovations. We...
Directory of Open Access Journals (Sweden)
Osmir José Lavoranti
2010-06-01
Full Text Available Reliable evaluation of the stability of genotypes and environment is of prime concern to plant breeders, but the lack of a comprehensive analysis of the structure of the GE interaction has been a stumbling block to the recommendation of varieties. The Additive Main Effects and Multiplicative Interaction (AMMI Model currently offers the good approach to interpretation and understanding of the GE interaction but lacks a way of assessing the stability of its estimates. The present contribution proposes the use of bootstrap resampling
in the AMMI Model, and applies it to obtain both a graphical and a numerical analysis of the phenotypic
stability of 20 Eucalyptus grandis progenies from Australia that were planted in seven environments in the Southern and Southeastern regions of Brazil. The results showed distinct behaviors of genotypes and
environments and the genotype x environment interaction was significant (p value < 0.01. The bootstrap coefficient of stability based on the squared Mahalanobis distance of the scores showed that genotypes and environments can be differentiated in terms of their stabilities. Graphical analysis of the AMMI biplot provided a better understanding of the interpretation of phenotypic stability. The proposed AMMI bootstrap eliminated the uncertainties regarding the identification of low scores in traditional analyses.As posições críticas dos estatísticos, que atuam em programas de melhoramento genético, referem-se à falta de uma análise criteriosa da estrutura da interação do genótipo com o ambiente (GE como um dos principais problemas para a recomendação de cultivares. A metodologia AMMI (additive main effects and multiplicative interaction analysis propõe ser mais eficiente que as análises usuais na interpretação e compreensão da interação GE, entretanto, à dificuldade de se interpretar a interação quando há baixa explicação do primeiro componente principal; à dificuldade de
Bootstrap Determination of the Co-Integration Rank in Heteroskedastic VAR Models
DEFF Research Database (Denmark)
Cavaliere, Giuseppe; Rahbek, Anders; Taylor, A. M. Robert
In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio [PLR] co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates of...... the underlying VAR model which obtain under the reduced rank null hypothesis. They propose methods based on an i.i.d. bootstrap re-sampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co-integrated VAR model with i.i.d. innovations. In this paper we...... investigate the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap re-sampling scheme, when time-varying behaviour is present in either the conditional or unconditional variance of the innovations. We show that the bootstrap PLR tests are asymptotically...
Bootstrap Determination of the Co-integration Rank in Heteroskedastic VAR Models
DEFF Research Database (Denmark)
Cavaliere, Giuseppe; Rahbek, Anders; Taylor, A.M.Robert
In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio [PLR] co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates of...... the underlying VAR model which obtain under the reduced rank null hypothesis. They propose methods based on an i.i.d. bootstrap re-sampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co-integrated VAR model with i.i.d. innovations. In this paper we...... investigate the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap re-sampling scheme, when time-varying behaviour is present in either the conditional or unconditional variance of the innovations. We show that the bootstrap PLR tests are asymptotically...
The wild tapered block bootstrap
DEFF Research Database (Denmark)
Hounyo, Ulrich
In this paper, a new resampling procedure, called the wild tapered block bootstrap, is introduced as a means of calculating standard errors of estimators and constructing confidence regions for parameters based on dependent heterogeneous data. The method consists in tapering each overlapping block......-of-the-art block-based method in terms of asymptotic accuracy of variance estimation and distribution approximation. For stationary time series, the asymptotic validity, and the favorable bias properties of the new bootstrap method are shown in two important cases: smooth functions of means, and M-estimators. The...... estimator for the sample mean is shown to be robust against heteroskedasticity of the wild tapered block bootstrap. This easy to implement alternative bootstrap method works very well even for moderate sample sizes....
Mitterpach, Róbert
2012-01-01
Aim of this thesis is to introduce the reader to the basic bootstrap techniques used in econometrics, to present their variations and importance. Results of the ordinary least squares model, residual bootstrap and case resampling bootstrap will be presented and compared on cross-sectional data and time series from small numbered random subsample from the available data. Bootstrap was shown to improve numerical performance of ordinary least squares model.
The Local Fractional Bootstrap
DEFF Research Database (Denmark)
Bennedsen, Mikkel; Hounyo, Ulrich; Lunde, Asger;
new resampling method, the local fractional bootstrap, relies on simulating an auxiliary fractional Brownian motion that mimics the fine properties of high frequency differences of the Brownian semistationary process under the null hypothesis. We prove the first order validity of the bootstrap method...
Introductory statistics and analytics a resampling perspective
Bruce, Peter C
2014-01-01
Concise, thoroughly class-tested primer that features basic statistical concepts in the concepts in the context of analytics, resampling, and the bootstrapA uniquely developed presentation of key statistical topics, Introductory Statistics and Analytics: A Resampling Perspective provides an accessible approach to statistical analytics, resampling, and the bootstrap for readers with various levels of exposure to basic probability and statistics. Originally class-tested at one of the first online learning companies in the discipline, www.statistics.com, the book primarily focuses on application
Wild Bootstrap Versus Moment-Oriented Bootstrap
Sommerfeld, Volker
1997-01-01
We investigate the relative merits of a “moment-oriented” bootstrap method of Bunke (1997) in comparison with the classical wild bootstrap of Wu (1986) in nonparametric heteroscedastic regression situations. The “moment-oriented” bootstrap is a wild bootstrap based on local estimators of higher order error moments that are smoothed by kernel smoothers. In this paper we perform an asymptotic comparison of these two dierent bootstrap procedures. We show that the moment-oriented bootstrap is in ...
A bootstrap procedure to select hyperspectral wavebands related to tannin content
Ferwerda, J.G.; Skidmore, A.K.; Stein, A.
2006-01-01
Detection of hydrocarbons in plants with hyperspectral remote sensing is hampered by overlapping absorption pits, while the `optimal' wavebands for detecting some surface characteristics (e.g. chlorophyll, lignin, tannin) may shift. We combined a phased regression with a bootstrap procedure to find
Efficient p-value evaluation for resampling-based tests
Yu, K.
2011-01-05
The resampling-based test, which often relies on permutation or bootstrap procedures, has been widely used for statistical hypothesis testing when the asymptotic distribution of the test statistic is unavailable or unreliable. It requires repeated calculations of the test statistic on a large number of simulated data sets for its significance level assessment, and thus it could become very computationally intensive. Here, we propose an efficient p-value evaluation procedure by adapting the stochastic approximation Markov chain Monte Carlo algorithm. The new procedure can be used easily for estimating the p-value for any resampling-based test. We show through numeric simulations that the proposed procedure can be 100-500 000 times as efficient (in term of computing time) as the standard resampling-based procedure when evaluating a test statistic with a small p-value (e.g. less than 10( - 6)). With its computational burden reduced by this proposed procedure, the versatile resampling-based test would become computationally feasible for a much wider range of applications. We demonstrate the application of the new method by applying it to a large-scale genetic association study of prostate cancer.
Generalized bootstrap for estimating equations
Chatterjee, Snigdhansu; Bose, Arup
2005-01-01
We introduce a generalized bootstrap technique for estimators obtained by solving estimating equations. Some special cases of this generalized bootstrap are the classical bootstrap of Efron, the delete-d jackknife and variations of the Bayesian bootstrap. The use of the proposed technique is discussed in some examples. Distributional consistency of the method is established and an asymptotic representation of the resampling variance estimator is obtained.
MacKinnon, James G.
2007-01-01
This paper surveys bootstrap and Monte Carlo methods for testing hypotheses in econometrics. Several different ways of computing bootstrap P values are discussed, including the double bootstrap and the fast double bootstrap. It is emphasized that there are many different procedures for generating bootstrap samples for regression models and other types of model. As an illustration, a simulation experiment examines the performance of several methods of bootstrapping the supF test for structural...
Del Barrio, Eustasio; Lescornel, Hélène; Loubes, Jean-Michel
2016-01-01
Wasserstein barycenters and variance-like criterion using Wasserstein distance are used in many problems to analyze the homo-geneity of collections of distributions and structural relationships between the observations. We propose the estimation of the quantiles of the empirical process of the Wasserstein's variation using a bootstrap procedure. Then we use these results for statistical inference on a distribution registration model for general deformation functions. The tests are based on th...
A Bayesian approach to efficient differential allocation for resampling-based significance testing
Directory of Open Access Journals (Sweden)
Soi Sameer
2009-06-01
Full Text Available Abstract Background Large-scale statistical analyses have become hallmarks of post-genomic era biological research due to advances in high-throughput assays and the integration of large biological databases. One accompanying issue is the simultaneous estimation of p-values for a large number of hypothesis tests. In many applications, a parametric assumption in the null distribution such as normality may be unreasonable, and resampling-based p-values are the preferred procedure for establishing statistical significance. Using resampling-based procedures for multiple testing is computationally intensive and typically requires large numbers of resamples. Results We present a new approach to more efficiently assign resamples (such as bootstrap samples or permutations within a nonparametric multiple testing framework. We formulated a Bayesian-inspired approach to this problem, and devised an algorithm that adapts the assignment of resamples iteratively with negligible space and running time overhead. In two experimental studies, a breast cancer microarray dataset and a genome wide association study dataset for Parkinson's disease, we demonstrated that our differential allocation procedure is substantially more accurate compared to the traditional uniform resample allocation. Conclusion Our experiments demonstrate that using a more sophisticated allocation strategy can improve our inference for hypothesis testing without a drastic increase in the amount of computation on randomized data. Moreover, we gain more improvement in efficiency when the number of tests is large. R code for our algorithm and the shortcut method are available at http://people.pcbi.upenn.edu/~lswang/pub/bmc2009/.
A Neurocomputational Theory of how Explicit Learning Bootstraps Early Procedural Learning
Directory of Open Access Journals (Sweden)
Erick Joseph Paul
2013-12-01
Full Text Available It is widely accepted that human learning and memory is mediated by multiple memory systems that are each best suited to different requirements and demands. Within the domain of categorization, at least two systems are thought to facilitate learning: an explicit (declarative system depending largely on the prefrontal cortex, and a procedural (non-declarative system depending on the basal ganglia. Substantial evidence suggests that each system is optimally suited to learn particular categorization tasks. However, it remains unknown precisely how these systems interact to produce optimal learning and behavior. In order to investigate this issue, the present research evaluated the progression of learning through simulation of categorization tasks using COVIS, a well-known model of human category learning that includes both explicit and procedural learning systems. Specifically, the model's parameter space was thoroughly explored in procedurally learned categorization tasks across a variety of conditions and architectures to identify plausible interaction architectures. The simulation results support the hypothesis that one-way interaction between the systems occurs such that the explicit system "bootstraps" learning early on in the procedural system. Thus, the procedural system initially learns a suboptimal strategy employed by the explicit system and later refines its strategy. This bootstrapping could be from cortical-striatal projections that originate in premotor or motor regions of cortex, or possibly by the explicit system’s control of motor responses through basal ganglia-mediated loops.
A neurocomputational theory of how explicit learning bootstraps early procedural learning.
Paul, Erick J; Ashby, F Gregory
2013-01-01
It is widely accepted that human learning and memory is mediated by multiple memory systems that are each best suited to different requirements and demands. Within the domain of categorization, at least two systems are thought to facilitate learning: an explicit (declarative) system depending largely on the prefrontal cortex, and a procedural (non-declarative) system depending on the basal ganglia. Substantial evidence suggests that each system is optimally suited to learn particular categorization tasks. However, it remains unknown precisely how these systems interact to produce optimal learning and behavior. In order to investigate this issue, the present research evaluated the progression of learning through simulation of categorization tasks using COVIS, a well-known model of human category learning that includes both explicit and procedural learning systems. Specifically, the model's parameter space was thoroughly explored in procedurally learned categorization tasks across a variety of conditions and architectures to identify plausible interaction architectures. The simulation results support the hypothesis that one-way interaction between the systems occurs such that the explicit system "bootstraps" learning early on in the procedural system. Thus, the procedural system initially learns a suboptimal strategy employed by the explicit system and later refines its strategy. This bootstrapping could be from cortical-striatal projections that originate in premotor or motor regions of cortex, or possibly by the explicit system's control of motor responses through basal ganglia-mediated loops. PMID:24385962
Survey bootstrap and bootstrap weights
Stas Kolenikov
2008-01-01
In this presentation, I will review the bootstrap for complex surveys with designs featuring stratification, clustering, and unequal probability weights. I will present the Stata module bsweights, which creates the bootstrap weights for designs specified through and supported by svy. I will also provide simple demonstrations highlighting the use of the procedure and its syntax. I will discuss various tuning parameters and their impact on the performance of the procedure, and I will give argum...
DEFF Research Database (Denmark)
Hounyo, Ulrich; Varneskov, Rasmus T.
We provide a new resampling procedure - the local stable bootstrap - that is able to mimic the dependence properties of realized power variations for pure-jump semimartingales observed at different frequencies. This allows us to propose a bootstrap estimator and inference procedure for the activity...... index of the underlying process, β, as well as a bootstrap test for whether it obeys a jump-diffusion or a pure-jump process, that is, of the null hypothesis H₀: β=2 against the alternative H₁: β<2. We establish first-order asymptotic validity of the resulting bootstrap power variations, activity index...... estimator, and diffusion test for H0. Moreover, the finite sample size and power properties of the proposed diffusion test are compared to those of benchmark tests using Monte Carlo simulations. Unlike existing procedures, our bootstrap test is correctly sized in general settings. Finally, we illustrate use...
Variance estimation in neutron coincidence counting using the bootstrap method
International Nuclear Information System (INIS)
In the study, we demonstrate the implementation of the “bootstrap” method for a reliable estimation of the statistical error in Neutron Multiplicity Counting (NMC) on plutonium samples. The “bootstrap” method estimates the variance of a measurement through a re-sampling process, in which a large number of pseudo-samples are generated, from which the so-called bootstrap distribution is generated. The outline of the present study is to give a full description of the bootstrapping procedure, and to validate, through experimental results, the reliability of the estimated variance. Results indicate both a very good agreement between the measured variance and the variance obtained through the bootstrap method, and a robustness of the method with respect to the duration of the measurement and the bootstrap parameters
Variance estimation in neutron coincidence counting using the bootstrap method
Energy Technology Data Exchange (ETDEWEB)
Dubi, C., E-mail: chendb331@gmail.com [Physics Department, Nuclear Research Center of the Negev, P.O.B. 9001 Beer Sheva (Israel); Ocherashvilli, A.; Ettegui, H. [Physics Department, Nuclear Research Center of the Negev, P.O.B. 9001 Beer Sheva (Israel); Pedersen, B. [Nuclear Security Unit, Institute for Transuranium Elements, Via E. Fermi, 2749 JRC, Ispra (Italy)
2015-09-11
In the study, we demonstrate the implementation of the “bootstrap” method for a reliable estimation of the statistical error in Neutron Multiplicity Counting (NMC) on plutonium samples. The “bootstrap” method estimates the variance of a measurement through a re-sampling process, in which a large number of pseudo-samples are generated, from which the so-called bootstrap distribution is generated. The outline of the present study is to give a full description of the bootstrapping procedure, and to validate, through experimental results, the reliability of the estimated variance. Results indicate both a very good agreement between the measured variance and the variance obtained through the bootstrap method, and a robustness of the method with respect to the duration of the measurement and the bootstrap parameters.
Resampling in particle filters
Hol, Jeroen D.
2004-01-01
In this report a comparison is made between four frequently encountered resampling algorithms for particle filters. A theoretical framework is introduced to be able to understand and explain the differences between the resampling algorithms. This facilitates a comparison of the algorithms based on resampling quality and on computational complexity. Using extensive Monte Carlo simulations the theoretical results are verified. It is found that systematic resampling is favourable, both in resamp...
Del Barrio, Eustasio; Lescornel, Hélène; Loubes, Jean-Michel
2016-01-01
Wasserstein barycenters and variance-like criterion using Wasser-stein distance are used in many problems to analyze the homogeneity of collections of distributions and structural relationships between the observations. We propose the estimation of the quantiles of the empirical process of the Wasserstein's variation using a bootstrap procedure. Then we use these results for statistical inference on a distribution registration model for general deformation functions. The tests are based on th...
Bootstrap, Wild Bootstrap and Generalized Bootstrap
Mammen, Enno
1995-01-01
Some modifications and generalizations of the bootstrap procedurehave been proposed. In this note we will consider the wild bootstrap and the generalized bootstrap and we will give two arguments why it makes sense touse these modifications instead of the original bootstrap. The firstargument is that there exist examples where generalized and wild bootstrapwork, but where the original bootstrap fails and breaks down. The secondargument will be based on higher order considerations. We will show...
On constructing accurate conﬁdence bands for ROC curves through smooth resampling
Bertail, Patrice; Clémençon, Stéphan; Vayatis, Nicolas
2008-01-01
This paper is devoted to thoroughly inves- tigating how to bootstrap the ROC curve, a widely used visual tool for evaluating the accuracy of test/scoring statistics s(X) in the bipartite setup. The issue of conﬁdence bands for the ROC curve is considered and a resampling procedure based on a smooth ver- sion of the empirical distribution called the ”smoothed bootstrap” is introduced. Theo- retical arguments and simulation results are presented to show that the ”smoothed boot- strap” is prefer...
Applications of the Fast Double Bootstrap
MacKinnon, James G.
2006-01-01
The fast double bootstrap, or FDB, is a procedure for calculating bootstrap P values that is much more computationally efficient than the double bootstrap itself. In many cases, it can provide more accurate results than ordinary bootstrap tests. For the fast double bootstrap to be valid, the test statistic must be asymptotically independent of the random parts of the bootstrap data generating process. This paper presents simulation evidence on the performance of FDB tests in three cases of in...
The bootstrap and Bayesian bootstrap method in assessing bioequivalence
International Nuclear Information System (INIS)
Parametric method for assessing individual bioequivalence (IBE) may concentrate on the hypothesis that the PK responses are normal. Nonparametric method for evaluating IBE would be bootstrap method. In 2001, the United States Food and Drug Administration (FDA) proposed a draft guidance. The purpose of this article is to evaluate the IBE between test drug and reference drug by bootstrap and Bayesian bootstrap method. We study the power of bootstrap test procedures and the parametric test procedures in FDA (2001). We find that the Bayesian bootstrap method is the most excellent.
Niska, Christoffer
2014-01-01
Practical and instruction-based, this concise book will take you from understanding what Bootstrap is, to creating your own Bootstrap theme in no time! If you are an intermediate front-end developer or designer who wants to learn the secrets of Bootstrap, this book is perfect for you.
Bootstrap and Wild Bootstrap for High Dimensional Linear Models
Mammen, Enno
1993-01-01
In this paper two bootstrap procedures are considered for the estimation of the distribution of linear contrasts and of F-test statistics in high dimensional linear models. An asymptotic approach will be chosen where the dimension p of the model may increase for sample size $n\\rightarrow\\infty$. The range of validity will be compared for the normal approximation and for the bootstrap procedures. Furthermore, it will be argued that the rates of convergence are different for the bootstrap proce...
Improving the Reliability of Bootstrap Tests
Russell Davidson; MacKinnon, James G.
2000-01-01
We first propose procedures for estimating the rejection probabilities for bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication. These procedures are only about twice as expensive as estimating rejection probabilities for asymptotic tersts. We then propose procedures for computing modified bootstrap P values that will often be more accurate than ordinary ones. These procedures are closely related to the double bootstrap, but they are far ...
Bootstrap confidence intervals
Thomas J. DiCiccio; Efron, Bradley
1996-01-01
This article surveys bootstrap methods for producing good approximate confidence intervals. The goal is to improve by an order of magnitude upon the accuracy of the standard intervals $\\hat{\\theta} \\pm z^{(\\alpha)} \\hat{\\sigma}$, in a way that allows routine application even to very complicated problems. Both theory and examples are used to show how this is done. The first seven sections provide a heuristic overview of four bootstrap confidence interval procedures: $BC_a$, bootstrap-t , ABC a...
Asymptotic properties of robust three-stage procedure based on bootstrap for m-estimator
Hlávka, Zdenéek
2000-01-01
The paper concerns the fixed-width confidence intervals for location based on M- estimators in the location model. A robust three-stage procedure is proposed and its asymptotic properties are studied. The performance of the procedure depends on some tuning parameters. Their effect on the proposed confidence interval is checked together with the overall behaviour of the procedure in a simulation study.
The cluster bootstrap consistency in generalized estimating equations
Cheng, Guang
2013-03-01
The cluster bootstrap resamples clusters or subjects instead of individual observations in order to preserve the dependence within each cluster or subject. In this paper, we provide a theoretical justification of using the cluster bootstrap for the inferences of the generalized estimating equations (GEE) for clustered/longitudinal data. Under the general exchangeable bootstrap weights, we show that the cluster bootstrap yields a consistent approximation of the distribution of the regression estimate, and a consistent approximation of the confidence sets. We also show that a computationally more efficient one-step version of the cluster bootstrap provides asymptotically equivalent inference. © 2012.
Bootstrapping heteroskedastic regression models: wild bootstrap vs. pairs bootstrap
Flachaire, Emmanuel
2005-01-01
International audience In regression models, appropriate bootstrap methods for inference robust to heteroskedasticity of unknown form are the wild bootstrap and the pairs bootstrap. The finite sample performance of a heteroskedastic-robust test is investigated with Monte Carlo experiments. The simulation results suggest that one specific version of the wild bootstrap outperforms the other versions of the wild bootstrap and of the pairs bootstrap. It is the only one for which the bootstrap ...
A Neurocomputational Theory of how Explicit Learning Bootstraps Early Procedural Learning
Erick Joseph Paul; F. Gregory Ashby
2013-01-01
It is widely accepted that human learning and memory is mediated by multiple memory systems that are each best suited to different requirements and demands. Within the domain of categorization, at least two systems are thought to facilitate learning: an explicit (declarative) system depending largely on the prefrontal cortex, and a procedural (non-declarative) system depending on the basal ganglia. Substantial evidence suggests that each system is optimally suited to learn particular categori...
A neurocomputational theory of how explicit learning bootstraps early procedural learning
Paul, Erick J.; Ashby, F. Gregory
2013-01-01
It is widely accepted that human learning and memory is mediated by multiple memory systems that are each best suited to different requirements and demands. Within the domain of categorization, at least two systems are thought to facilitate learning: an explicit (declarative) system depending largely on the prefrontal cortex, and a procedural (non-declarative) system depending on the basal ganglia. Substantial evidence suggests that each system is optimally suited to learn particular categori...
RIO: Analyzing proteomes by automated phylogenomics using resampled inference of orthologs
Directory of Open Access Journals (Sweden)
Eddy Sean R
2002-05-01
Full Text Available Abstract Background When analyzing protein sequences using sequence similarity searches, orthologous sequences (that diverged by speciation are more reliable predictors of a new protein's function than paralogous sequences (that diverged by gene duplication. The utility of phylogenetic information in high-throughput genome annotation ("phylogenomics" is widely recognized, but existing approaches are either manual or not explicitly based on phylogenetic trees. Results Here we present RIO (Resampled Inference of Orthologs, a procedure for automated phylogenomics using explicit phylogenetic inference. RIO analyses are performed over bootstrap resampled phylogenetic trees to estimate the reliability of orthology assignments. We also introduce supplementary concepts that are helpful for functional inference. RIO has been implemented as Perl pipeline connecting several C and Java programs. It is available at http://www.genetics.wustl.edu/eddy/forester/. A web server is at http://www.rio.wustl.edu/. RIO was tested on the Arabidopsis thaliana and Caenorhabditis elegans proteomes. Conclusion The RIO procedure is particularly useful for the automated detection of first representatives of novel protein subfamilies. We also describe how some orthologies can be misleading for functional inference.
Confidence Intervals for Effect Sizes: Applying Bootstrap Resampling
Banjanovic, Erin S.; Osborne, Jason W.
2016-01-01
Confidence intervals for effect sizes (CIES) provide readers with an estimate of the strength of a reported statistic as well as the relative precision of the point estimate. These statistics offer more information and context than null hypothesis statistic testing. Although confidence intervals have been recommended by scholars for many years,…
Janitza, Silke; Binder, Harald; Boulesteix, Anne-Laure
2016-05-01
The bootstrap method has become a widely used tool applied in diverse areas where results based on asymptotic theory are scarce. It can be applied, for example, for assessing the variance of a statistic, a quantile of interest or for significance testing by resampling from the null hypothesis. Recently, some approaches have been proposed in the biometrical field where hypothesis testing or model selection is performed on a bootstrap sample as if it were the original sample. P-values computed from bootstrap samples have been used, for example, in the statistics and bioinformatics literature for ranking genes with respect to their differential expression, for estimating the variability of p-values and for model stability investigations. Procedures which make use of bootstrapped information criteria are often applied in model stability investigations and model averaging approaches as well as when estimating the error of model selection procedures which involve tuning parameters. From the literature, however, there is evidence that p-values and model selection criteria evaluated on bootstrap data sets do not represent what would be obtained on the original data or new data drawn from the overall population. We explain the reasons for this and, through the use of a real data set and simulations, we assess the practical impact on procedures relevant to biometrical applications in cases where it has not yet been studied. Moreover, we investigate the behavior of subsampling (i.e., drawing from a data set without replacement) as a potential alternative solution to the bootstrap for these procedures. PMID:26372408
A comparison of four different block bootstrap methods
Boris Radovanov; Aleksandra Marcikić
2014-01-01
The paper contains a description of four different block bootstrap methods, i.e., non-overlapping block bootstrap, overlapping block bootstrap (moving block bootstrap), stationary block bootstrap and subsampling. Furthermore, the basic goal of this paper is to quantify relative efficiency of each mentioned block bootstrap procedure and then to compare those methods. To achieve the goal, we measure mean square errors of estimation variance returns. The returns are calculated from 1250 daily ob...
Temperature Corrected Bootstrap Algorithm
Comiso, Joey C.; Zwally, H. Jay
1997-01-01
A temperature corrected Bootstrap Algorithm has been developed using Nimbus-7 Scanning Multichannel Microwave Radiometer data in preparation to the upcoming AMSR instrument aboard ADEOS and EOS-PM. The procedure first calculates the effective surface emissivity using emissivities of ice and water at 6 GHz and a mixing formulation that utilizes ice concentrations derived using the current Bootstrap algorithm but using brightness temperatures from 6 GHz and 37 GHz channels. These effective emissivities are then used to calculate surface ice which in turn are used to convert the 18 GHz and 37 GHz brightness temperatures to emissivities. Ice concentrations are then derived using the same technique as with the Bootstrap algorithm but using emissivities instead of brightness temperatures. The results show significant improvement in the area where ice temperature is expected to vary considerably such as near the continental areas in the Antarctic, where the ice temperature is colder than average, and in marginal ice zones.
Pfiffner, H. J.
1969-01-01
Circuit can sample a number of transducers in sequence without drawing from them. This bootstrap unloader uses a differential amplifier with one input connected to a circuit which is the equivalent of the circuit to be unloaded, and the other input delivering the proper unloading currents.
Bhaumik, Snig
2015-01-01
If you are a web developer who designs and develops websites and pages using HTML, CSS, and JavaScript, but have very little familiarity with Bootstrap, this is the book for you. Previous experience with HTML, CSS, and JavaScript will be helpful, while knowledge of jQuery would be an extra advantage.
Ding, Cody S
2005-02-01
Although multidimensional scaling (MDS) profile analysis is widely used to study individual differences, there is no objective way to evaluate the statistical significance of the estimated scale values. In the present study, a resampling technique (bootstrapping) was used to construct confidence limits for scale values estimated from MDS profile analysis. These bootstrap confidence limits were used, in turn, to evaluate the significance of marker variables of the profiles. The results from analyses of both simulation data and real data suggest that the bootstrap method may be valid and may be used to evaluate hypotheses about the statistical significance of marker variables of MDS profiles. PMID:16097342
The Chopthin Algorithm for Resampling
Gandy, Axel; Lau, F. Din-Houn
2016-08-01
Resampling is a standard step in particle filters and more generally sequential Monte Carlo methods. We present an algorithm, called chopthin, for resampling weighted particles. In contrast to standard resampling methods the algorithm does not produce a set of equally weighted particles; instead it merely enforces an upper bound on the ratio between the weights. Simulation studies show that the chopthin algorithm consistently outperforms standard resampling methods. The algorithms chops up particles with large weight and thins out particles with low weight, hence its name. It implicitly guarantees a lower bound on the effective sample size. The algorithm can be implemented efficiently, making it practically useful. We show that the expected computational effort is linear in the number of particles. Implementations for C++, R (on CRAN), Python and Matlab are available.
Bootstraping the general linear hypothesis test
Delicado, Pedro; Río, Manuel del, 1690-1766
1993-01-01
We discuss the use of bootstrap methodology in hypothesis testing, focusing on the classical F-test for linear hypotheses in the linear model. A modification of the F-statistics which allows for resampling under the null hypothesis is proposed. This approach is specifically considered in the one-way analysis of variance model. A simulation study illustrating the behaviour of our proposal is presented.
Monotonicity-preserving bootstrapped kriging metamodels for expensive simulations
Kleijnen, Jack P.C.; Beers, W.C.M. van
2013-01-01
Kriging (Gaussian process, spatial correlation) metamodels approximate the Input/Output (I/O) functions implied by the underlying simulation models; such metamodels serve sensitivity analysis and optimization, especially for computationally expensive simulations. In practice, simulation analysts often know that the I/O function is monotonic. To obtain a Kriging metamodel that preserves this known shape, this article uses bootstrapping (or resampling). Parametric bootstrapping assuming normali...
On the M fewer than N bootstrap approximation to the trimmed mean
Gribkova, N.; Helmers, R.
2008-01-01
We show that the M fewer than N (N is the real data sample size, M denotes the size of the bootstrap resample; M=N ! 0, as M ! 1) bootstrap approximation to the distribution of the trimmed mean is consistent without any conditions on the population distribution F, whereas Efron's naive (i.e. M = N)
Beran, Rudolf
1994-01-01
This essay is organized around the theoretical and computationalproblem of constructing bootstrap confidence sets, with forays into relatedtopics. The seven section headings are: Introduction; The Bootstrap World;Bootstrap Confidence Sets; Computing Bootstrap Confidence Sets; Quality ofBootstrap Confidence Sets; Iterated and Two-step Boostrap; Further Resources.
A Score Based Approach to Wild Bootstrap Inference
Patrick M. Kline; Andres Santos
2010-01-01
We propose a generalization of the wild bootstrap of Wu (1986) and Liu (1988) based upon perturbing the scores of M-estimators. This "score bootstrap" procedure avoids recomputing the estimator in each bootstrap iteration, making it substantially less costly to compute than the conventional nonparametric bootstrap, particularly in complex nonlinear models. Despite this computational advantage, in the linear model, the score bootstrap studentized test statistic is equivalent to that of the con...
Nonparametric confidence intervals based on extreme bootstrap percentiles
Lee, SMS
2000-01-01
Monte Carlo approximation of standard bootstrap confidence intervals relies on the drawing of a large number, B say, of bootstrap resamples. Conventional choice of B is often made on the order of 1,000. While this choice may prove to be more than sufficient for some cases, it may be far from adequate for others. A new approach is suggested to construct confidence intervals based on extreme bootstrap percentiles and an adaptive choice of B. It economizes on the computational effort in a proble...
Improving the Reliability of Bootstrap Tests with the Fast Double Bootstrap
Davidson, Russell; MacKinnon, James
2006-01-01
Two procedures are proposed for estimating the rejection probabilities of bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication. These procedures are only about twice as expensive (per replication) as estimating rejection probabilities for asymptotic tests. Then a new procedure is proposed for computing bootstrap P values that will often be more accurate than ordinary ones. This “fast double bootstrap” is closely related to the double boot...
Efficient bootstrap with weakly dependent processes
Francesco Bravo; Federico Crudu
2012-01-01
The efficient bootstrap methodology is developed for overidentified moment conditions models with weakly dependent observation. The resulting bootstrap procedure is shown to be asymptotically valid and can be used to approximate the distributions of t-statistics, J statistic for overidentifying restrictions, and Wald, Lagrange multiplier and distance statistics for nonlinear hypotheses. The asymptotic validity of the efficient bootstrap based on a computationally less demanding approximate k-...
The wild bootstrap for multilevel models
Modugno, Lucia; Giannerini, Simone
2015-01-01
In this paper we study the performance of the most popular bootstrap schemes for multilevel data. Also, we propose a modified version of the wild bootstrap procedure for hierarchical data structures. The wild bootstrap does not require homoscedasticity or assumptions on the distribution of the error processes. Hence, it is a valuable tool for robust inference in a multilevel framework. We assess the finite size performances of the schemes through a Monte Carlo study. The results show that for...
Kim, Jae-In; Kim, Taejung
2016-01-01
Epipolar resampling is the procedure of eliminating vertical disparity between stereo images. Due to its importance, many methods have been developed in the computer vision and photogrammetry field. However, we argue that epipolar resampling of image sequences, instead of a single pair, has not been studied thoroughly. In this paper, we compare epipolar resampling methods developed in both fields for handling image sequences. Firstly we briefly review the uncalibrated and calibrated epipolar resampling methods developed in computer vision and photogrammetric epipolar resampling methods. While it is well known that epipolar resampling methods developed in computer vision and in photogrammetry are mathematically identical, we also point out differences in parameter estimation between them. Secondly, we tested representative resampling methods in both fields and performed an analysis. We showed that for epipolar resampling of a single image pair all uncalibrated and photogrammetric methods tested could be used. More importantly, we also showed that, for image sequences, all methods tested, except the photogrammetric Bayesian method, showed significant variations in epipolar resampling performance. Our results indicate that the Bayesian method is favorable for epipolar resampling of image sequences. PMID:27011186
Investigations of dipole localization accuracy in MEG using the bootstrap.
Darvas, F; Rautiainen, M; Pantazis, D; Baillet, S; Benali, H; Mosher, J C; Garnero, L; Leahy, R M
2005-04-01
We describe the use of the nonparametric bootstrap to investigate the accuracy of current dipole localization from magnetoencephalography (MEG) studies of event-related neural activity. The bootstrap is well suited to the analysis of event-related MEG data since the experiments are repeated tens or even hundreds of times and averaged to achieve acceptable signal-to-noise ratios (SNRs). The set of repetitions or epochs can be viewed as a set of independent realizations of the brain's response to the experiment. Bootstrap resamples can be generated by sampling with replacement from these epochs and averaging. In this study, we applied the bootstrap resampling technique to MEG data from somatotopic experimental and simulated data. Four fingers of the right and left hand of a healthy subject were electrically stimulated, and about 400 trials per stimulation were recorded and averaged in order to measure the somatotopic mapping of the fingers in the S1 area of the brain. Based on single-trial recordings for each finger we performed 5000 bootstrap resamples. We reconstructed dipoles from these resampled averages using the Recursively Applied and Projected (RAP)-MUSIC source localization algorithm. We also performed a simulation for two dipolar sources with overlapping time courses embedded in realistic background brain activity generated using the prestimulus segments of the somatotopic data. To find correspondences between multiple sources in each bootstrap, sample dipoles with similar time series and forward fields were assumed to represent the same source. These dipoles were then clustered by a Gaussian Mixture Model (GMM) clustering algorithm using their combined normalized time series and topographies as feature vectors. The mean and standard deviation of the dipole position and the dipole time series in each cluster were computed to provide estimates of the accuracy of the reconstructed source locations and time series. PMID:15784414
On Resampling Algorithms for Particle Filters
Hol, Jeroen; Schön, Thomas; Gustafsson, Fredrik
2007-01-01
In this paper a comparison is made between four frequently encountered resampling algorithms for particle filters. A theoretical framework is introduced to be able to understand and explain the differences between the resampling algorithms. This facilitates a comparison of the algorithms with respect to their resampling quality and computational complexity.Using extensive Monte Carlo simulations the theoretical results are verified. It is found that systematic resampling is favourable, both i...
Magno, Alexandre
2013-01-01
A practical, step-by-step tutorial on developing websites for mobile using Bootstrap.This book is for anyone who wants to get acquainted with the new features available in Bootstrap 3 and who wants to develop websites with the mobile-first feature of Bootstrap. The reader should have a basic knowledge of Bootstrap as a frontend framework.
The Finite Population Bootstrap - From the Maximum Likelihood to the Horvitz-Thompson Approach
Directory of Open Access Journals (Sweden)
Andreas Quatember
2014-06-01
Full Text Available The finite population bootstrap method is used as a computer-intensive alternative to estimate the sampling distribution of a sample statis-tic. The generation of a so-called “bootstrap population” is the necessarystep between the original sample drawn and the resamples needed to mimicthis distribution. The most important question for researchers to answer ishow to create an adequate bootstrap population, which may serve as a close-to-reality basis for the resampling process. In this paper, a review of someapproaches to answer this fundamental question is presented. Moreover, anapproach based on the idea behind the Horvitz-Thompson estimator allow-ing not only whole units in the bootstrap population but also parts of wholeunits is proposed. In a simulation study, this method is compared with a moreheuristic technique from the bootstrap literature.
Bootstrap inference in econometrics
James G. MacKinnon
2002-01-01
The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas of bootstrap inference. I discuss Monte Carlo tests, several types of bootstrap test, and bootstrap confidence intervals. Although bootstrapping often works well, it does not do so in every case.
Efficient bootstrap with weakly dependent processes
Bravo, Francesco; Crudu, Federico
2012-01-01
The efficient bootstrap methodology is developed for overidentified moment conditions models with weakly dependent observation. The resulting bootstrap procedure is shown to be asymptotically valid and can be used to approximate the distributions of t-statistics, the J-statistic for overidentifying
Polyphase antialiasing in resampling of images.
Seidner, Daniel
2005-11-01
Changing resolution of images is a common operation. It is also common to use simple, i.e., small, interpolation kernels satisfying some "smoothness" qualities that are determined in the spatial domain. Typical applications use linear interpolation or piecewise cubic interpolation. These are popular since the interpolation kernels are small and the results are acceptable. However, since the interpolation kernel, i.e., impulse response, has a finite and small length, the frequency domain characteristics are not good. Therefore, when we enlarge the image by a rational factor of (L/M), two effects usually appear and cause a noticeable degradation in the quality of the image. The first is jagged edges and the second is low-frequency modulation of high-frequency components, such as sampling noise. Both effects result from aliasing. Enlarging an image by a factor of (L/M) is represented by first interpolating the image on a grid L times finer than the original sampling grid, and then resampling it every M grid points. While the usual treatment of the aliasing created by the resampling operation is aimed toward improving the interpolation filter in the frequency domain, this paper suggests reducing the aliasing effects using a polyphase representation of the interpolation process and treating the polyphase filters separately. The suggested procedure is simple. A considerable reduction in the aliasing effects is obtained for a small interpolation kernel size. We discuss separable interpolation and so the analysis is conducted for the one-dimensional case. PMID:16279186
Evaluating Neural Network Predictors by Bootstrapping
Blake LeBaron; Andreas S. Weigend
1994-01-01
We present a new method, inspired by the bootstrap, whose goal it is to determine the quality and reliability of a neural network predictor. Our method leads to more robust forecasting along with a large amount of statistical information on forecast performance that we exploit. We exhibit the method in the context of multi-variate time series prediction on financial data from the New York Stock Exchange. It turns out that the variation due to different resamplings (i.e., splits between traini...
Non-Parametric Data Dependent Bootstrap for Conditional Moment Model
Bruce E. Hansen
2000-01-01
A new non-parametric bootstrap is introduced for dependent data. The bootstrap is based on a weighted empirical-likelihood estimate of the one-step-ahead conditional distribution, imposing the conditional moment restrictions implied by the model. This is the first dependent-data bootstrap procedure which imposes conditional moment restrictions on a bootstrap distribution. The method can be applied to form confidence intervals and p-values from hypothesis tests in Generalized Method of Moments...
Shaar, R.; Ron, H.; Tauxe, L.; Kessel, R.; Agnon, A.
2011-12-01
constraints for the 'true' value. We introduce a new bootstrap procedure to calculate a 95% confidence interval of the result. We substantiate the new procedure by conducting two independent tests. The first uses synthetic re-melted slag produced under known field intensities - 3 SD samples and 4 non-SD samples. The second compares paleointensity determinations from archaeological slag samples of the same age - 34 SD samples and 10 non-SD samples. The two tests suggest that the bootstrap technique is an optimal approach for non-ideal dataset.
A Direct Bootstrap Method for Complex Sampling Designs From a Finite Population
Antal, Erika; Tillé, Yves
2016-01-01
In complex designs, classical bootstrap methods result in a biased variance estimator when the sampling design is not taken into account. Resampled units are usually rescaled or weighted in order to achieve unbiasedness in the linear case. In the present article, we propose novel resampling methods that may be directly applied to variance estimation. These methods consist of selecting subsamples under a completely different sampling scheme from that which generated the original sample, whic...
Chain ladder method: Bayesian bootstrap versus classical bootstrap
Peters, Gareth W.; Mario V. W\\"uthrich; Shevchenko, Pavel V.
2010-01-01
The intention of this paper is to estimate a Bayesian distribution-free chain ladder (DFCL) model using approximate Bayesian computation (ABC) methodology. We demonstrate how to estimate quantities of interest in claims reserving and compare the estimates to those obtained from classical and credibility approaches. In this context, a novel numerical procedure utilising Markov chain Monte Carlo (MCMC), ABC and a Bayesian bootstrap procedure was developed in a truly distribution-free setting. T...
Bootstrap Methods in Econometrics
MacKinnon, James G.
2006-01-01
There are many bootstrap methods that can be used for econometric analysis. In certain circumstances, such as regression models with independent and identically distributed error terms, appropriately chosen bootstrap methods generally work very well. However, there are many other cases, such as regression models with dependent errors, in which bootstrap methods do not always work well. This paper discusses a large number of bootstrap methods that can be useful in econometrics. Applications to...
Bootstrapping structured page segmentation
Ma, Huanfeng; Doermann, David S.
2003-01-01
In this paper, we present an approach to the bootstrap learning of a page segmentation model. The idea evolves from attempts to segment dictionaries that often have a consistent page structure, and is extended to the segmentation of more general structured documents. In cases of highly regular structure, the layout can be learned from examples of only a few pages. The system is first trained using a small number of samples, and a larger test set is processed based on the training result. After making corrections to a selected subset of the test set, these corrected samples are combined with the original training samples to generate bootstrap samples. The newly created samples are used to retrain the system, refine the learned features and resegment the test samples. This procedure is applied iteratively until the learned parameters are stable. Using this approach, we do not need to initially provide a large set of training samples. We have applied this segmentation to many structured documents such as dictionaries, phone books, spoken language transcripts, and obtained satisfying segmentation performance.
Approximate regenerative-block bootstrap for Markov chains: some simulation studies
Bertail, Patrice; Clémençon, Stéphan
2007-01-01
Abstract : In Bertail & Clémençon (2005a) a novel methodology for bootstrappinggeneral Harris Markov chains has been proposed, which crucially exploits their renewalproperties (when eventually extended via the Nummelin splitting technique) and has theoreticalproperties that surpass other existing methods within the Markovian framework(bmoving block bootstrap, sieve bootstrap etc...). This paper is devoted to discuss practicalissues related to the implementation of this specific resampling met...
Fixed-b Subsampling and Block Bootstrap: Improved Confidence Sets Based on P-value Calibration
Shao, Xiaofeng; Politis, Dimitris N.
2012-01-01
Subsampling and block-based bootstrap methods have been used in a wide range of inference problems for time series. To accommodate the dependence, these resampling methods involve a bandwidth parameter, such as subsampling window width and block size in the block-based bootstrap. In empirical work, using different bandwidth parameters could lead to different inference results, but the traditional first order asymptotic theory does not capture the choice of the bandwidth. In this article, we p...
Iterated smoothed bootstrap confidence intervals for population quantiles
Lee, SMS; Ho, YHS
2005-01-01
This paper investigates the effects of smoothed bootstrap iterations on coverage probabilities of smoothed bootstrap and bootstrap-t confidence intervals for population quantiles, and establishes the optimal kernel bandwidths at various stages of the smoothing procedures. The conventional smoothed bootstrap and bootstrap-t methods have been known to yield one-sided coverage errors of orders O(n−1/2) and o(n−2/3), respectively, for intervals based on the sample quantile of a random sample of s...
A Resampling Based Clustering Algorithm for Replicated Gene Expression Data.
Li, Han; Li, Chun; Hu, Jie; Fan, Xiaodan
2015-01-01
In gene expression data analysis, clustering is a fruitful exploratory technique to reveal the underlying molecular mechanism by identifying groups of co-expressed genes. To reduce the noise, usually multiple experimental replicates are performed. An integrative analysis of the full replicate data, instead of reducing the data to the mean profile, carries the promise of yielding more precise and robust clusters. In this paper, we propose a novel resampling based clustering algorithm for genes with replicated expression measurements. Assuming those replicates are exchangeable, we formulate the problem in the bootstrap framework, and aim to infer the consensus clustering based on the bootstrap samples of replicates. In our approach, we adopt the mixed effect model to accommodate the heterogeneous variances and implement a quasi-MCMC algorithm to conduct statistical inference. Experiments demonstrate that by taking advantage of the full replicate data, our algorithm produces more reliable clusters and has robust performance in diverse scenarios, especially when the data is subject to multiple sources of variance. PMID:26671802
Change-point in stochastic design regression and the bootstrap
Seijo, Emilio; Sen, Bodhisattva
2011-01-01
In this paper we study the consistency of different bootstrap procedures for constructing confidence intervals (CIs) for the unique jump discontinuity (change-point) in an otherwise smooth regression function in a stochastic design setting. This problem exhibits nonstandard asymptotics and we argue that the standard bootstrap procedures in regression fail to provide valid confidence intervals for the change-point. We propose a version of smoothed bootstrap, illustrate its remarkable finite sa...
Rubin, Donald B.
1981-01-01
The Bayesian bootstrap is the Bayesian analogue of the bootstrap. Instead of simulating the sampling distribution of a statistic estimating a parameter, the Bayesian bootstrap simulates the posterior distribution of the parameter; operationally and inferentially the methods are quite similar. Because both methods of drawing inferences are based on somewhat peculiar model assumptions and the resulting inferences are generally sensitive to these assumptions, neither method should be applied wit...
Nonparametric bootstrap prediction
Fushiki, Tadayoshi; Komaki, Fumiyasu; Aihara, Kazuyuki
2005-01-01
Ensemble learning has recently been intensively studied in the field of machine learning. `Bagging' is a method of ensemble learning and uses bootstrap data to construct various predictors. The required prediction is then obtained by averaging the predictors. Harris proposed using this technique with the parametric bootstrap predictive distribution to construct predictive distributions, and showed that the parametric bootstrap predictive distribution gives asymptotically better prediction tha...
Bootstrapping Macroeconometric Models
2001-01-01
This paper outlines a bootstrapping approach to the estimation and analysis of macroeconometric models. It integrates for dynamic, nonlinear, simultaneous equation models the bootstrapping approach to evaluating estimators initiated by Efron (1979) and the stochastic simulation approach to evaluating models' properties initiated by Adelman and Adelman (1959). It also estimates for a particular model the gain in coverage accuracy from using bootstrap confidence intervals over asymptotic confid...
Assessing Uncertainties in Surface Water Security: A Probabilistic Multi-model Resampling approach
Rodrigues, D. B. B.
2015-12-01
Various uncertainties are involved in the representation of processes that characterize interactions between societal needs, ecosystem functioning, and hydrological conditions. Here, we develop an empirical uncertainty assessment of water security indicators that characterize scarcity and vulnerability, based on a multi-model and resampling framework. We consider several uncertainty sources including those related to: i) observed streamflow data; ii) hydrological model structure; iii) residual analysis; iv) the definition of Environmental Flow Requirement method; v) the definition of critical conditions for water provision; and vi) the critical demand imposed by human activities. We estimate the overall uncertainty coming from the hydrological model by means of a residual bootstrap resampling approach, and by uncertainty propagation through different methodological arrangements applied to a 291 km² agricultural basin within the Cantareira water supply system in Brazil. Together, the two-component hydrograph residual analysis and the block bootstrap resampling approach result in a more accurate and precise estimate of the uncertainty (95% confidence intervals) in the simulated time series. We then compare the uncertainty estimates associated with water security indicators using a multi-model framework and provided by each model uncertainty estimation approach. The method is general and can be easily extended forming the basis for meaningful support to end-users facing water resource challenges by enabling them to incorporate a viable uncertainty analysis into a robust decision making process.
A comparison of four different block bootstrap methods
Directory of Open Access Journals (Sweden)
Boris Radovanov
2014-12-01
Full Text Available The paper contains a description of four different block bootstrap methods, i.e., non-overlapping block bootstrap, overlapping block bootstrap (moving block bootstrap, stationary block bootstrap and subsampling. Furthermore, the basic goal of this paper is to quantify relative efficiency of each mentioned block bootstrap procedure and then to compare those methods. To achieve the goal, we measure mean square errors of estimation variance returns. The returns are calculated from 1250 daily observations of Serbian stock market index values BELEX15 from April 2009 to April 2014. Thereby, considering the effects of potential changes in decisions according to variations in the sample length and purposes of the use, this paper introduces stability analysis which contains robustness testing of the different sample size and the different block length. Testing results indicate some changes in bootstrap method efficiencies when altering the sample size or the block length.
Jongjoo, Kim; Davis, Scott K; Taylor, Jeremy F
2002-06-01
Empirical confidence intervals (CIs) for the estimated quantitative trait locus (QTL) location from selective and non-selective non-parametric bootstrap resampling methods were compared for a genome scan involving an Angus x Brahman reciprocal fullsib backcross population. Genetic maps, based on 357 microsatellite markers, were constructed for 29 chromosomes using CRI-MAP V2.4. Twelve growth, carcass composition and beef quality traits (n = 527-602) were analysed to detect QTLs utilizing (composite) interval mapping approaches. CIs were investigated for 28 likelihood ratio test statistic (LRT) profiles for the one QTL per chromosome model. The CIs from the non-selective bootstrap method were largest (87 7 cM average or 79-2% coverage of test chromosomes). The Selective II procedure produced the smallest CI size (42.3 cM average). However, CI sizes from the Selective II procedure were more variable than those produced by the two LOD drop method. CI ranges from the Selective II procedure were also asymmetrical (relative to the most likely QTL position) due to the bias caused by the tendency for the estimated QTL position to be at a marker position in the bootstrap samples and due to monotonicity and asymmetry of the LRT curve in the original sample. PMID:12220133
Change-point in stochastic design regression and the bootstrap
Seijo, Emilio
2011-01-01
In this paper we study the consistency of different bootstrap procedures for constructing confidence intervals (CIs) for the unique jump discontinuity (change-point) in an otherwise smooth regression function in a stochastic design setting. This problem exhibits nonstandard asymptotics and we argue that the standard bootstrap procedures in regression fail to provide valid confidence intervals for the change-point. We propose a version of smoothed bootstrap, illustrate its remarkable finite sample performance in our simulation study, and prove the consistency of the procedure. The $m$ out of $n$ bootstrap procedure is also considered and shown to be consistent. We also provide sufficient conditions for any bootstrap procedure to be consistent in this scenario.
Tiwari, Mukesh K.; Adamowski, Jan
2013-10-01
A new hybrid wavelet-bootstrap-neural network (WBNN) model is proposed in this study for short term (1, 3, and 5 day; 1 and 2 week; and 1 and 2 month) urban water demand forecasting. The new method was tested using data from the city of Montreal in Canada. The performance of the WBNN method was compared with the autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average model with exogenous input variables (ARIMAX), traditional NNs, wavelet analysis-based NNs (WNN), bootstrap-based NNs (BNN), and a simple naïve persistence index model. The WBNN model was developed as an ensemble of several NNs built using bootstrap resamples of wavelet subtime series instead of raw data sets. The results demonstrated that the hybrid WBNN and WNN models produced significantly more accurate forecasting results than the traditional NN, BNN, ARIMA, and ARIMAX models. It was also found that the WBNN model reduces the uncertainty associated with the forecasts, and the performance of WBNN forecasted confidence bands was found to be more accurate and reliable than BNN forecasted confidence bands. It was found in this study that maximum temperature and total precipitation improved the accuracy of water demand forecasts using wavelet analysis. The performance of WBNN models was also compared for different numbers of bootstrap resamples (i.e., 25, 50, 100, 200, and 500) and it was found that WBNN models produced optimum results with different numbers of bootstrap resamples for different lead time forecasts with considerable variability.
Model Based Bootstrap Methods for Interval Censored Data
Sen, Bodhisattva; Xu, Gongjun
2013-01-01
We investigate the performance of model based bootstrap methods for constructing point-wise confidence intervals around the survival function with interval censored data. We show that bootstrapping from the nonparametric maximum likelihood estimator of the survival function is inconsistent for both the current status and case 2 interval censoring models. A model based smoothed bootstrap procedure is proposed and shown to be consistent. In addition, simulation studies are conducted to illustra...
Sahiner, Berkman; Chan, Heang-Ping; Hadjiiski, Lubomir
2008-01-01
In a practical classifier design problem the sample size is limited, and the available finite sample needs to be used both to design a classifier and to predict the classifier's performance for the true population. Since a larger sample is more representative of the population, it is advantageous to design the classifier with all the available cases, and to use a resampling technique for performance prediction. We conducted a Monte Carlo simulation study to compare the ability of different resampling techniques in predicting the performance of a neural network (NN) classifier designed with the available sample. We used the area under the receiver operating characteristic curve as the performance index for the NN classifier. We investigated resampling techniques based on the cross-validation, the leave-one-out method, and three different types of bootstrapping, namely, the ordinary, .632, and .632+ bootstrap. Our results indicated that, under the study conditions, there can be a large difference in the accuracy of the prediction obtained from different resampling methods, especially when the feature space dimensionality is relatively large and the sample size is small. Although this investigation is performed under some specific conditions, it reveals important trends for the problem of classifier performance prediction under the constraint of a limited data set. PMID:18234468
Simulation-Optimization via Kriging and Bootstrapping: A Survey (Revision of CentER DP 2011-064)
Kleijnen, Jack P.C.
2013-01-01
Abstract: This article surveys optimization of simulated systems. The simulation may be either deterministic or random. The survey reflects the author’s extensive experience with simulation-optimization through Kriging (or Gaussian process) metamodels. The analysis of these metamodels may use parametric bootstrapping for deterministic simulation or distribution-free bootstrapping (or resampling) for random simulation. The survey covers: (1) Simulation-optimization through "efficient global op...
Bootstrapping phylogenies inferred from rearrangement data
Directory of Open Access Journals (Sweden)
Lin Yu
2012-08-01
Full Text Available Abstract Background Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date. The standard method used in sequence-based phylogenetic inference is the bootstrap, but it relies on a large number of homologous characters that can be resampled; yet in the case of rearrangements, the entire genome is a single character. Alternatives such as the jackknife suffer from the same problem, while likelihood tests cannot be applied in the absence of well established probabilistic models. Results We present a new approach to the assessment of distance-based phylogenetic inference from whole-genome data; our approach combines features of the jackknife and the bootstrap and remains nonparametric. For each feature of our method, we give an equivalent feature in the sequence-based framework; we also present the results of extensive experimental testing, in both sequence-based and genome-based frameworks. Through the feature-by-feature comparison and the experimental results, we show that our bootstrapping approach is on par with the classic phylogenetic bootstrap used in sequence-based reconstruction, and we establish the clear superiority of the classic bootstrap for sequence data and of our corresponding new approach for rearrangement data over proposed variants. Finally, we test our approach on a small dataset of mammalian genomes, verifying that the support values match current thinking about the respective branches. Conclusions Our method is the first to provide a standard of assessment to match that of the classic phylogenetic bootstrap for aligned sequences. Its
Fourier transform resampling: Theory and application
International Nuclear Information System (INIS)
One of the most challenging problems in medical imaging is the development of reconstruction algorithms for nonstandard geometries. This work focuses on the application of Fourier analysis to the problem of resampling or rebinning. Conventional resampling methods utilizing some form of interpolation almost always result in a loss of resolution in the tomographic image. Fourier Transform Resampling (FTRS) offers potential improvement because the Modulation Transfer Function (MTF) of the process behaves like an ideal low pass filter. The MTF, however, is nonstationary if the coordinate transformation is nonlinear. FTRS may be viewed as a generalization of the linear coordinate transformations of standard Fourier analysis. Simulated MTF's were obtained by projecting point sources at different transverse positions in the flat fan beam detector geometry. These MTF's were compared to the closed form expression for FIRS. Excellent agreement was obtained for frequencies at or below the estimated cutoff frequency. The resulting FTRS algorithm is applied to simulations with symmetric fan beam geometry, an elliptical orbit and uniform attenuation, with a normalized root mean square error (NRME) of 0.036. Also, a Tc-99m point source study (1 cm dia., placed in air 10 cm from the COR) for a circular fan beam acquisition was reconstructed with a hybrid resampling method. The FWHM of the hybrid resampling method was 11.28 mm and compares favorably with a direct reconstruction (FWHM: 11.03 mm)
Echeverri, Alejandro Castedo; Serone, Marco
2016-01-01
We study the numerical bounds obtained using a conformal-bootstrap method - advocated in ref. [1] but never implemented so far - where different points in the plane of conformal cross ratios $z$ and $\\bar z$ are sampled. In contrast to the most used method based on derivatives evaluated at the symmetric point $z=\\bar z =1/2$, we can consistently "integrate out" higher-dimensional operators and get a reduced simpler, and faster to solve, set of bootstrap equations. We test this "effective" bootstrap by studying the 3D Ising and $O(n)$ vector models and bounds on generic 4D CFTs, for which extensive results are already available in the literature. We also determine the scaling dimensions of certain scalar operators in the $O(n)$ vector models, with $n=2,3,4$, which have not yet been computed using bootstrap techniques.
Dynamics of bootstrap percolation
Indian Academy of Sciences (India)
Prabodh Shukla
2008-08-01
Bootstrap percolation transition may be first order or second order, or it may have a mixed character where a first-order drop in the order parameter is preceded by critical fluctuations. Recent studies have indicated that the mixed transition is characterized by power-law avalanches, while the continuous transition is characterized by truncated avalanches in a related sequential bootstrap process. We explain this behaviour on the basis of an analytical and numerical study of the avalanche distributions on a Bethe lattice.
Bootstrap percolation with inhibition
Einarsson, Hafsteinn; Lengler, Johannes; Panagiotou, Konstantinos; Mousset, Frank; Steger, Angelika
2014-01-01
Bootstrap percolation is a prominent framework for studying the spreading of activity on a graph. We begin with an initial set of active vertices. The process then proceeds in rounds, and further vertices become active as soon as they have a certain number of active neighbors. A recurring feature in bootstrap percolation theory is an `all-or-nothing' phenomenon: either the size of the starting set is so small that the process stops very soon, or it percolates (almost) completely. Motivated by...
A bootstrap estimation scheme for chemical compositional data with nondetects
Palarea-Albaladejo, J; Martín-Fernández, J.A; Olea, Ricardo A.
2014-01-01
The bootstrap method is commonly used to estimate the distribution of estimators and their associated uncertainty when explicit analytic expressions are not available or are difficult to obtain. It has been widely applied in environmental and geochemical studies, where the data generated often represent parts of whole, typically chemical concentrations. This kind of constrained data is generically called compositional data, and they require specialised statistical methods to properly account for their particular covariance structure. On the other hand, it is not unusual in practice that those data contain labels denoting nondetects, that is, concentrations falling below detection limits. Nondetects impede the implementation of the bootstrap and represent an additional source of uncertainty that must be taken into account. In this work, a bootstrap scheme is devised that handles nondetects by adding an imputation step within the resampling process and conveniently propagates their associated uncertainly. In doing so, it considers the constrained relationships between chemical concentrations originated from their compositional nature. Bootstrap estimates using a range of imputation methods, including new stochastic proposals, are compared across scenarios of increasing difficulty. They are formulated to meet compositional principles following the log-ratio approach, and an adjustment is introduced in the multivariate case to deal with nonclosed samples. Results suggest that nondetect bootstrap based on model-based imputation is generally preferable. A robust approach based on isometric log-ratio transformations appears to be particularly suited in this context. Computer routines in the R statistical programming language are provided.
Wild cluster bootstrap confidence intervals
MacKinnon, James G.
2014-01-01
Confidence intervals based on cluster-robust covariance matrices can be constructed in many ways. In addition to conventional intervals obtained by inverting Wald (t) tests, the paper studies intervals obtained by inverting LM tests, studentized bootstrap intervals based on the wild cluster bootstrap, and restricted bootstrap intervals obtained by inverting bootstrap Wald and LM tests. It also studies the choice of an auxiliary distribution for the wild bootstrap, a modified covariance matrix...
Breakdown theory for bootstrap quantiles
Singh, Kesar
1998-01-01
A general formula for computing the breakdown point in robustness for the $t$th bootstrap quantile of a statistic $T_n$ is obtained. The answer depends on $t$ and the breakdown point of $T_n$. Since the bootstrap quantiles are vital ingredients of bootstrap confidence intervals, the theory has implications pertaining to robustness of bootstrap confidence intervals. For certain $L$ and $M$ estimators, a robustification of bootstrap is suggested via the notion of Winsorization.
Quantitative evaluation of PET image using event information bootstrap
Song, Hankyeol; Kwak, Shin Hye; Kim, Kyeong Min; Kang, Joo Hyun; Chung, Yong Hyun; Woo, Sang-Keun
2016-04-01
The purpose of this study was to enhance the effect in the PET image quality according to event bootstrap of small animal PET data. In order to investigate the time difference condition, realigned sinograms were generated from randomly sampled data set using bootstrap. List-mode data was obtained from small animal PET scanner for Ge-68 30 sec, Y-90 20 min and Y-90 60 min. PET image was reconstructed by Ordered Subset Expectation Maximization(OSEM) 2D with the list-mode format. Image analysis was investigated by Signal to Noise Ratio(SNR) of Ge-68 and Y-90 image. Non-parametric resampled PET image SNR percent change for the Ge-68 30 sec, Y-90 60 min, and Y-90 20 min was 1.69 %, 7.03 %, and 4.78 %, respectively. SNR percent change of non-parametric resampled PET image with time difference condition was 1.08 % for the Ge-68 30 sec, 6.74 % for the Y-90 60 min and 10.94 % for the Y-90 29 min. The result indicated that the bootstrap with time difference condition had a potential to improve a noisy Y-90 PET image quality. This method should be expected to reduce Y-90 PET measurement time and to enhance its accuracy.
Quilty, John; Adamowski, Jan; Khalil, Bahaa; Rathinasamy, Maheswaran
2016-03-01
The input variable selection problem has recently garnered much interest in the time series modeling community, especially within water resources applications, demonstrating that information theoretic (nonlinear)-based input variable selection algorithms such as partial mutual information (PMI) selection (PMIS) provide an improved representation of the modeled process when compared to linear alternatives such as partial correlation input selection (PCIS). PMIS is a popular algorithm for water resources modeling problems considering nonlinear input variable selection; however, this method requires the specification of two nonlinear regression models, each with parametric settings that greatly influence the selected input variables. Other attempts to develop input variable selection methods using conditional mutual information (CMI) (an analog to PMI) have been formulated under different parametric pretenses such as k nearest-neighbor (KNN) statistics or kernel density estimates (KDE). In this paper, we introduce a new input variable selection method based on CMI that uses a nonparametric multivariate continuous probability estimator based on Edgeworth approximations (EA). We improve the EA method by considering the uncertainty in the input variable selection procedure by introducing a bootstrap resampling procedure that uses rank statistics to order the selected input sets; we name our proposed method bootstrap rank-ordered CMI (broCMI). We demonstrate the superior performance of broCMI when compared to CMI-based alternatives (EA, KDE, and KNN), PMIS, and PCIS input variable selection algorithms on a set of seven synthetic test problems and a real-world urban water demand (UWD) forecasting experiment in Ottawa, Canada.
On the Bootstrap of $U$ and $V$ Statistics
Arcones, Miguel A.; Gine, Evarist
1992-01-01
Bootstrap distributional limit theorems for $U$ and $V$ statistics are proved. They hold a.s., under weak moment conditions and without restrictions on the bootstrap sample size (as long as it tends to $\\infty$), regardless of the degree of degeneracy of $U$ and $V$. A testing procedure based on these results is outlined.
Using Commonly Available Software for Conducting Bootstrap Analyses.
Fan, Xitao
Bootstrap analysis, both for nonparametric statistical inference and for describing sample results stability and replicability, has been gaining prominence among quantitative researchers in educational and psychological research. Procedurally, however, it is often quite a challenge for quantitative researchers to implement bootstrap analysis in…
Bootstrap position analysis for forecasting low flow frequency
Tasker, Gary D.; Dunne, P.
1997-01-01
A method of random resampling of residuals from stochastic models is used to generate a large number of 12-month-long traces of natural monthly runoff to be used in a position analysis model for a water-supply storage and delivery system. Position analysis uses the traces to forecast the likelihood of specified outcomes such as reservoir levels falling below a specified level or streamflows falling below statutory passing flows conditioned on the current reservoir levels and streamflows. The advantages of this resampling scheme, called bootstrap position analysis, are that it does not rely on the unverifiable assumption of normality, fewer parameters need to be estimated directly from the data, and accounting for parameter uncertainty is easily done. For a given set of operating rules and water-use requirements for a system, water managers can use such a model as a decision-making tool to evaluate different operating rules. ?? ASCE,.
An approximate analytical approach to resampling averages
DEFF Research Database (Denmark)
Malzahn, Dorthe; Opper, M.
2004-01-01
Using a novel reformulation, we develop a framework to compute approximate resampling data averages analytically. The method avoids multiple retraining of statistical models on the samples. Our approach uses a combination of the replica "trick" of statistical physics and the TAP approach for appr...
An approximate analytical approach to resampling averages
DEFF Research Database (Denmark)
Malzahn, Dorthe; Opper, M.
2004-01-01
Using a novel reformulation, we develop a framework to compute approximate resampling data averages analytically. The method avoids multiple retraining of statistical models on the samples. Our approach uses a combination of the replica "trick" of statistical physics and the TAP approach for...
Bootstrapping Density-Weighted Average Derivatives
DEFF Research Database (Denmark)
Cattaneo, Matias D.; Crump, Richard K.; Jansson, Michael
Employing the "small bandwidth" asymptotic framework of Cattaneo, Crump, and Jansson (2009), this paper studies the properties of a variety of bootstrap-based inference procedures associated with the kernel-based density-weighted averaged derivative estimator proposed by Powell, Stock, and Stoker...
Bootstrapped models for intrinsic random functions
Energy Technology Data Exchange (ETDEWEB)
Campbell, K.
1988-08-01
Use of intrinsic random function stochastic models as a basis for estimation in geostatistical work requires the identification of the generalized covariance function of the underlying process. The fact that this function has to be estimated from data introduces an additional source of error into predictions based on the model. This paper develops the sample reuse procedure called the bootstrap in the context of intrinsic random functions to obtain realistic estimates of these errors. Simulation results support the conclusion that bootstrap distributions of functionals of the process, as well as their kriging variance, provide a reasonable picture of variability introduced by imperfect estimation of the generalized covariance function.
Rejon-Barrera, Fernando; Robbins, Daniel
2016-01-01
We work out all of the details required for implementation of the conformal bootstrap program applied to the four-point function of two scalars and two vectors in an abstract conformal field theory in arbitrary dimension. This includes a review of which tensor structures make appearances, a construction of the projectors onto the required mixed symmetry representations, and a computation of the conformal blocks for all possible operators which can be exchanged. These blocks are presented as differential operators acting upon the previously known scalar conformal blocks. Finally, we set up the bootstrap equations which implement crossing symmetry. Special attention is given to the case of conserved vectors, where several simplifications occur.
Introduction to the Bootstrap World
Boos, Dennis D.
2003-01-01
The bootstrap has made a fundamental impact on how we carry out statistical inference in problems without analytic solutions. This fact is illustrated with examples and comments that emphasize the parametric bootstrap and hypothesis testing.
Generalized Bootstrap Method for Assessment of Uncertainty in Semivariogram Inference
Olea, R.A.; Pardo-Iguzquiza, E.
2011-01-01
The semivariogram and its related function, the covariance, play a central role in classical geostatistics for modeling the average continuity of spatially correlated attributes. Whereas all methods are formulated in terms of the true semivariogram, in practice what can be used are estimated semivariograms and models based on samples. A generalized form of the bootstrap method to properly model spatially correlated data is used to advance knowledge about the reliability of empirical semivariograms and semivariogram models based on a single sample. Among several methods available to generate spatially correlated resamples, we selected a method based on the LU decomposition and used several examples to illustrate the approach. The first one is a synthetic, isotropic, exhaustive sample following a normal distribution, the second example is also a synthetic but following a non-Gaussian random field, and a third empirical sample consists of actual raingauge measurements. Results show wider confidence intervals than those found previously by others with inadequate application of the bootstrap. Also, even for the Gaussian example, distributions for estimated semivariogram values and model parameters are positively skewed. In this sense, bootstrap percentile confidence intervals, which are not centered around the empirical semivariogram and do not require distributional assumptions for its construction, provide an achieved coverage similar to the nominal coverage. The latter cannot be achieved by symmetrical confidence intervals based on the standard error, regardless if the standard error is estimated from a parametric equation or from bootstrap. ?? 2010 International Association for Mathematical Geosciences.
Poland, David; Simmons-Duffin, David
2016-06-01
The conformal bootstrap was proposed in the 1970s as a strategy for calculating the properties of second-order phase transitions. After spectacular success elucidating two-dimensional systems, little progress was made on systems in higher dimensions until a recent renaissance beginning in 2008. We report on some of the main results and ideas from this renaissance, focusing on new determinations of critical exponents and correlation functions in the three-dimensional Ising and O(N) models.
International Nuclear Information System (INIS)
Sensitivity analysis aims at quantifying influence of input parameters dispersion on the output dispersion of a numerical model. When the model evaluation is time consuming, the computation of Sobol' indices based on Monte Carlo method is not applicable and a surrogate model has to be used. Among all approximation methods, polynomial chaos expansion is one of the most efficient to calculate variance-based sensitivity indices. Indeed, their computation is analytically derived from the expansion coefficients but without error estimators of the meta-model approximation. In order to evaluate the reliability of these indices, we propose to build confidence intervals by bootstrap re-sampling on the experimental design used to estimate the polynomial chaos approximation. Since the evaluation of the sensitivity indices is obtained with confidence intervals, it is possible to find a design of experiments allowing the computation of sensitivity indices with a given accuracy. - Highlights: • The proposed methodology combines advantages of sparse polynomial chaos expansion with bootstrap re-sampling to compute variance-based sensitivity indices. • A conservative way to choose the number of bootstrap re-sampling is presented. • A method to increase the degree of the polynomial basis, linked to the size of confidence intervals, is proposed. • Comparisons with classical meta-model error estimators reveals the interest of a sensitivity-indices-oriented methodology
Resampling Methods Improve the Predictive Power of Modeling in Class-Imbalanced Datasets
Directory of Open Access Journals (Sweden)
Paul H. Lee
2014-09-01
Full Text Available In the medical field, many outcome variables are dichotomized, and the two possible values of a dichotomized variable are referred to as classes. A dichotomized dataset is class-imbalanced if it consists mostly of one class, and performance of common classification models on this type of dataset tends to be suboptimal. To tackle such a problem, resampling methods, including oversampling and undersampling can be used. This paper aims at illustrating the effect of resampling methods using the National Health and Nutrition Examination Survey (NHANES wave 2009–2010 dataset. A total of 4677 participants aged ≥20 without self-reported diabetes and with valid blood test results were analyzed. The Classification and Regression Tree (CART procedure was used to build a classification model on undiagnosed diabetes. A participant demonstrated evidence of diabetes according to WHO diabetes criteria. Exposure variables included demographics and socio-economic status. CART models were fitted using a randomly selected 70% of the data (training dataset, and area under the receiver operating characteristic curve (AUC was computed using the remaining 30% of the sample for evaluation (testing dataset. CART models were fitted using the training dataset, the oversampled training dataset, the weighted training dataset, and the undersampled training dataset. In addition, resampling case-to-control ratio of 1:1, 1:2, and 1:4 were examined. Resampling methods on the performance of other extensions of CART (random forests and generalized boosted trees were also examined. CARTs fitted on the oversampled (AUC = 0.70 and undersampled training data (AUC = 0.74 yielded a better classification power than that on the training data (AUC = 0.65. Resampling could also improve the classification power of random forests and generalized boosted trees. To conclude, applying resampling methods in a class-imbalanced dataset improved the classification power of CART, random forests
Convex and Monotonic Bootstrapped Kriging
Kleijnen, Jack P.C.; Mehdad, E.; Beers, W.C.M. van
2012-01-01
Abstract: Distribution-free bootstrapping of the replicated responses of a given discreteevent simulation model gives bootstrapped Kriging (Gaussian process) metamodels; we require these metamodels to be either convex or monotonic. To illustrate monotonic Kriging, we use an M/M/1 queueing simulation with as output either the mean or the 90% quantile of the transient-state waiting times, and as input the traffic rate. In this example, monotonic bootstrapped Kriging enables better sensitivity a...
Bo E. Honoré; Hu, Luojia
2015-01-01
The bootstrap is a convenient tool for calculating standard errors of the parameters of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. The paper contains no new difficult math. But we believe that it can be useful.
Bootstrapping and Bartlett corrections in the cointegrated VAR model
Omtzigt, P.H.; Fachin, S.
2002-01-01
The small sample properties of tests on long-run coefficients in cointegrated systems are still a matter of concern to applied econometricians. We compare the performance of the Bartlett correction, the bootstrap and the fast double bootstrap for tests on ccointegration parameters in the maximum likelihood framework. We show by means of a theoretical result and simulations that all three procedures should be based on the unrestricted estimate of the cointegration vectors. The fast double boot...
Detrending bootstrap unit root tests
Smeekes, S.
2009-01-01
The role of detrending in bootstrap unit root tests is investigated. When bootstrapping, detrending must not only be done for the construction of the test statistic, but also in the first step of the bootstrap algorithm. It is argued that the two points should be treated separately. Asymptotic validity of sieve bootstrap ADF unit root tests is shown for test statistics based on full sample and recursive OLS and GLS detrending. It is also shown that the detrending method in the first step of t...
Chester, Shai M
2016-01-01
We initiate the conformal bootstrap study of Quantum Electrodynamics in $2+1$ space-time dimensions (QED$_{3}$) with $N$ flavors of charged fermions by focusing on the 4-point function of four monopole operators with the lowest unit of topological charge. We obtain upper bounds on the scaling dimension of the doubly-charged monopole operator, with and without assuming other gaps in the operator spectrum. Intriguingly, we find a (gap-dependent) kink in these bounds that comes reasonably close to the large $N$ extrapolation of the scaling dimensions of the singly-charged and doubly-charged monopole operators down to $N=4$ and $N=6$.
Iliesiu, Luca; Kos, Filip; Poland, David; Pufu, Silviu S.; Simmons-Duffin, David; Yacoby, Ran
2016-03-01
We study the conformal bootstrap for a 4-point function of fermions in 3D. We first introduce an embedding formalism for 3D spinors and compute the conformal blocks appearing in fermion 4-point functions. Using these results, we find general bounds on the dimensions of operators appearing in the ψ × ψ OPE, and also on the central charge C T . We observe features in our bounds that coincide with scaling dimensions in the GrossNeveu models at large N . We also speculate that other features could coincide with a fermionic CFT containing no relevant scalar operators.
Fixed-b Subsampling and Block Bootstrap: Improved Confidence Sets Based on P-value Calibration
Shao, Xiaofeng
2012-01-01
Subsampling and block-based bootstrap methods have been used in a wide range of inference problems for time series. To accommodate the dependence, these resampling methods involve a bandwidth parameter, such as subsampling window width and block size in the block-based bootstrap. In empirical work, using different bandwidth parameters could lead to different inference results, but the traditional first order asymptotic theory does not capture the choice of the bandwidth. In this article, we propose to adopt the fixed-b approach, as advocated by Kiefer and Vogelsang (2005) in the heteroscedasticity-autocorrelation robust testing context, to account for the influence of the bandwidth on the inference. Under the fixed-b asymptotic framework, we derive the asymptotic null distribution of the p-values for subsampling and the moving block bootstrap, and further propose a calibration of the traditional small-b based confidence intervals (regions, bands) and tests. Our treatment is fairly general as it includes both ...
Robust, Scalable, and Fast Bootstrap Method for Analyzing Large Scale Data
Basiri, Shahab; Ollila, Esa; Koivunen, Visa
2016-02-01
In this paper we address the problem of performing statistical inference for large scale data sets i.e., Big Data. The volume and dimensionality of the data may be so high that it cannot be processed or stored in a single computing node. We propose a scalable, statistically robust and computationally efficient bootstrap method, compatible with distributed processing and storage systems. Bootstrap resamples are constructed with smaller number of distinct data points on multiple disjoint subsets of data, similarly to the bag of little bootstrap method (BLB) [1]. Then significant savings in computation is achieved by avoiding the re-computation of the estimator for each bootstrap sample. Instead, a computationally efficient fixed-point estimation equation is analytically solved via a smart approximation following the Fast and Robust Bootstrap method (FRB) [2]. Our proposed bootstrap method facilitates the use of highly robust statistical methods in analyzing large scale data sets. The favorable statistical properties of the method are established analytically. Numerical examples demonstrate scalability, low complexity and robust statistical performance of the method in analyzing large data sets.
Balogh, József; Morris, Robert
2011-01-01
Graph bootstrap percolation is a deterministic cellular automaton which was introduced by Bollob\\'as in 1968, and is defined as follows. Given a graph $H$, and a set $G \\subset E(K_n)$ of initially `infected' edges, we infect, at each time step, a new edge $e$ if there is a copy of $H$ in $K_n$ such that $e$ is the only not-yet infected edge of $H$. We say that $G$ percolates in the $H$-bootstrap process if eventually every edge of $K_n$ is infected. The extremal questions for this model, when $H$ is the complete graph $K_r$, were solved (independently) by Alon, Kalai and Frankl almost thirty years ago. In this paper we study the random questions, and determine the critical probability $p_c(n,K_r)$ for the $K_r$-process up to a poly-logarithmic factor. In the case $r = 4$ we prove a stronger result, and determine the threshold for $p_c(n,K_4)$.
Breakdown Point Theory for Implied Probability Bootstrap
Lorenzo Camponovo; Taisuke Otsu
2011-01-01
This paper studies robustness of bootstrap inference methods under moment conditions. In particular, we compare the uniform weight and implied probability bootstraps by analyzing behaviors of the bootstrap quantiles when outliers take arbitrarily large values, and derive the breakdown points for those bootstrap quantiles. The breakdown point properties characterize the situation where the implied probability bootstrap is more robust than the uniform weight bootstrap against outliers. Simulati...
The bootstrap fraction in TFTR
International Nuclear Information System (INIS)
The TRANSP plasma analysis code is used to calculate the bootstrap current generated during neutral beam injection and ion cyclotron resonance frequency heating for a wide variety of TFTR discharges. An empirical scaling relation is given for the bootstrap current fraction using the ratio of the peakednesses of the thermal pressure and of the total current density. copyright 1997 American Institute of Physics
On sieve bootstrap prediction intervals.
Andrés M. Alonso; Peña, Daniel; Romo Urroz, Juan
2003-01-01
In this paper we consider a sieve bootstrap method for constructing nonparametric prediction intervals for a general class of linear processes. We show that the sieve bootstrap provides consistent estimators of the conditional distribution of future values given the observed data.
Ultrafast Approximation for Phylogenetic Bootstrap
Bui Quang Minh, [No Value; Nguyen, Thi; von Haeseler, Arndt
2013-01-01
Nonparametric bootstrap has been a widely used tool in phylogenetic analysis to assess the clade support of phylogenetic trees. However, with the rapidly growing amount of data, this task remains a computational bottleneck. Recently, approximation methods such as the RAxML rapid bootstrap (RBS) and
Explorations in Statistics: the Bootstrap
Curran-Everett, Douglas
2009-01-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This fourth installment of Explorations in Statistics explores the bootstrap. The bootstrap gives us an empirical approach to estimate the theoretical variability among possible values of a sample statistic such as the…
Second Thoughts on the Bootstrap
Efron, Bradley
2003-01-01
This brief review article is appearing in the issue of Statistical Science that marks the 25th anniversary of the bootstrap. It concerns some of the theoretical and methodological aspects of the bootstrap and how they might influence future work in statistics.
Bootstrapping pre-averaged realized volatility under market microstructure noise
DEFF Research Database (Denmark)
Hounyo, Ulrich; Goncalves, Sílvia; Meddahi, Nour
The main contribution of this paper is to propose a bootstrap method for inference on integrated volatility based on the pre-averaging approach of Jacod et al. (2009), where the pre-averaging is done over all possible overlapping blocks of consecutive observations. The overlapping nature of the pre......-averaged returns implies that these are kn-dependent with kn growing slowly with the sample size n. This motivates the application of a blockwise bootstrap method. We show that the "blocks of blocks" bootstrap method suggested by Politis and Romano (1992) (and further studied by Bühlmann and Künsch (1995)) is...... valid only when volatility is constant. The failure of the blocks of blocks bootstrap is due to the heterogeneity of the squared pre-averaged returns when volatility is stochastic. To preserve both the dependence and the heterogeneity of squared pre-averaged returns, we propose a novel procedure that...
Bootstrapped models for intrinsic random functions
Energy Technology Data Exchange (ETDEWEB)
Campbell, K.
1987-01-01
The use of intrinsic random function stochastic models as a basis for estimation in geostatistical work requires the identification of the generalized covariance function of the underlying process, and the fact that this function has to be estimated from the data introduces an additional source of error into predictions based on the model. This paper develops the sample reuse procedure called the ''bootstrap'' in the context of intrinsic random functions to obtain realistic estimates of these errors. Simulation results support the conclusion that bootstrap distributions of functionals of the process, as well as of their ''kriging variance,'' provide a reasonable picture of the variability introduced by imperfect estimation of the generalized covariance function.
Assessment of Person Fit Using Resampling-Based Approaches
Sinharay, Sandip
2016-01-01
De la Torre and Deng suggested a resampling-based approach for person-fit assessment (PFA). The approach involves the use of the [math equation unavailable] statistic, a corrected expected a posteriori estimate of the examinee ability, and the Monte Carlo (MC) resampling method. The Type I error rate of the approach was closer to the nominal level…
GPU acceleration of the particle filter: the Metropolis resampler
Murray, Lawrence
2012-01-01
We consider deployment of the particle filter on modern massively parallel hardware architectures, such as Graphics Processing Units (GPUs), with a focus on the resampling stage. While standard multinomial and stratified resamplers require a sum of importance weights computed collectively between threads, a Metropolis resampler favourably requires only pair-wise ratios between weights, computed independently by threads, and can be further tuned for performance by adjusting its number of iterations. While achieving respectable results for the stratified and multinomial resamplers, we demonstrate that a Metropolis resampler can be faster where the variance in importance weights is modest, and so is worth considering in a performance-critical context, such as particle Markov chain Monte Carlo and real-time applications.
Collier, Scott; Yin, Xi
2016-01-01
We constrain the spectrum of two-dimensional unitary, compact conformal field theories with central charge c > 1 using modular bootstrap. Upper bounds on the gap in the dimension of primary operators of any spin, as well as in the dimension of scalar primaries, are computed numerically as functions of the central charge using semi-definite programming. Our bounds refine those of Hellerman and Friedan-Keller, and are in some cases saturated by known CFTs. In particular, we show that unitary CFTs with c < 8 must admit relevant deformations, and that a nontrivial bound on the gap of scalar primaries exists for c < 25. We also study bounds on the dimension gap in the presence of twist gaps, bounds on the degeneracy of operators, and demonstrate how "extremal spectra" which maximize the degeneracy at the gap can be determined numerically.
Building Confidence Intervals with Block Bootstraps for the Variance Ratio Test of Predictability
Eduardo José Araújo Lima; Benjamin Miranda Tabak
2007-01-01
This paper compares different versions of the multiple variance ratio test based on bootstrap techniques for the construction of empirical distributions. It also analyzes the crucial issue of selecting optimal block sizes when block bootstrap procedures are used, by applying the methods developed by Hall et al. (1995) and by Politis and White (2004). By comparing the results of the different methods using Monte Carlo simulations, we conclude that methodologies using block bootstrap methods pr...
On the Impact of Bootstrap in Survey Sampling and Small-Area Estimation
Lahiri, P.
2003-01-01
Development of valid bootstrap procedures has been a challenging problem for survey samplers for the last two decades. This is due to the fact that in surveys we constantly face various complex issues such as complex correlation structure induced by the survey design, weighting, imputation, small-area estimation, among others. In this paper, we critically review various bootstrap methods developed to deal with these challenging issues. We discuss two applications where the bootstrap has been ...
The bootstrap current in tokamaks
International Nuclear Information System (INIS)
The properties of the Hirshman equation for the bootstrap in the tokamak and the difference between it and the simpler Hinton-Hazeltine equation are discussed. The Hirshman model, which takes into account finite-aspect-ratio effects, is used to calculate the bootstrap current in the plasma in a circular cross section with Te = Ti. Approximate upper and lower bounds on the bootstrap current are obtained. These restrict the range of variation of the current as the temperature and density profiles vary. 16 refs., 9 figs
Linear algebra and bootstrap percolation
Balogh, József; Morris, Robert; Riordan, Oliver
2011-01-01
In $\\HH$-bootstrap percolation, a set $A \\subset [n]$ of initially `infected' vertices spreads by infecting vertices which are the only uninfected vertex in an edge of the hypergraph $\\HH \\subset \\P(n)$. A particular case of this is the $H$-bootstrap process, in which $\\HH$ encodes copies of $H$ in a graph $G$. We find the minimum size of a set $A$ that leads to complete infection when $G$ is a power of a complete graph and $H$ is a hypercube. The proof uses linear algebra, a technique that is new in bootstrap percolation, although standard in the study of weakly saturated graphs, which are equivalent to (edge) $H$-bootstrap percolation on a complete graph.
Bootstrapping Realized Multivariate Volatility Measures.
Donovon, Prosper; Goncalves, Silvia; Meddahi, Nour
2013-01-01
We study bootstrap methods for statistics that are a function of multivariate high frequency returns such as realized regression coefficients and realized covariances and correlations. For these measures of covariation, the Monte Carlo simulation results of Barndorff-Nielsen and Shephard (2004) show that finite sample distortions associated with their feasible asymptotic theory approach may arise if sampling is not too frequent. This motivates our use of the bootstrap as an altern...
Deep Exploration via Bootstrapped DQN
Osband, Ian; Blundell, Charles; Pritzel, Alexander; Van Roy, Benjamin
2016-01-01
Efficient exploration in complex environments remains a major challenge for reinforcement learning. We propose bootstrapped DQN, a simple algorithm that explores in a computationally and statistically efficient manner through use of randomized value functions. Unlike dithering strategies such as epsilon-greedy exploration, bootstrapped DQN carries out temporally-extended (or deep) exploration; this can lead to exponentially faster learning. We demonstrate these benefits in complex stochastic ...
Bootstrap current in a tokamak
Energy Technology Data Exchange (ETDEWEB)
Kessel, C.E.
1994-03-01
The bootstrap current in a tokamak is examined by implementing the Hirshman-Sigmar model and comparing the predicted current profiles with those from two popular approximations. The dependences of the bootstrap current profile on the plasma properties are illustrated. The implications for steady state tokamaks are presented through two constraints; the pressure profile must be peaked and {beta}{sub p} must be kept below a critical value.
Bootstrap current in a tokamak
International Nuclear Information System (INIS)
The bootstrap current in a tokamak is examined by implementing the Hirshman-Sigmar model and comparing the predicted current profiles with those from two popular approximations. The dependences of the bootstrap current profile on the plasma properties are illustrated. The implications for steady state tokamaks are presented through two constraints; the pressure profile must be peaked and βp must be kept below a critical value
Bootstrap percolation on spatial networks
Jian Gao; Tao Zhou; Yanqing Hu
2015-01-01
Bootstrap percolation is a general representation of some networked activation process, which has found applications in explaining many important social phenomena, such as the propagation of information. Inspired by some recent findings on spatial structure of online social networks, here we study bootstrap percolation on undirected spatial networks, with the probability density function of long-range links’ lengths being a power law with tunable exponent. Setting the size of the giant active...
International Nuclear Information System (INIS)
Confidence interval estimation by the bootstrap method is investigated for the uncertainty quantification of neutronics calculation using the random sampling method. The random sampling method is a simple and practical technique to quantify an uncertainty (standard deviation) of the target parameter calculated by a core analysis code. It is noted that a statistical error is inevitably included in the estimated uncertainty because of the probabilistic method using random numbers. In order to estimate the statistical error of uncertainty, we focus on the bootstrap method. The bootstrap method is one of the resampling techniques to evaluate variance and confidence interval of a sample estimate (e.g. variance) without the assumption of normality. Through a lattice burnup calculation for a simplified boiling water reactor (BWR) fuel assembly, it is verified that the bootstrap method can reasonably estimate the confidence interval of uncertainty of infinite neutron multiplication factor (kinf) due to covariance data of JENDL-4.0. In the case of this problem, the distribution of kinf is well approximated by a normal distribution; thus, the confidence interval of uncertainty can be also estimated by the aid of chi-squared distribution. The merit using the bootstrap method is to simply estimate the confidence interval of uncertainty without the assumption of normality. (author)
Bootstrap Dynamical Symmetry Breaking
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Wei-Shu Hou
2013-01-01
Full Text Available Despite the emergence of a 125 GeV Higgs-like particle at the LHC, we explore the possibility of dynamical electroweak symmetry breaking by strong Yukawa coupling of very heavy new chiral quarks Q . Taking the 125 GeV object to be a dilaton with suppressed couplings, we note that the Goldstone bosons G exist as longitudinal modes V L of the weak bosons and would couple to Q with Yukawa coupling λ Q . With m Q ≳ 700 GeV from LHC, the strong λ Q ≳ 4 could lead to deeply bound Q Q ¯ states. We postulate that the leading “collapsed state,” the color-singlet (heavy isotriplet, pseudoscalar Q Q ¯ meson π 1 , is G itself, and a gap equation without Higgs is constructed. Dynamical symmetry breaking is affected via strong λ Q , generating m Q while self-consistently justifying treating G as massless in the loop, hence, “bootstrap,” Solving such a gap equation, we find that m Q should be several TeV, or λ Q ≳ 4 π , and would become much heavier if there is a light Higgs boson. For such heavy chiral quarks, we find analogy with the π − N system, by which we conjecture the possible annihilation phenomena of Q Q ¯ → n V L with high multiplicity, the search of which might be aided by Yukawa-bound Q Q ¯ resonances.
Bootstrapping quarks and gluons
International Nuclear Information System (INIS)
Dual topological unitarization (DTU) - the approach to S-matrix causality and unitarity through combinatorial topology - is reviewed. Amplitudes associated with triangulated spheres are shown to constitute the core of particle physics. Each sphere is covered by triangulated disc faces corresponding to hadrons. The leading current candidate for the hadron-face triangulation pattern employs 3-triangle basic subdiscs whose orientations correspond to baryon number and topological color. Additional peripheral triangles lie along the hadron-face perimeter. Certain combinations of peripheral triangles with a basic-disc triangle can be identified as quarks, the flavor of a quark corresponding to the orientation of its edges that lie on the hadron-face perimeter. Both baryon number and flavor are additively conserved. Quark helicity, which can be associated with triangle-interior orientation, is not uniformly conserved and interacts with particle momentum, whereas flavor does not. Three different colors attach to the 3 quarks associated with a single basic subdisc, but there is no additive physical conservation law associated with color. There is interplay between color and quark helicity. In hadron faces with more than one basic subdisc, there may occur pairs of adjacent flavorless but colored triangles with net helicity +-1 that are identifiable as gluons. Broken symmetry is an automatic feature of the bootstrap. T, C and P symmetries, as well as up-down flavor symmetry, persist on all orientable surfaces
Bootstrapping Time Dilation Decoherence
Gooding, Cisco; Unruh, William G.
2015-10-01
We present a general relativistic model of a spherical shell of matter with a perfect fluid on its surface coupled to an internal oscillator, which generalizes a model recently introduced by the authors to construct a self-gravitating interferometer (Gooding and Unruh in Phys Rev D 90:044071, 2014). The internal oscillator evolution is defined with respect to the local proper time of the shell, allowing the oscillator to serve as a local clock that ticks differently depending on the shell's position and momentum. A Hamiltonian reduction is performed on the system, and an approximate quantum description is given to the reduced phase space. If we focus only on the external dynamics, we must trace out the clock degree of freedom, and this results in a form of intrinsic decoherence that shares some features with a proposed "universal" decoherence mechanism attributed to gravitational time dilation (Pikovski et al in Nat Phys, 2015). We note that the proposed decoherence remains present in the (gravity-free) limit of flat spacetime, emphasizing that the effect can be attributed entirely to proper time differences, and thus is not necessarily related to gravity. Whereas the effect described in (Pikovski et al in Nat Phys, 2015) vanishes in the absence of an external gravitational field, our approach bootstraps the gravitational contribution to the time dilation decoherence by including self-interaction, yielding a fundamentally gravitational intrinsic decoherence effect.
A Primer on Bootstrap Factor Analysis as Applied to Health Studies Research
Lu, Wenhua; Miao, Jingang; McKyer, E. Lisako J.
2014-01-01
Objectives: To demonstrate how the bootstrap method could be conducted in exploratory factor analysis (EFA) with a syntax written in SPSS. Methods: The data obtained from the Texas Childhood Obesity Prevention Policy Evaluation project (T-COPPE project) were used for illustration. A 5-step procedure to conduct bootstrap factor analysis (BFA) was…
Mir, Tasika; Bernstein, Mark
2016-06-01
Background This is a qualitative study designed to examine neurosurgeons' and neuro-oncologists' perceptions of resampling surgery for glioblastoma multiforme electively, post-therapy or at asymptomatic relapse. Methods Twenty-six neurosurgeons, three radiation oncologists and one neuro-oncologist were selected using convenience sampling and interviewed. Participants were presented with hypothetical scenarios in which resampling surgery was offered within a clinical trial and another in which the surgery was offered on a routine basis. Results Over half of the participants were interested in doing this within a clinical trial. About a quarter of the participants would be willing to consider routine resampling surgery if: (1) a resection were done rather than a simple biopsy; (2) they could wait until the patient becomes symptomatic and (3) there was a preliminary in vitro study with existing tumour samples to be able to offer patients some trial drugs. The remaining quarter of participants was entirely against the trial. Participants also expressed concerns about resource allocation, financial barriers, possibilities of patient coercion and the fear of patients' inability to offer true informed consent. Conclusion Overall, if surgeons are convinced of the benefits of the trial from their information from scientists, and they feel that patients are providing truly informed consent, then the majority would be willing to consider performing the surgery. Many surgeons would still feel uncomfortable with the procedure unless they are able to offer the patient some benefit from the procedure such that the risk to benefit ratio is balanced. PMID:26760112
Medical Image Retrieval Based on Multi-Layer Resampling Template
Institute of Scientific and Technical Information of China (English)
WANG Xin-rui; YANG Yun-feng
2014-01-01
Medical image application in clinical diagnosis and treatment is becoming more and more widely, How to use a large number of images in the image management system and it is a very important issue how to assist doctors to analyze and diagnose. This paper studies the medical image retrieval based on multi-layer resampling template under the thought of the wavelet decomposition, the image retrieval method consists of two retrieval process which is coarse and fine retrieval. Coarse retrieval process is the medical image retrieval process based on the image contour features. Fine retrieval process is the medical image retrieval process based on multi-layer resampling template, a multi-layer sampling operator is employed to extract image resampling images each layer, then these resampling images are retrieved step by step to finish the process from coarse to fine retrieval.
Resampling Algorithms for Particle Filters: A Computational Complexity Perspective
Directory of Open Access Journals (Sweden)
Miodrag Bolić
2004-11-01
Full Text Available Newly developed resampling algorithms for particle filters suitable for real-time implementation are described and their analysis is presented. The new algorithms reduce the complexity of both hardware and DSP realization through addressing common issues such as decreasing the number of operations and memory access. Moreover, the algorithms allow for use of higher sampling frequencies by overlapping in time the resampling step with the other particle filtering steps. Since resampling is not dependent on any particular application, the analysis is appropriate for all types of particle filters that use resampling. The performance of the algorithms is evaluated on particle filters applied to bearings-only tracking and joint detection and estimation in wireless communications. We have demonstrated that the proposed algorithms reduce the complexity without performance degradation.
A Note on the Particle Filter with Posterior Gaussian Resampling
Xiong, X; Navon, I.M.; Uzunoglu, B.
2011-01-01
Particle filter (PF) is a fully non-linear filter with Bayesian conditional probability estimation, compared here with the well-known ensemble Kalman filter (EnKF). A Gaussian resampling (GR) method is proposed to generate the posterior analysis ensemble in an effective and efficient way. The Lorenz model is used to test the proposed method. The PF with Gaussian resampling (PFGR) can approximate more accurately the Bayesian analysis. The present work demonstrates that the proposed PFGR posses...
Double-bootstrap methods that use a single double-bootstrap simulation
Chang, Jinyuan; Hall, Peter
2014-01-01
We show that, when the double bootstrap is used to improve performance of bootstrap methods for bias correction, techniques based on using a single double-bootstrap sample for each single-bootstrap sample can be particularly effective. In particular, they produce third-order accuracy for much less computational expense than is required by conventional double-bootstrap methods. However, this improved level of performance is not available for the single double-bootstrap methods that have been s...
A bootstrap evaluation of the effect of data splitting on financial time series.
LeBaron, B; Weigend, A S
1998-01-01
Exposes problems of the commonly used technique of splitting the available data into training, validation, and test sets that are held fixed, warns about drawing too strong conclusions from such static splits, and shows potential pitfalls of ignoring variability across splits. Using a bootstrap or resampling method, we compare the uncertainty in the solution stemming from the data splitting with neural-network specific uncertainties (parameter initialization, choice of number of hidden units, etc.). We present two results on data from the New York Stock Exchange. First, the variation due to different resamplings is significantly larger than the variation due to different network conditions. This result implies that it is important to not over-interpret a model (or an ensemble of models) estimated on one specific split of the data. Second, on each split, the neural-network solution with early stopping is very close to a linear model; no significant nonlinearities are extracted. PMID:18252443
Application of bootstrap to detecting chaos in financial time series
Brzozowska-Rup, Katarzyna; Orłowski, Arkadiusz
2004-12-01
A moving blocks bootstrap procedure is used to investigate the dynamics of nominal exchange rates and the return rates of the US Dollar against the Polish Zloty. The problem if these financial time series exhibit chaotic behavior is undertaken. A possibility of detecting the presence of a positive Lyapunov exponent is studied.
A Bootstrap Cointegration Rank Test for Panels of VAR Models
DEFF Research Database (Denmark)
Callot, Laurent
functions of the individual Cointegrated VARs (CVAR) models. A bootstrap based procedure is used to compute empirical distributions of the trace test statistics for these individual models. From these empirical distributions two panel trace test statistics are constructed. The satisfying small sample...
Einecke, Sabrina; Bissantz, Nicolai; Clevermann, Fabian; Rhode, Wolfgang
2016-01-01
Astroparticle experiments such as IceCube or MAGIC require a deconvolution of their measured data with respect to the response function of the detector to provide the distributions of interest, e.g. energy spectra. In this paper, appropriate uncertainty limits that also allow to draw conclusions on the geometric shape of the underlying distribution are determined using bootstrap methods, which are frequently applied in statistical applications. Bootstrap is a collective term for resampling methods that can be employed to approximate unknown probability distributions or features thereof. A clear advantage of bootstrap methods is their wide range of applicability. For instance, they yield reliable results, even if the usual normality assumption is violated. The use, meaning and construction of uncertainty limits to any user-specific confidence level in the form of confidence intervals and levels are discussed. The precise algorithms for the implementation of these methods, applicable for any deconvolution algor...
Bootstrap bias-adjusted GMM estimators
Ramalho, Joaquim J.S.
2005-01-01
The ability of six alternative bootstrap methods to reduce the bias of GMM parameter estimates is examined in an instrumental variable framework using Monte Carlo analysis. Promising results were found for the two bootstrap estimators suggested in the paper.
Analytical bootstrap methods for censored data
Alan D. Hutson
2002-01-01
Analytic bootstrap estimators for the moments of survival quantities are derived. By using these expressions recommendations can be made as to the appropriateness of bootstrap estimation under censored data conditions.
The Bootstrap Approach for Testing Skewness Persistence
Krishnamurty Muralidhar
1993-01-01
This study presents a new methodology for testing changes in skewness between time periods (or samples) using the bootstrap method. A Monte Carlo simulation experiment was conducted to compare the effectiveness of the bootstrap method with the method suggested by Lau, Wingender and Lau (1989) to test skewness persistence. The results show the bootstrap method to be more powerful than the other method. The bootstrap method was also used to determine the persistence of skewness in stock returns...
Unsupervised model compression for multilayer bootstrap networks
ZHANG, XIAO-LEI
2015-01-01
Recently, multilayer bootstrap network (MBN) has demonstrated promising performance in unsupervised dimensionality reduction. It can learn compact representations in standard data sets, i.e. MNIST and RCV1. However, as a bootstrap method, the prediction complexity of MBN is high. In this paper, we propose an unsupervised model compression framework for this general problem of unsupervised bootstrap methods. The framework compresses a large unsupervised bootstrap model into a small model by ta...
Bootstrap Sequential Determination of the Co-integration Rank in VAR Models
DEFF Research Database (Denmark)
Guiseppe, Cavaliere; Rahbæk, Anders; Taylor, A.M. Robert
empirical rejection frequencies often very much in excess of the nominal level. As a consequence, bootstrap versions of these tests have been developed. To be useful, however, sequential procedures for determining the co-integrating rank based on these bootstrap tests need to be consistent, in the sense...... we fill this gap in the literature by proposing a bootstrap sequential algorithm which we demonstrate delivers consistent cointegration rank estimation for general I(1) processes. Finite sample Monte Carlo simulations show the proposed procedure performs well in practice....
Coefficient Omega Bootstrap Confidence Intervals: Nonnormal Distributions
Padilla, Miguel A.; Divers, Jasmin
2013-01-01
The performance of the normal theory bootstrap (NTB), the percentile bootstrap (PB), and the bias-corrected and accelerated (BCa) bootstrap confidence intervals (CIs) for coefficient omega was assessed through a Monte Carlo simulation under conditions not previously investigated. Of particular interests were nonnormal Likert-type and binary items.…
On the Asymptotic Accuracy of Efron's Bootstrap
Singh, Kesar
1981-01-01
In the non-lattice case it is shown that the bootstrap approximation of the distribution of the standardized sample mean is asymptotically more accurate than approximation by the limiting normal distribution. The exact convergence rate of the bootstrap approximation of the distributions of sample quantiles is obtained. A few other convergence rates regarding the bootstrap method are also studied.
The bootstrap and edgeworth expansion
Hall, Peter
1992-01-01
This monograph addresses two quite different topics, in the belief that each can shed light on the other. Firstly, it lays the foundation for a particular view of the bootstrap. Secondly, it gives an account of Edgeworth expansion. Chapter 1 is about the bootstrap, witih almost no mention of Edgeworth expansion; Chapter 2 is about Edgeworth expansion, with scarcely a word about the bootstrap; and Chapters 3 and 4 bring these two themes together, using Edgeworth expansion to explore and develop the properites of the bootstrap. The book is aimed a a graduate level audience who has some exposure to the methods of theoretical statistics. However, technical details are delayed until the last chapter (entitled "Details of Mathematical Rogour"), and so a mathematically able reader without knowledge of the rigorous theory of probability will have no trouble understanding the first four-fifths of the book. The book simultaneously fills two gaps in the literature; it provides a very readable graduate level account of t...
Bootstrap-Based Regularization for Low-Rank Matrix Estimation
Josse, Julie; Wager, Stefan
2014-01-01
We develop a flexible framework for low-rank matrix estimation that allows us to transform noise models into regularization schemes via a simple bootstrap algorithm. Effectively, our procedure seeks an autoencoding basis for the observed matrix that is stable with respect to the specified noise model; we call the resulting procedure a stable autoencoder. In the simplest case, with an isotropic noise model, our method is equivalent to a classical singular value shrinkage estimator. For non-iso...
A Bootstrap Cointegration Rank Test for Panels of VAR Models
Callot, Laurent
2010-01-01
This paper proposes a sequential procedure to determine the common cointegration rank of panels of cointegrated VARs. It shows how a panel of cointegrated VARs can be transformed in a set of independent individual models. The likelihood function of the transformed panel is the sum of the likelihood functions of the individual Cointegrated VARs (CVAR) models. A bootstrap based procedure is used to compute empirical distributions of the trace test statistics for these individual models. From th...
A two-stage productivity analysis using bootstrapped Malmquist index and quantile regression
Kaditi, Eleni A.; Nitsi, Elisavet I.
2009-01-01
This paper examines the effects of farm characteristics and government policies in enhancing productivity growth for a sample of Greek farms, using a two-stage procedure. In the 1st-stage, non-parametric estimates of Malmquist index and its decompositions are computed, while a bootstrapping procedure is applied to provide their statistical precision. In the 2nd-stage, the productivity growth estimates are regressed on various covariates using a bootstrapped quantile regression approach. The e...
Feti, Andreea; Dudele, Aiga
2012-01-01
Bootstrapping plays a vital role in the life of small and medium-sized enter-prises. By providing a large variety of financing alternatives bootstrapping ensures the existence of entrepreneurship, even though, too less attention is paid to bootstrapping in the specific literature. Therefore, the master thesis strives to eliminate the gaps in the theory by bringing new insights in the field of bootstrapping.The purpose of the master thesis is to investigate the usage of boot-strapping methods ...
Re-sampling of inline holographic images for improved reconstruction resolution
Podorov, S G; Paganin, D M; Pavlov, K M
2009-01-01
Digital holographic microscopy based on Gabor in-line holography is a well-known method to reconstruct both the amplitude and phase of small objects. To reconstruct the image of an object from its hologram, obtained under illumination by monochromatic scalar waves, numerical calculations of Fresnel integrals are required. To improve spatial resolution in the resulting reconstruction, we re-sample the holographic data before application of the reconstruction algorithm. This procedure amounts to inverting an interpolated Fresnel diffraction image to recover the object. The advantage of this method is demonstrated on experimental data, for the case of visible-light Gabor holography of a resolution grid and a gnat wing.
PARTICLE FILTER BASED VEHICLE TRACKING APPROACH WITH IMPROVED RESAMPLING STAGE
Directory of Open Access Journals (Sweden)
Wei Leong Khong
2014-02-01
Full Text Available Optical sensors based vehicle tracking can be widely implemented in traffic surveillance and flow control. The vast development of video surveillance infrastructure in recent years has drawn the current research focus towards vehicle tracking using high-end and low cost optical sensors. However, tracking vehicles via such sensors could be challenging due to the high probability of changing vehicle appearance and illumination, besides the occlusion and overlapping incidents. Particle filter has been proven as an approach which can overcome nonlinear and non-Gaussian situations caused by cluttered background and occlusion incidents. Unfortunately, conventional particle filter approach encounters particle degeneracy especially during and after the occlusion. Particle filter with sampling important resampling (SIR is an important step to overcome the drawback of particle filter, but SIR faced the problem of sample impoverishment when heavy particles are statistically selected many times. In this work, genetic algorithm has been proposed to be implemented in the particle filter resampling stage, where the estimated position can converge faster to hit the real position of target vehicle under various occlusion incidents. The experimental results show that the improved particle filter with genetic algorithm resampling method manages to increase the tracking accuracy and meanwhile reduce the particle sample size in the resampling stage.
Introduction to Permutation and Resampling-Based Hypothesis Tests
LaFleur, Bonnie J.; Greevy, Robert A.
2009-01-01
A resampling-based method of inference--permutation tests--is often used when distributional assumptions are questionable or unmet. Not only are these methods useful for obvious departures from parametric assumptions (e.g., normality) and small sample sizes, but they are also more robust than their parametric counterparts in the presences of…
Bootstrap Current in Spherical Tokamaks
Institute of Scientific and Technical Information of China (English)
王中天; 王龙
2003-01-01
Variational principle for the neoclassical theory has been developed by including amomentum restoring term in the electron-electron collisional operator, which gives an additionalfree parameter maximizing the heat production rate. All transport coefficients are obtained in-cluding the bootstrap current. The essential feature of the study is that the aspect ratio affects thefunction of the electron-electron collision operator through a geometrical factor. When the aspectratio approaches to unity, the fraction of circulating particles goes to zero and the contribution toparticle flux from the electron-electron collision vanishes. The resulting diffusion coefficient is inrough agreement with Hazeltine. When the aspect ratio approaches to infinity, the results are inagreement with Rosenbluth. The formalism gives the two extreme cases a connection. The theoryis particularly important for the calculation of bootstrap current in spherical tokamaks and thepresent tokamaks, in which the square root of the inverse aspect ratio, in general, is not small.
Bootstrapping N=2 chiral correlators
Lemos, Madalena; Liendo, Pedro
2016-01-01
We apply the numerical bootstrap program to chiral operators in four-dimensional N=2 SCFTs. In the first part of this work we study four-point functions in which all fields have the same conformal dimension. We give special emphasis to bootstrapping a specific theory: the simplest Argyres-Douglas fixed point with no flavor symmetry. In the second part we generalize our setup and consider correlators of fields with unequal dimension. This is an example of a mixed correlator and allows us to probe new regions in the parameter space of N=2 SCFTs. In particular, our results put constraints on relations in the Coulomb branch chiral ring and on the curvature of the Zamolodchikov metric.
Bootstrapping N=2 chiral correlators
Energy Technology Data Exchange (ETDEWEB)
Lemos, Madalena [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Liendo, Pedro [Humboldt-Univ. Berlin (Germany). IMIP
2015-12-15
We apply the numerical bootstrap program to chiral operators in four-dimensional N=2 SCFTs. In the first part of this work we study four-point functions in which all fields have the same conformal dimension. We give special emphasis to bootstrapping a specific theory: the simplest Argyres-Douglas fixed point with no flavor symmetry. In the second part we generalize our setup and consider correlators of fields with unequal dimension. This is an example of a mixed correlator and allows us to probe new regions in the parameter space of N=2 SCFTs. In particular, our results put constraints on relations in the Coulomb branch chiral ring and on the curvature of the Zamolodchikov metric.
Horn, D.
2015-03-01
The quark model emerged from the Gell-Mann-Ne'eman flavor SU(3) symmetry. Its development, in the context of strong interactions, took place in a heuristic theoretical framework, referred to as the Bootstrap Era. Setting the background for the dominant ideas in strong interaction of the early 1960s, we outline some aspects of the constituent quark model. An independent theoretical development was the emergence of hadron duality in 1967, leading to a realization of the Bootstrap idea by relating hadron resonances (in the s-channel) with Regge pole trajectories (in t- and u-channels). The synthesis of duality with the quark-model has been achieved by duality diagrams, serving as a conceptual framework for discussing many aspects of hadron dynamics toward the end of the 1960s.
Conformal Bootstrap in Mellin Space
Gopakumar, Rajesh; Sen, Kallol; Sinha, Aninda
2016-01-01
We propose a new approach towards analytically solving for the dynamical content of Conformal Field Theories (CFTs) using the bootstrap philosophy. This combines the original bootstrap idea of Polyakov with the modern technology of the Mellin representation of CFT amplitudes. We employ exchange Witten diagrams with built in crossing symmetry as our basic building blocks rather than the conventional conformal blocks in a particular channel. Demanding consistency with the operator product expansion (OPE) implies an infinite set of constraints on operator dimensions and OPE coefficients. We illustrate the power of this method in the epsilon expansion of the Wilson-Fisher fixed point by computing operator dimensions and, strikingly, OPE coefficients to higher orders in epsilon than currently available using other analytic techniques (including Feynman diagram calculations). Our results enable us to get a somewhat better agreement of certain observables in the 3d Ising model, with the precise numerical values that...
Bootstrapping N=2 chiral correlators
International Nuclear Information System (INIS)
We apply the numerical bootstrap program to chiral operators in four-dimensional N=2 SCFTs. In the first part of this work we study four-point functions in which all fields have the same conformal dimension. We give special emphasis to bootstrapping a specific theory: the simplest Argyres-Douglas fixed point with no flavor symmetry. In the second part we generalize our setup and consider correlators of fields with unequal dimension. This is an example of a mixed correlator and allows us to probe new regions in the parameter space of N=2 SCFTs. In particular, our results put constraints on relations in the Coulomb branch chiral ring and on the curvature of the Zamolodchikov metric.
On a generalized bootstrap principle
International Nuclear Information System (INIS)
The S-matrices for non-simply-laced affine Toda field theories are considered in the context of a generalized bootstrap principle. The S-matrices, and in particular their poles, depend on a parameter whose range lies between the Coxeter numbers of dual pairs of the corresponding non-simply-laced algebras. It is proposed that only odd order poles in the physical strip with positive coefficients throughout this range should participate in the bootstrap. All other singularities have an explanation in principle in terms of a generalized Coleman-Thun mechanism. Besides the S-matrices introduced by Delius, Grisaru and Zanon, the missing case (F4(1), e6(2)), is also considered and provides many interesting examples of pole generation. (author)
Bootstrap clustering for graph partitioning
Gambette, Philippe; Guénoche, Alain
2011-01-01
Given a simple undirected weighted or unweighted graph, we try to cluster the vertex set into communities and also to quantify the robustness of these clusters. For that task, we propose a new method, called bootstrap clustering which consists in (i) defining a new clustering algorithm for graphs, (ii) building a set of graphs similar to the initial one, (iii) applying the clustering method to each of them, making a profile (set) of partitions, (iv) computing a consensus partition for this pr...
Conformal Bootstrap in Embedding Space
Fortin, Jean-François
2016-01-01
It is shown how to obtain conformal blocks from embedding space with the help of the operator product expansion. The minimal conformal block originates from scalar exchange in a four-point correlation functions of four scalars. All remaining conformal blocks are simple derivatives of the minimal conformal block. With the help of the orthogonality properties of the conformal blocks, the analytic conformal bootstrap can be implemented directly in embedding space, leading to a Jacobi-like definition of conformal field theories.
Conformal bootstrap in embedding space
Fortin, Jean-François; Skiba, Witold
2016-05-01
It is shown how to obtain conformal blocks from embedding space with the help of the operator product expansion. The minimal conformal block originates from scalar exchange in a four-point correlation function of four scalars. All remaining conformal blocks are simple derivatives of the minimal conformal block. With the help of the orthogonality properties of the conformal blocks, the analytic conformal bootstrap can be implemented directly in embedding space, leading to a Jacobi-like definition of conformal field theories.
Bootstrapping High Dimensional Time Series
Zhang, Xianyang; Cheng, Guang
2014-01-01
This article studies bootstrap inference for high dimensional weakly dependent time series in a general framework of approximately linear statistics. The following high dimensional applications are covered: (1) uniform confidence band for mean vector; (2) specification testing on the second order property of time series such as white noise testing and bandedness testing of covariance matrix; (3) specification testing on the spectral property of time series. In theory, we first derive a Gaussi...
Modified Bootstrap Sensitometry In Radiography
Bednarek, Daniel R.; Rudin, Stephen
1981-04-01
A new modified bootstrap approach to sensitometry is presented which provides H and D curves that show almost exact agreement with those obtained using conventional methods. Two bootstrap techniques are described; both involve a combination of inverse-square and stepped-wedge modulation of the radiation field and provide intensity-scale sensitometric curves as appropriate for medical radiography. H and D curves obtained with these modified techniques are compared with those obtained for screen-film combinations using inverse-square sensitometry as well as with those obtained for direct x-ray film using time-scale sensitometry. The stepped wedge of the Wisconsin X-Ray Test Cassette was used in the bootstrap approach since it provides sufficient exposure latitude to encompass the useful density range of medical x-ray film. This approach makes radiographic sensitometry quick and convenient, allowing accurate characteristic curves to be obtained for any screen-film cassette using standard diagnostic x-ray equipment.
Theoretical comparisons of block bootstrap methods
Lahiri, S. N.
1999-01-01
In this paper, we compare the asymptotic behavior of some common block bootstrap methods based on nonrandom as well as random block lengths. It is shown that, asymptotically, bootstrap estimators derived using any of the methods considered in the paper have the same amount of bias to the first order. However, the variances of these bootstrap estimators may be different even in the first order. Expansions for the bias, the variance and the mean-squared error of different bloc...
Comparison of resampling method applied to censored data
Directory of Open Access Journals (Sweden)
Claude Arrabal
2014-06-01
Full Text Available This paper is about a comparison study among the performances of variance estimators of certain parameters, usingresampling techniques such as bootstrap and jackknife. The comparison will be made among several situations ofsimulated censored data, relating the observed values of estimates to real values. For real data, it will be consideredthe dataset Stanford heart transplant, analyzed by Cho et al. (2009 using the model of Cox regression (Cox, 1972for adjustment. It is noted that the Jackknife residual is ecient to analyze inuential data points in the responsevariable.Keywords: bootstrap, Jackknife, simulation, Cox Regression Model, censored data.
Focused grid-based resampling for protein docking and mapping.
Mamonov, Artem B; Moghadasi, Mohammad; Mirzaei, Hanieh; Zarbafian, Shahrooz; Grove, Laurie E; Bohnuud, Tanggis; Vakili, Pirooz; Ch Paschalidis, Ioannis; Vajda, Sandor; Kozakov, Dima
2016-04-30
The fast Fourier transform (FFT) sampling algorithm has been used with success in application to protein-protein docking and for protein mapping, the latter docking a variety of small organic molecules for the identification of binding hot spots on the target protein. Here we explore the local rather than global usage of the FFT sampling approach in docking applications. If the global FFT based search yields a near-native cluster of docked structures for a protein complex, then focused resampling of the cluster generally leads to a substantial increase in the number of conformations close to the native structure. In protein mapping, focused resampling of the selected hot spot regions generally reveals further hot spots that, while not as strong as the primary hot spots, also contribute to ligand binding. The detection of additional ligand binding regions is shown by the improved overlap between hot spots and bound ligands. © 2016 Wiley Periodicals, Inc. PMID:26837000
Multiquark hadrons in topological bootstrap
International Nuclear Information System (INIS)
We use the lowest-order topological bootstrap framework to calculate hadron masses by imposing duality on an infinite sum of ladder graphs generated from spherical unitarity. By making a certain simple dynamical approximation, we derive an explicit generic Regge-trajectory formula for any given process. If we then make certain reasonable dynamical assumptions and require simultaneous consistency for entire sets of processes, we are able to calculate the masses of all the lowest meson, baryon and multiquark states involving u and d quarks, and the Regge trajectories associated with each of them. The only arbitrary parameter is the mass of the rho, which merely serves to set the mass scale
Adaptive Distributed Resampling Algorithm with Non-Proportional Allocation
Demirel, Ömer; Smal, Ihor; Niessen, Wiro; Meijering, Erik; Ivo F Sbalzarini
2013-01-01
The distributed resampling algorithm with proportional allocation (RNA) is key to implementing particle filtering applications on parallel computer systems. We extend the original work by Bolic et al. by introducing an adaptive RNA (ARNA) algorithm, improving RNA by dynamically adjusting the particle-exchange ratio and randomizing the process ring topology. This improves the runtime performance of ARNA by about 9% over RNA with 10% particle exchange. ARNA also significantly improves the speed...
Using re-sampling methods in mortality studies.
Directory of Open Access Journals (Sweden)
Igor Itskovich
Full Text Available Traditional methods of computing standardized mortality ratios (SMR in mortality studies rely upon a number of conventional statistical propositions to estimate confidence intervals for obtained values. Those propositions include a common but arbitrary choice of the confidence level and the assumption that observed number of deaths in the test sample is a purely random quantity. The latter assumption may not be fully justified for a series of periodic "overlapping" studies. We propose a new approach to evaluating the SMR, along with its confidence interval, based on a simple re-sampling technique. The proposed method is most straightforward and requires neither the use of above assumptions nor any rigorous technique, employed by modern re-sampling theory, for selection of a sample set. Instead, we include all possible samples that correspond to the specified time window of the study in the re-sampling analysis. As a result, directly obtained confidence intervals for repeated overlapping studies may be tighter than those yielded by conventional methods. The proposed method is illustrated by evaluating mortality due to a hypothetical risk factor in a life insurance cohort. With this method used, the SMR values can be forecast more precisely than when using the traditional approach. As a result, the appropriate risk assessment would have smaller uncertainties.
Generic Hardware Architectures for Sampling and Resampling in Particle Filters
Directory of Open Access Journals (Sweden)
Petar M. Djurić
2005-10-01
Full Text Available Particle filtering is a statistical signal processing methodology that has recently gained popularity in solving several problems in signal processing and communications. Particle filters (PFs have been shown to outperform traditional filters in important practical scenarios. However their computational complexity and lack of dedicated hardware for real-time processing have adversely affected their use in real-time applications. In this paper, we present generic architectures for the implementation of the most commonly used PF, namely, the sampling importance resampling filter (SIRF. These provide a generic framework for the hardware realization of the SIRF applied to any model. The proposed architectures significantly reduce the memory requirement of the filter in hardware as compared to a straightforward implementation based on the traditional algorithm. We propose two architectures each based on a different resampling mechanism. Further, modifications of these architectures for acceleration of resampling process are presented. We evaluate these schemes based on resource usage and latency. The platform used for the evaluations is the Xilinx Virtex II pro FPGA. The architectures presented here have led to the development of the first hardware (FPGA prototype for the particle filter applied to the bearings-only tracking problem.
Statistical bootstrap model and annihilations
Möhring, H J
1974-01-01
The statistical bootstrap model (SBM) describes the decay of single, high mass, hadronic states (fireballs, clusters) into stable particles. Coupling constants B, one for each isospin multiplet of stable particles, are the only free parameter of the model. They are related to the maximum temperature parameter T/sub 0/. The various versions of the SMB can be classified into two groups: full statistical bootstrap models and linear ones. The main results of the model are the following: i) All momentum spectra are isotropic; especially the exclusive ones are described by invariant phase space. The inclusive and semi-inclusive single-particle distributions are asymptotically of pure exponential shape; the slope is governed by T /sub 0/ only. ii) The model parameter B for pions has been obtained by fitting the multiplicity distribution in pp and pn at rest, and corresponds to T/sub 0/=0.167 GeV in the full SBM with exotics. The average pi /sup -/ multiplicity for the linear and the full SBM (both with exotics) is c...
The (2, 0) superconformal bootstrap
Beem, Christopher; Lemos, Madalena; Rastelli, Leonardo; van Rees, Balt C.
2016-01-01
We develop the conformal bootstrap program for six-dimensional conformal field theories with (2, 0) supersymmetry, focusing on the universal four-point function of stress tensor multiplets. We review the solution of the superconformal Ward identities and describe the superconformal block decomposition of this correlator. We apply numerical bootstrap techniques to derive bounds on operator product expansion (OPE) coefficients and scaling dimensions from the constraints of crossing symmetry and unitarity. We also derive analytic results for the large spin spectrum using the light cone expansion of the crossing equation. Our principal result is strong evidence that the A1 theory realizes the minimal allowed central charge (c =25 ) for any interacting (2, 0) theory. This implies that the full stress tensor four-point function of the A1 theory is the unique unitary solution to the crossing symmetry equation at c =25 . For this theory, we estimate the scaling dimensions of the lightest unprotected operators appearing in the stress tensor operator product expansion. We also find rigorous upper bounds for dimensions and OPE coefficients for a general interacting (2, 0) theory of central charge c . For large c , our bounds appear to be saturated by the holographic predictions obtained from eleven-dimensional supergravity.
Bootstrap percolation on spatial networks
Gao, Jian; Zhou, Tao; Hu, Yanqing
2015-10-01
Bootstrap percolation is a general representation of some networked activation process, which has found applications in explaining many important social phenomena, such as the propagation of information. Inspired by some recent findings on spatial structure of online social networks, here we study bootstrap percolation on undirected spatial networks, with the probability density function of long-range links’ lengths being a power law with tunable exponent. Setting the size of the giant active component as the order parameter, we find a parameter-dependent critical value for the power-law exponent, above which there is a double phase transition, mixed of a second-order phase transition and a hybrid phase transition with two varying critical points, otherwise there is only a second-order phase transition. We further find a parameter-independent critical value around -1, about which the two critical points for the double phase transition are almost constant. To our surprise, this critical value -1 is just equal or very close to the values of many real online social networks, including LiveJournal, HP Labs email network, Belgian mobile phone network, etc. This work helps us in better understanding the self-organization of spatial structure of online social networks, in terms of the effective function for information spreading.
Bootstrap percolation in high dimensions
Balogh, Jozsef; Morris, Robert
2009-01-01
In r-neighbour bootstrap percolation on a graph G, a set of initially infected vertices A \\subset V(G) is chosen independently at random, with density p, and new vertices are subsequently infected if they have at least r infected neighbours. The set A is said to percolate if eventually all vertices are infected. Our aim is to understand this process on the grid, [n]^d, for arbitrary functions n = n(t), d = d(t) and r = r(t), as t -> infinity. The main question is to determine the critical probability p_c([n]^d,r) at which percolation becomes likely, and to give bounds on the size of the critical window. In this paper we study this problem when r = 2, for all functions n and d satisfying d \\gg log n. The bootstrap process has been extensively studied on [n]^d when d is a fixed constant and 2 \\le r \\le d, and in these cases p_c([n]^d,r) has recently been determined up to a factor of 1 + o(1) as n -> infinity. At the other end of the scale, Balogh and Bollobas determined p_c([2]^d,2) up to a constant factor, and...
A Bayesian Bootstrap for a Finite Population
Lo, Albert Y.
1988-01-01
A Bayesian bootstrap for a finite population is introduced; its small-sample distributional properties are discussed and compared with those of the frequentist bootstrap for a finite population. It is also shown that the two are first-order asymptotically equivalent.
Coefficient Alpha Bootstrap Confidence Interval under Nonnormality
Padilla, Miguel A.; Divers, Jasmin; Newton, Matthew
2012-01-01
Three different bootstrap methods for estimating confidence intervals (CIs) for coefficient alpha were investigated. In addition, the bootstrap methods were compared with the most promising coefficient alpha CI estimation methods reported in the literature. The CI methods were assessed through a Monte Carlo simulation utilizing conditions…
Bootstrapping Phylogenetic Trees: Theory and Methods
Holmes, Susan
2003-01-01
This is a survey of the use of the bootstrap in the area of systematic and evolutionary biology. I present the current usage by biologists of the bootstrap as a tool both for making inferences and for evaluating robustness, and propose a framework for thinking about these problems in terms of mathematical statistics.
Bootstrap Prediction Intervals in Non-Parametric Regression with Applications to Anomaly Detection
Kumar, Sricharan; Srivistava, Ashok N.
2012-01-01
Prediction intervals provide a measure of the probable interval in which the outputs of a regression model can be expected to occur. Subsequently, these prediction intervals can be used to determine if the observed output is anomalous or not, conditioned on the input. In this paper, a procedure for determining prediction intervals for outputs of nonparametric regression models using bootstrap methods is proposed. Bootstrap methods allow for a non-parametric approach to computing prediction intervals with no specific assumptions about the sampling distribution of the noise or the data. The asymptotic fidelity of the proposed prediction intervals is theoretically proved. Subsequently, the validity of the bootstrap based prediction intervals is illustrated via simulations. Finally, the bootstrap prediction intervals are applied to the problem of anomaly detection on aviation data.
Limitations of bootstrap current models
International Nuclear Information System (INIS)
We assess the accuracy and limitations of two analytic models of the tokamak bootstrap current: (1) the well-known Sauter model (1999 Phys. Plasmas 6 2834, 2002 Phys. Plasmas 9 5140) and (2) a recent modification of the Sauter model by Koh et al (2012 Phys. Plasmas 19 072505). For this study, we use simulations from the first-principles kinetic code NEO as the baseline to which the models are compared. Tests are performed using both theoretical parameter scans as well as core-to-edge scans of real DIII-D and NSTX plasma profiles. The effects of extreme aspect ratio, large impurity fraction, energetic particles, and high collisionality are studied. In particular, the error in neglecting cross-species collisional coupling—an approximation inherent to both analytic models—is quantified. Furthermore, the implications of the corrections from kinetic NEO simulations on MHD equilibrium reconstructions is studied via integrated modeling with kinetic EFIT. (paper)
The N=2 superconformal bootstrap
Beem, Christopher; Lemos, Madalena; Liendo, Pedro; Rastelli, Leonardo; van Rees, Balt C.
2016-03-01
In this work we initiate the conformal bootstrap program for N=2 super-conformal field theories in four dimensions. We promote an abstract operator-algebraic viewpoint in order to unify the description of Lagrangian and non-Lagrangian theories, and formulate various conjectures concerning the landscape of theories. We analyze in detail the four-point functions of flavor symmetry current multiplets and of N=2 chiral operators. For both correlation functions we review the solution of the superconformal Ward identities and describe their superconformal block decompositions. This provides the foundation for an extensive numerical analysis discussed in the second half of the paper. We find a large number of constraints for operator dimensions, OPE coefficients, and central charges that must hold for any N=2 superconformal field theory.
On uniform resampling and gaze analysis of bidirectional texture functions
Czech Academy of Sciences Publication Activity Database
Filip, Jiří; Chantler, M.J.; Haindl, Michal
2009-01-01
Roč. 6, č. 3 (2009), s. 1-15. ISSN 1544-3558 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant ostatní: EC Marie Curie(BE) 41358 Institutional research plan: CEZ:AV0Z10750506 Keywords : BTF * texture * eye tracking Subject RIV: BD - Theory of Information Impact factor: 1.447, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-on uniform resampling and gaze analysis of bidirectional texture functions.pdf
Bootstrap Sequential Determination of the Co-integration Rank in VAR Models
DEFF Research Database (Denmark)
Cavaliere, Giuseppe; Rahbek, Anders; Taylor, A. M. Robert
empirical rejection frequencies often very much in excess of the nominal level. As a consequence, bootstrap versions of these tests have been developed. To be useful, however, sequential procedures for determining the co-integrating rank based on these bootstrap tests need to be consistent, in the sense...... that the probability of selecting a rank smaller than (equal to) the true co-integrating rank will converge to zero (one minus the marginal significance level), as the sample size diverges, for general I(1) processes. No such likelihood-based procedure is currently known to be available. In this paper...... we fill this gap in the literature by proposing a bootstrap sequential algorithm which we demonstrate delivers consistent cointegration rank estimation for general I(1) processes. Finite sample Monte Carlo simulations show the proposed procedure performs well in practice....
On the estimation of the extremal index based on scaling and resampling
Hamidieh, Kamal; Michailidis, George
2010-01-01
The extremal index parameter theta characterizes the degree of local dependence in the extremes of a stationary time series and has important applications in a number of areas, such as hydrology, telecommunications, finance and environmental studies. In this study, a novel estimator for theta based on the asymptotic scaling of block-maxima and resampling is introduced. It is shown to be consistent and asymptotically normal for a large class of m-dependent time series. Further, a procedure for the automatic selection of its tuning parameter is developed and different types of confidence intervals that prove useful in practice proposed. The performance of the estimator is examined through simulations, which show its highly competitive behavior. Finally, the estimator is applied to three real data sets of daily crude oil prices, daily returns of the S&P 500 stock index, and high-frequency, intra-day traded volumes of a stock. These applications demonstrate additional diagnostic features of statistical plots ...
Bootstrap current estimate in the ETE Tokamak
International Nuclear Information System (INIS)
First estimates of the bootstrap current in the ETE small aspect ratio tokamak using the Hirshman single ion collisionless model show that we can expect from 25 to 55% of total bootstrap current depending on the optimization level of the plasma parameter profiles. Higher levels of bootstrap current are limited by peaked pressure profiles and βpol values which must be kept under a critical level due to stability conditions. Different methods for the trapped particle fraction calculation are also illustrated in this paper. (author). 7 refs., 5 figs., 1 tab
A model study in hadron statistical bootstrap
Hagedorn, Rolf
1973-01-01
In the framework of the statistical bootstrap the decay of a fireball is considered as an exact inverse of its statistical composition. This assumption leads to a bootstrap formulated in terms of integral equations for all kinds of distributions of the fireball's decay products. Solutions of the equations are obtained in terms of power series and of K-transforms and determine in the general case their asymptotic behaviour for large fireball mass. Relations to a thermodynamical description are established and illustrated by effective temperatures. The approach to the asymptotic limits is easy to investigate in a simplified linear bootstrap where the K-transforms can be more explicitly calculated. (30 refs).
Effect of resampling schemes on significance analysis of clustering and ranking
Mirshahvalad, Atieh; Archambault, Eric; Rosvall, Martin
2012-01-01
Community detection helps us simplify the complex configuration of networks, but communities are reliable only if they are statistically significant. To detect statistically significant communities, one approach is to repeatedly perturb the original network and analyze the communities. But the perturbation approach is reliable only if we understand how the results depend on the underlying assumptions of the perturbation method. Here we explore how maintaining link correlations in resampling schemes affects the significance of communities in citation networks. We compare maintained link correlations in non-parametric article resampling with parametric resampling of citations that reduce link correlations in multinomial and Poisson resampling. While multinomial resampling maintains the variance of individual link weights and eliminates correlations between connected links, Poisson resampling eliminates any link correlations. For significance analysis of ranking and clustering, we find that it is more important ...
Bootstrapping under constraint for the assessment of group behavior in human contact networks
Tremblay, Nicolas; Forest, Cary; Nornberg, Mark; Pinton, Jean-François; Borgnat, Pierre
2012-01-01
The increasing availability of time --and space-- resolved data describing human activities and interactions gives insights into both static and dynamic properties of human behavior. In practice, nevertheless, real-world datasets can often be considered as only one realisation of a particular event. This highlights a key issue in social network analysis: the statistical significance of estimated properties. In this context, we focus here on the assessment of quantitative features of specific subset of nodes in empirical networks. We present a resampling method based on bootstrapping groups of nodes under constraints within the empirical network. The method enables us to define confidence intervals for various Null Hypotheses concerning relevant properties of the subset of nodes under consideration, in order to characterize its behavior as "normal" or not. We apply this method to a high resolution dataset describing the face-to-face proximity of individuals during two co-located scientific conferences. As a ca...
Learning With l1 -Regularizer Based on Markov Resampling.
Gong, Tieliang; Zou, Bin; Xu, Zongben
2016-05-01
Learning with l1 -regularizer has brought about a great deal of research in learning theory community. Previous known results for the learning with l1 -regularizer are based on the assumption that samples are independent and identically distributed (i.i.d.), and the best obtained learning rate for the l1 -regularization type algorithms is O(1/√m) , where m is the samples size. This paper goes beyond the classic i.i.d. framework and investigates the generalization performance of least square regression with l1 -regularizer ( l1 -LSR) based on uniformly ergodic Markov chain (u.e.M.c) samples. On the theoretical side, we prove that the learning rate of l1 -LSR for u.e.M.c samples l1 -LSR(M) is with the order of O(1/m) , which is faster than O(1/√m) for the i.i.d. counterpart. On the practical side, we propose an algorithm based on resampling scheme to generate u.e.M.c samples. We show that the proposed l1 -LSR(M) improves on the l1 -LSR(i.i.d.) in generalization error at the low cost of u.e.M.c resampling. PMID:26011874
International Nuclear Information System (INIS)
This paper aims to propose a bootstrap method for characterizing the effect of uncertainty in shear strength parameters on slope reliability. The procedure for a traditional slope reliability analysis with fixed distributions of shear strength parameters is presented first. Then, the variations of the mean and standard deviation of shear strength parameters and the Akaike Information Criterion values associated with various distributions are studied to characterize the uncertainties in distribution parameters and types of shear strength parameters. The reliability of an infinite slope is presented to demonstrate the validity of the proposed method. The results indicate that the bootstrap method can effectively model the uncertain probability distributions of shear strength parameters. The uncertain distributions of shear strength parameters have a significant influence on slope reliability. With the bootstrap method, the slope reliability index is represented by a confidence interval instead of a single fixed index. The confidence interval increases with increasing factor of slope safety. Considering both the uncertainties in distribution parameters and distribution types of shear strength parameters leads to a higher variation and a wider confidence interval of reliability index. - Highlights: • A bootstrap method is proposed to characterize effect of uncertainty on reliability. • An infinite slope is studied to demonstrate validity of bootstrap method. • The bootstrap method can effectively model uncertain probability distributions. • Slope reliability index is a confidence interval instead of a single fixed index. • Confidence interval of reliability index increases with increasing factor of safety
The alignment of bootstrap current in tokamak
International Nuclear Information System (INIS)
By calculating the trapped particle fraction, solving the Grand-Shafranov equation describing plasma equilibrium, and using Harris model, the magnitude and alignment of the bootstrap current in tokamak are calculated and analysed under the conventional shear regimes and also the negative central shear regimes. The conclusion authors obtained are: through adjusting the profile parameters of plasma density, temperature and current, and the elongation k and triangularity d which describe the plasma shape, the alignment of bootstrap current profile with the equilibrium current profile can be produced; the negative central shear regimes are advantage ous to produce bootstrap current, and the profile of bootstrap current is well-aligned with the equilibrium current profile. By comparing authors' calculated results, the optimized parameters are obtained under the conventional shear and the negative central shear regimes
iDESWEB: Frameworks CSS: Bootstrap
Yuste Torregrosa, Álvaro; Luján Mora, Sergio
2012-01-01
Framework CSS (herramientas y pautas), frameworks más famosos (BluePrint, 960 Grid System, YUI), Twitter Bootstrap, ejemplo de botones, ejemplo de uso de la rejilla. Sitio web del curso: http://idesweb.es/
Investigating Mortality Uncertainty Using the Block Bootstrap
Directory of Open Access Journals (Sweden)
Xiaoming Liu
2010-01-01
Full Text Available This paper proposes a block bootstrap method for measuring mortality risk under the Lee-Carter model framework. In order to take account of all sources of risk (the process risk, the parameter risk, and the model risk properly, a block bootstrap is needed to cope with the spatial dependence found in the residuals. As a result, the prediction intervals we obtain for life expectancy are more accurate than the ones obtained from other similar methods.
Theoretical Comparison of Bootstrap Confidence Intervals
Hall, Peter
1988-01-01
We develop a unified framework within which many commonly used bootstrap critical points and confidence intervals may be discussed and compared. In all, seven different bootstrap methods are examined, each being usable in both parametric and nonparametric contexts. Emphasis is on the way in which the methods cope with first- and second-order departures from normality. Percentile-$t$ and accelerated bias-correction emerge as the most promising of existing techniques. Certain other methods are ...
Investigating Mortality Uncertainty Using the Block Bootstrap
Xiaoming Liu; W. John Braun
2010-01-01
This paper proposes a block bootstrap method for measuring mortality risk under the Lee-Carter model framework. In order to take account of all sources of risk (the process risk, the parameter risk, and the model risk) properly, a block bootstrap is needed to cope with the spatial dependence found in the residuals. As a result, the prediction intervals we obtain for life expectancy are more accurate than the ones obtained from other similar methods.
Bootstrapping Reflective Systems: The Case of Pharo
Polito, Guillermo; Ducasse, Stéphane; Fabresse, Luc; Bouraqadi, Noury; Van Ryseghem, Benjamin
2014-01-01
Bootstrapping is a technique commonly known by its usage in language definition by the introduction of a compiler written in the same language it compiles. This process is important to understand and modify the definition of a given language using the same language, taking benefit of the abstractions and expression power it provides. A bootstrap, then, supports the evolution of a language. However, the infrastructure of reflective systems like Smalltalk includes, in addition to a compiler, an...
Bootstrapping the European Gender Wage Gap
Rueckert, Eva
2003-01-01
This paper investigates the gender wage gap in Denmark, the Netherlands, France and Spain by bootstrapping the Oaxaca-Blinder decomposition. The bootstrap method is used to compute confidence intervals and to perform hypothesis tests for the (disaggregated) explained and unexplained components of the national earnings di?erentials between men and women. From the subset of paid employees selected from the European Community Household Panel (ECHP) it is revealed that the respective national gen...
A new approach to bootstrap inference in functional coefficient models
Herwartz, Helmut; Xu, Fang
2007-01-01
We introduce a new, factor based bootstrap approach which is robust under heteroskedastic error terms for inference in functional coefficient models. Modeling the functional coefficient parametrically, the bootstrap approximation of an F statistic is shown to hold asymptotically. In simulation studies with both parametric and nonparametric functional coefficients, factor based bootstrap inference outperforms the wild bootstrap and pairs bootstrap approach according to its size features. Apply...
The Bootstrap of Mean for Dependent Heterogeneous Arrays.
GONÇALVES, Silvia; White, Halbert
2001-01-01
Presently, conditions ensuring the validity of bootstrap methods for the sample mean of (possibly heterogeneous) near epoch dependent (NED) functions of mixing processes are unknown. Here we establish the validity of the bootstrap in this context, extending the applicability of bootstrap methods to a class of processes broadly relevant for applications in economics and finance. Our results apply to two block bootstrap methods: the moving blocks bootstrap of Künsch ( 989) and Liu and Singh ( 9...
Maximum Likelihood and the Bootstrap for Nonlinear Dynamic Models
Goncalves, Silvia; White, Halbert
2002-01-01
The bootstrap is an increasingly popular method for performing statistical inference. This paper provides the theoretical foundation for using the bootstrap as a valid tool of inference for quasi-maximum likelihood estimators (QMLE). We provide a unified framework for analyzing bootstrapped extremum estimators of nonlinear dynamic models for heterogeneous dependent stochastic processes. We apply our results to two block bootstrap methods, the moving blocks bootstrap of Künsch (1989) and Liu a...
Bootstrap current in NBI heated plasmas
International Nuclear Information System (INIS)
The expression for the bootstrap current density due to fast ions produced by NBI is derived in an axisymmetric magnetic field. From this expression the fast-ion-induced bootstrap current density is explicitly calculated in a large aspect ratio tokamak with circular cross-section. This bootstrap current is found to be quite small for parallel injection of neutral beams although it rapidly increases as it approaches perpendicular injection. In addition to the injection angle, this bootstrap current density depends strongly upon the values of the inverse aspect ratio an element of and the ratio υc (critical velocity)/υb (birth velocity). In perpendicular injection the ratio of the fast-ion-induced bootstrap current density to the bulk bootstrap current density is estimated for the typical parameters an element of = 0.1 and υc/υb = 0.5 as 0.09 (δβb/δr)/(δβe/δr), where βb and βe are the values of beta due to fast-ion and electron pressures, respectively. (author). 7 refs, 4 figs
Aptamer Affinity Maturation by Resampling and Microarray Selection.
Kinghorn, Andrew B; Dirkzwager, Roderick M; Liang, Shaolin; Cheung, Yee-Wai; Fraser, Lewis A; Shiu, Simon Chi-Chin; Tang, Marco S L; Tanner, Julian A
2016-07-19
Aptamers have significant potential as affinity reagents, but better approaches are critically needed to discover higher affinity nucleic acids to widen the scope for their diagnostic, therapeutic, and proteomic application. Here, we report aptamer affinity maturation, a novel aptamer enhancement technique, which combines bioinformatic resampling of aptamer sequence data and microarray selection to navigate the combinatorial chemistry binding landscape. Aptamer affinity maturation is shown to improve aptamer affinity by an order of magnitude in a single round. The novel aptamers exhibited significant adaptation, the complexity of which precludes discovery by other microarray based methods. Honing aptamer sequences using aptamer affinity maturation could help optimize a next generation of nucleic acid affinity reagents. PMID:27346322
Loop calculus and bootstrap-belief propagation for perfect matchings on arbitrary graphs
Chertkov, M.; Gelfand, A.; Shin, J.
2013-12-01
This manuscript discusses computation of the Partition Function (PF) and the Minimum Weight Perfect Matching (MWPM) on arbitrary, non-bipartite graphs. We present two novel problem formulations - one for computing the PF of a Perfect Matching (PM) and one for finding MWPMs - that build upon the inter-related Bethe Free Energy (BFE), Belief Propagation (BP), Loop Calculus (LC), Integer Linear Programming and Linear Programming frameworks. First, we describe an extension of the LC framework to the PM problem. The resulting formulas, coined (fractional) Bootstrap-BP, express the PF of the original model via the BFE of an alternative PM problem. We then study the zero-temperature version of this Bootstrap-BP formula for approximately solving the MWPM problem. We do so by leveraging the Bootstrap-BP formula to construct a sequence of MWPM problems, where each new problem in the sequence is formed by contracting odd-sized cycles (or blossoms) from the previous problem. This Bootstrap-and-Contract procedure converges reliably and generates an empirically tight upper bound for the MWPM. We conclude by discussing the relationship between our iterative procedure and the famous Blossom Algorithm of Edmonds '65 and demonstrate the performance of the Bootstrap-and-Contract approach on a variety of weighted PM problems.
Loop calculus and bootstrap-belief propagation for perfect matchings on arbitrary graphs
International Nuclear Information System (INIS)
This manuscript discusses computation of the Partition Function (PF) and the Minimum Weight Perfect Matching (MWPM) on arbitrary, non-bipartite graphs. We present two novel problem formulations – one for computing the PF of a Perfect Matching (PM) and one for finding MWPMs – that build upon the inter-related Bethe Free Energy (BFE), Belief Propagation (BP), Loop Calculus (LC), Integer Linear Programming and Linear Programming frameworks. First, we describe an extension of the LC framework to the PM problem. The resulting formulas, coined (fractional) Bootstrap-BP, express the PF of the original model via the BFE of an alternative PM problem. We then study the zero-temperature version of this Bootstrap-BP formula for approximately solving the MWPM problem. We do so by leveraging the Bootstrap-BP formula to construct a sequence of MWPM problems, where each new problem in the sequence is formed by contracting odd-sized cycles (or blossoms) from the previous problem. This Bootstrap-and-Contract procedure converges reliably and generates an empirically tight upper bound for the MWPM. We conclude by discussing the relationship between our iterative procedure and the famous Blossom Algorithm of Edmonds '65 and demonstrate the performance of the Bootstrap-and-Contract approach on a variety of weighted PM problems
Conditional Modeling and the Jitter Method of Spike Re-sampling: Supplement
Amarasingham, Asohan; Harrison, Matthew T.; Hatsopoulos, Nicholas G.; Geman, Stuart
2011-01-01
This technical report accompanies the manuscript "Conditional Modeling and the Jitter Method of Spike Re-sampling." It contains further details, comments, references, and equations concerning various simulations and data analyses presented in that manuscript, as well as a self-contained Mathematical Appendix that provides a formal treatment of jitter-based spike re-sampling methods.
Bootstrap inversion for Pn wave velocity in North-Western Italy
Directory of Open Access Journals (Sweden)
C. Eva
1997-06-01
Full Text Available An inversion of Pn arrival times from regional distance earthquakes (180-800 km, recorded by 94 seismic stations operating in North-Western Italy and surrounding areas, was carried out to image lateral variations of P-wave velocity at the crust-mantle boundary, and to estimate the static delay time at each station. The reliability of the obtained results was assessed using both synthetic tests and the bootstrap Monte Carlo resampling technique. Numerical simulations demonstrated the existence of a trade-off between cell velocities and estimated station delay times along the edge of the model. Bootstrap inversions were carried out to determine the standard deviation of velocities and time terms. Low Pn velocity anomalies are detected beneath the outer side of the Alps (-6% and the Western Po plain (-4% in correspondence with two regions of strong crustal thickening and negative Bouguer anomaly. In contrast, high Pn velocities are imaged beneath the inner side of the Alps (+4% indicating the presence of high velocity and density lower crust-upper mantle. The Ligurian sea shows high Pn velocities close to the Ligurian coastlines (+3% and low Pn velocities (-1.5% in the middle of the basin in agreement with the upper mantle velocity structure revealed by seismic refraction profiles.
Bootstrap states of the Z-pinch
International Nuclear Information System (INIS)
Steady bootstrap states of a Z-pinch are investigated both in absence and in presence of an imposed axial magnetic field, in terms of MHD theory with classical resistivity. The results indicate that bootstrap operation should become possible for certain classes of plasma profiles and that such operation can lead to higher bootstrap currents in a Z-pinch without axial magnetic field than in a tokamak-like case under similar plasma conditions. The ratio between the latter and the former currents is of the order of the square root of the beta value in the tokamak-like case. A simple numerical example is given on boot-strap operation in the Z-pinch. Neoclassical or anomalous diffusion will increase the diffusion velocity of the plasma but are not expected to affect the main physical features of the present results. This applies also to the kinetic effects in the weak-field region near the axis of the Z-pinch, because these effects can largely be described by MHD-like equations for a steady equilibrium. Bootstrap operation and the technical difficulty in realizing a volume distribution of particle sinks introduce certain constraints on the plasma and current profiles. This has to be taken into account in a stability analysis. The latter cannot only be performed in terms of MHD-like theory but has to be based on kinetic theory including large Larmor radius (LLR) effects. (author)
A Class of Population Covariance Matrices in the Bootstrap Approach to Covariance Structure Analysis
Yuan, Ke-Hai; Hayashi, Kentaro; Yanagihara, Hirokazu
2007-01-01
Model evaluation in covariance structure analysis is critical before the results can be trusted. Due to finite sample sizes and unknown distributions of real data, existing conclusions regarding a particular statistic may not be applicable in practice. The bootstrap procedure automatically takes care of the unknown distribution and, for a given…
The bootstrap conditions for the gluon Reggeization
International Nuclear Information System (INIS)
Compatibility of gluon Reggeization with s-channel unitarity requires the vertices of the Reggeon interactions to satisfy a series of bootstrap conditions. In order to derive, in the next-to-leading order (NLO), conditions related to the gluon production amplitudes, we calculate the s-channel discontinuities of these amplitudes and compare them with those required by the Reggeization. It turns out that these conditions include the so called strong bootstrap conditions for the kernel and for the impact factors of scattering particles, which were proposed earlier without derivation, and recently were proved to be satisfied. Besides this, there is a new bootstrap condition, which relates a number of Reggeon vertices and the gluon trajectory. (orig.)
Stability of LHD plasmas with bootstrap current
International Nuclear Information System (INIS)
Since a net toroidal current flowing in the direction increasing the rotational transform (t) has a destabilizing contribution in the Mercier criterion in the LHD configuration, two approaches are considered so that the bootstrap current should not flow in the direction. One is the change in the geometry by unbalancing the helical coil currents. The other is the enhancement of the collisionality in the plasma. In both cases, the bootstrap current can flow in the direction where t is decreased, because the geometrical factor in the limit of the 1/ν regime is drastically changed. The enhancement of the bumpiness and the l=1 components in the magnetic field is essential in the change. In these equilibria, the reduction of t by the bootstrap current results in the increase of the Shafranov shift, which leads to the improvement of the Mercier criterion. (author)
Bootstrap Percolation on Random Geometric Graphs
Bradonjić, Milan
2012-01-01
Bootstrap percolation has been used effectively to model phenomena as diverse as emergence of magnetism in materials, spread of infection, diffusion of software viruses in computer networks, adoption of new technologies, and emergence of collective action and cultural fads in human societies. It is defined on an (arbitrary) network of interacting agents whose state is determined by the state of their neighbors according to a threshold rule. In a typical setting, bootstrap percolation starts by random and independent "activation" of nodes with a fixed probability $p$, followed by a deterministic process for additional activations based on the density of active nodes in each neighborhood ($\\th$ activated nodes). Here, we study bootstrap percolation on random geometric graphs in the regime when the latter are (almost surely) connected. Random geometric graphs provide an appropriate model in settings where the neighborhood structure of each node is determined by geographical distance, as in wireless {\\it ad hoc} ...
Selfconsistent RF driven and bootstrap currents
International Nuclear Information System (INIS)
In order to achieve steady-state high performance regimes in tokamaks, it is important to sustain and control the pressure and magnetic shear profiles in high bootstrap current plasmas. RF waves can be used to achieve such a goal. Then the bootstrap current fraction must be calculated selfconsistently with RF induced currents, taking into account possible synergistic effects resulting from the distortion of the electron velocity-space distribution. Results obtained with a new 3-D code that solves the electron drift kinetic equation to study the synergistic effects are presented. While synergism between bootstrap and LH-driven currents remains modest, it may reach up to 30-40% for the case of EC current drive provided the plasma parameters are properly chosen. (author)
Suthers, G K; Wilson, S. R.
1990-01-01
Multipoint linkage analysis is a powerful method for mapping a rare disease gene on the human gene map despite limited genotype and pedigree data. However, there is no standard procedure for determining a confidence interval for gene location by using multipoint linkage analysis. A genetic counselor needs to know the confidence interval for gene location in order to determine the uncertainty of risk estimates provided to a consultant on the basis of DNA studies. We describe a resampling, or "...
Bootstrap percolation: a renormalisation group approach
International Nuclear Information System (INIS)
In bootstrap percolation, sites are occupied at random with probability p, but each site is considered active only if at least m of its neighbours are also active. Within an approximate position-space renormalization group framework on a square lattice we obtain the behaviour of the critical concentration p (sub)c and of the critical exponents ν and β for m = 0 (ordinary percolation), 1,2 and 3. We find that the bootstrap percolation problem can be cast into different universality classes, characterized by the values of m. (author)
BOOTSTRAPPING FOR EXTRACTING RELATIONS FROM LARGE CORPORA
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
A new approach of relation extraction is described in this paper. It adopts a bootstrapping model with a novel iteration strategy, which generates more precise examples of specific relation. Compared with previous methods, the proposed method has three main advantages: first, it needs less manual intervention; second, more abundant and reasonable information are introduced to represent a relation pattern; third, it reduces the risk of circular dependency occurrence in bootstrapping. Scalable evaluation methodology and metrics are developed for our task with comparable techniques over TianWang 100G corpus. The experimental results show that it can get 90% precision and have excellent expansibility.
Early Stop Criterion from the Bootstrap Ensemble
DEFF Research Database (Denmark)
Hansen, Lars Kai; Larsen, Jan; Fog, Torben L.
1997-01-01
This paper addresses the problem of generalization error estimation in neural networks. A new early stop criterion based on a Bootstrap estimate of the generalization error is suggested. The estimate does not require the network to be trained to the minimum of the cost function, as required by...... other methods based on asymptotic theory. Moreover, in contrast to methods based on cross-validation which require data left out for testing, and thus biasing the estimate, the Bootstrap technique does not have this disadvantage. The potential of the suggested technique is demonstrated on various time...
Conference on Bootstrapping and Related Techniques
Rothe, Günter; Sendler, Wolfgang
1992-01-01
This book contains 30 selected, refereed papers from an in- ternational conference on bootstrapping and related techni- ques held in Trier 1990. Thepurpose of the book is to in- form about recent research in the area of bootstrap, jack- knife and Monte Carlo Tests. Addressing the novice and the expert it covers as well theoretical as practical aspects of these statistical techniques. Potential users in different disciplines as biometry, epidemiology, computer science, economics and sociology but also theoretical researchers s- hould consult the book to be informed on the state of the art in this area.
Bootstrap Method for Dependent Data Structure and Measure of Statistical Precision
Directory of Open Access Journals (Sweden)
T. O. Olatayo
2010-01-01
Full Text Available Problem statement: This article emphasized on the construction of valid inferential procedures for an estimator θ^ as a measure of its statistical precision for dependent data structure. Approach: The truncated geometric bootstrap estimates of standard error and other measures of statistical precision such as bias, coefficient of variation, ratio and root mean square error are considered. Results: We extend it to other measures of statistical precision such as bootstrap confidence interval for an estimator θ^ and illustrate with real geological data. Conclusion/Recommendations: The bootstrap estimates of standard error and other measures of statistical accuracy such as bias, ratio, coefficient of variation and root mean square error reveals the suitability of the method for dependent data structure.
The use of the bootstrap in the analysis of case-control studies with missing data
DEFF Research Database (Denmark)
Siersma, Volkert Dirk; Johansen, Christoffer
2004-01-01
nonparametric bootstrap, bootstrap confidence intervals, missing values, multiple imputation, matched case-control study......nonparametric bootstrap, bootstrap confidence intervals, missing values, multiple imputation, matched case-control study...
A Large Sample Study of the Bayesian Bootstrap
Lo, Albert Y.
1987-01-01
An asymptotic justification of the Bayesian bootstrap is given. Large-sample Bayesian bootstrap probability intervals for the mean, the variance and bands for the distribution, the smoothed density and smoothed rate function are also provided.
Wild bootstrap of the mean in the infinite variance case
Giuseppe Cavaliere; Iliyan Georgiev; Robert Taylor, A. M.
2011-01-01
It is well known that the standard i.i.d. bootstrap of the mean is inconsistent in a location model with infinite variance (alfa-stable) innovations. This occurs because the bootstrap distribution of a normalised sum of infinite variance random variables tends to a random distribution. Consistent bootstrap algorithms based on subsampling methods have been proposed but have the drawback that they deliver much wider confidence sets than those generated by the i.i.d. bootstrap owing to the fact ...
uniform bootstrap confidence bands for bounded influence curve estimators
Härdle, Wolfgang Karl; Ritov, Ya‘acov; Wang, Weining
2013-01-01
We consider theoretical bootstrap "coupling" techniques for nonparametric robust smoothers and quantile regression, and verify the bootstrap improvement. To cope with curse of dimensionality, a variant of "coupling" bootstrap techniques are developed for additive models with both symmetric error distributions and further extension to the quantile regression framework. Our bootstrap method can be used in many situations like constructing con dence intervals and bands. We demonstrate the bootst...
Comment on: 'A Poisson resampling method for simulating reduced counts in nuclear medicine images'
DEFF Research Database (Denmark)
de Nijs, Robin
2015-01-01
direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all...... counts below 100. Only Poisson resampling was not affected by this, while Gaussian redrawing was less affected by itthan Poisson redrawing. Poisson resampling is the method of choice, when simulating half-count (or less) images from full-count images. It simulates correctly the statistical properties...
Weak Convergence of Smoothed and Nonsmoothed Bootstrap Quantile Estimates
Falk, M; Reiss, R.-D.
1989-01-01
Under fairly general assumptions on the underlying distribution function, the bootstrap process, pertaining to the sample $q$-quantile, converges weakly in $D_\\mathbb{R}$ to the standard Brownian motion. Furthermore, weak convergence of a smoothed bootstrap quantile estimate is proved which entails that in this particular case the smoothed bootstrap estimate outperforms the nonsmoothed one.
Testing for asymmetry in economic time series using bootstrap methods
Claudio Lupi; Patrizia Ordine
2001-01-01
In this paper we show that phase-scrambling bootstrap offers a natural framework for asymmetry testing in economic time series. A comparison with other bootstrap schemes is also sketched. A Monte Carlo analysis is carried out to evaluate the size and power properties of the phase-scrambling bootstrap-based test.
The bootstrap current and its consequences
International Nuclear Information System (INIS)
The physical mechanism behind the bootstrap current is explained, and the consequences are discussed with the emphasis on the two main objectives of fusion plasma, confinement and MHD stability. For a tokamak reactor that is optimized for good confinement and stability, and that has a limited size, the total plasma current exceeds the bootstrap current by a factor of three to five and therefore almost all the plasma current must be driven through other means. Furthermore, the neoclassical tearing mode which is driven by the bootstrap current is expected to be the limiting MHD instability in these reactors. Raising the fraction of the bootstrap current is not expected to be beneficial for confinement and stability expect when broad pressure profiles (internal transport barriers) can be realized. In stellarators several optimizations are possible, either optimizing the current to zero such that it does not destroy the desired topology, and it does not generate any current-driven instabilities, or using the current to generate some of the poloidal field. (author)
How to Bootstrap a Human Communication System
Fay, Nicolas; Arbib, Michael; Garrod, Simon
2013-01-01
How might a human communication system be bootstrapped in the absence of conventional language? We argue that motivated signs play an important role (i.e., signs that are linked to meaning by structural resemblance or by natural association). An experimental study is then reported in which participants try to communicate a range of pre-specified…
Pulling Econometrics Students up by Their Bootstraps
O'Hara, Michael E.
2014-01-01
Although the concept of the sampling distribution is at the core of much of what we do in econometrics, it is a concept that is often difficult for students to grasp. The thought process behind bootstrapping provides a way for students to conceptualize the sampling distribution in a way that is intuitive and visual. However, teaching students to…
Automatic bootstrapping and tracking of object contours.
Chiverton, John; Xie, Xianghua; Mirmehdi, Majid
2012-03-01
A new fully automatic object tracking and segmentation framework is proposed. The framework consists of a motion-based bootstrapping algorithm concurrent to a shape-based active contour. The shape-based active contour uses finite shape memory that is automatically and continuously built from both the bootstrap process and the active-contour object tracker. A scheme is proposed to ensure that the finite shape memory is continuously updated but forgets unnecessary information. Two new ways of automatically extracting shape information from image data given a region of interest are also proposed. Results demonstrate that the bootstrapping stage provides important motion and shape information to the object tracker. This information is found to be essential for good (fully automatic) initialization of the active contour. Further results also demonstrate convergence properties of the content of the finite shape memory and similar object tracking performance in comparison with an object tracker with unlimited shape memory. Tests with an active contour using a fixed-shape prior also demonstrate superior performance for the proposed bootstrapped finite-shape-memory framework and similar performance when compared with a recently proposed active contour that uses an alternative online learning model. PMID:21908256
Usery, E.L.; Finn, M.P.; Scheidt, D.J.; Ruhl, S.; Beard, T.; Bearden, M.
2004-01-01
Researchers have been coupling geographic information systems (GIS) data handling and processing capability to watershed and waterquality models for many years. This capability is suited for the development of databases appropriate for water modeling. However, it is rare for GIS to provide direct inputs to the models. To demonstrate the logical procedure of coupling GIS for model parameter extraction, we selected the Agricultural Non-Point Source (AGNPS) pollution model. Investigators can generate data layers at various resolutions and resample to pixel sizes to support models at particular scales. We developed databases of elevation, land cover, and soils at various resolutions in four watersheds. The ability to use multiresolution databases for the generation of model parameters is problematic for grid-based models. We used database development procedures and observed the effects of resolution and resampling on GIS input datasets and parameters generated from those inputs for AGNPS. Results indicate that elevation values at specific points compare favorably between 3- and 30-m raster datasets. Categorical data analysis indicates that land cover classes vary significantly. Derived parameters parallel the results of the base GIS datasets. Analysis of data resampled from 30-m to 60-, 120-, 210-, 240-, 480-, 960-, and 1920-m pixels indicates a general degradation of both elevation and land cover correlations as resolution decreases. Initial evaluation of model output values for soluble nitrogen and phosphorous indicates similar degradation with resolution. ?? Springer-Verlag 2004.
The Block-block Bootstrap: Improved Asymptotic Refinements
Donald W.K. Andrews
2002-01-01
The asymptotic refinements attributable to the block bootstrap for time series are not as large as those of the nonparametric iid bootstrap or the parametric bootstrap. One reason is that the independence between the blocks in the block bootstrap sample does not mimic the dependence structure of the original sample. This is the join-point problem. In this paper, we propose a method of solving this problem. The idea is not to alter the block bootstrap. Instead, we alter the original sample sta...
Resampling of an Image by Block-Based Interpolation or Decimation with Compensation
Kapinos, M.; J. Mihalik; J. Zavacky
2000-01-01
Due to multiple standards on digital coding of image it is expected that conversion from one picture format to another will be quite necessary for display or recording of different format sources. Conventional approach of 2-D sampling rate conversion by polyphase filters requires relatively large memory and computational power. Therefore, a new efficient method for image resampling has been presented. The proposed approach performs resampling block by block with overlap. To minimize the overl...
DEFF Research Database (Denmark)
Huang, Shaojun; Mathe, Laszlo; Teodorescu, Remus
proper switching instances needed for the resampling modulation technique. The software implementation of the proposed phase shifted PWM (PS-PWM) method, and its application in a distributed control system for MMC, are fully discussed in this paper. Simulation and experiment results show that the...... proposed solution can realize the resampled uniform PWM and provide high effective sampling frequency and low time delay, which is critical for the distributed control of MMC....
Lightweight CoAP-Based Bootstrapping Service for the Internet of Things.
Garcia-Carrillo, Dan; Marin-Lopez, Rafael
2016-01-01
The Internet of Things (IoT) is becoming increasingly important in several fields of industrial applications and personal applications, such as medical e-health, smart cities, etc. The research into protocols and security aspects related to this area is continuously advancing in making these networks more reliable and secure, taking into account these aspects by design. Bootstrapping is a procedure by which a user obtains key material and configuration information, among other parameters, to operate as an authenticated party in a security domain. Until now solutions have focused on re-using security protocols that were not developed for IoT constraints. For this reason, in this work we propose a design and implementation of a lightweight bootstrapping service for IoT networks that leverages one of the application protocols used in IoT : Constrained Application Protocol (CoAP). Additionally, in order to provide flexibility, scalability, support for large scale deployment, accountability and identity federation, our design uses technologies such as the Extensible Authentication Protocol (EAP) and Authentication Authorization and Accounting (AAA). We have named this service CoAP-EAP. First, we review the state of the art in the field of bootstrapping and specifically for IoT. Second, we detail the bootstrapping service: the architecture with entities and interfaces and the flow operation. Third, we obtain performance measurements of CoAP-EAP (bootstrapping time, memory footprint, message processing time, message length and energy consumption) and compare them with PANATIKI. The most significant and constrained representative of the bootstrapping solutions related with CoAP-EAP. As we will show, our solution provides significant improvements, mainly due to an important reduction of the message length. PMID:26978362
Lightweight CoAP-Based Bootstrapping Service for the Internet of Things
Directory of Open Access Journals (Sweden)
Dan Garcia-Carrillo
2016-03-01
Full Text Available The Internet of Things (IoT is becoming increasingly important in several fields of industrial applications and personal applications, such as medical e-health, smart cities, etc. The research into protocols and security aspects related to this area is continuously advancing in making these networks more reliable and secure, taking into account these aspects by design. Bootstrapping is a procedure by which a user obtains key material and configuration information, among other parameters, to operate as an authenticated party in a security domain. Until now solutions have focused on re-using security protocols that were not developed for IoT constraints. For this reason, in this work we propose a design and implementation of a lightweight bootstrapping service for IoT networks that leverages one of the application protocols used in IoT : Constrained Application Protocol (CoAP. Additionally, in order to provide flexibility, scalability, support for large scale deployment, accountability and identity federation, our design uses technologies such as the Extensible Authentication Protocol (EAP and Authentication Authorization and Accounting (AAA. We have named this service CoAP-EAP. First, we review the state of the art in the field of bootstrapping and specifically for IoT. Second, we detail the bootstrapping service: the architecture with entities and interfaces and the flow operation. Third, we obtain performance measurements of CoAP-EAP (bootstrapping time, memory footprint, message processing time, message length and energy consumption and compare them with PANATIKI. The most significant and constrained representative of the bootstrapping solutions related with CoAP-EAP. As we will show, our solution provides significant improvements, mainly due to an important reduction of the message length.
Lightweight CoAP-Based Bootstrapping Service for the Internet of Things
Garcia-Carrillo, Dan; Marin-Lopez, Rafael
2016-01-01
The Internet of Things (IoT) is becoming increasingly important in several fields of industrial applications and personal applications, such as medical e-health, smart cities, etc. The research into protocols and security aspects related to this area is continuously advancing in making these networks more reliable and secure, taking into account these aspects by design. Bootstrapping is a procedure by which a user obtains key material and configuration information, among other parameters, to operate as an authenticated party in a security domain. Until now solutions have focused on re-using security protocols that were not developed for IoT constraints. For this reason, in this work we propose a design and implementation of a lightweight bootstrapping service for IoT networks that leverages one of the application protocols used in IoT : Constrained Application Protocol (CoAP). Additionally, in order to provide flexibility, scalability, support for large scale deployment, accountability and identity federation, our design uses technologies such as the Extensible Authentication Protocol (EAP) and Authentication Authorization and Accounting (AAA). We have named this service CoAP-EAP. First, we review the state of the art in the field of bootstrapping and specifically for IoT. Second, we detail the bootstrapping service: the architecture with entities and interfaces and the flow operation. Third, we obtain performance measurements of CoAP-EAP (bootstrapping time, memory footprint, message processing time, message length and energy consumption) and compare them with PANATIKI. The most significant and constrained representative of the bootstrapping solutions related with CoAP-EAP. As we will show, our solution provides significant improvements, mainly due to an important reduction of the message length. PMID:26978362
Lahiri, S. N.
2005-01-01
Efron [J. Roy. Statist. Soc. Ser. B 54 (1992) 83--111] proposed a computationally efficient method, called the jackknife-after-bootstrap, for estimating the variance of a bootstrap estimator for independent data. For dependent data, a version of the jackknife-after-bootstrap method has been recently proposed by Lahiri [Econometric Theory 18 (2002) 79--98]. In this paper it is shown that the jackknife-after-bootstrap estimators of the variance of a bootstrap quantile are consistent for both de...
Dexter, Troy A; Kowalewski, Michał
2013-12-01
Quantitative estimates of growth rates can augment ecological and paleontological applications of body-size data. However, in contrast to body-size estimates, assessing growth rates is often time-consuming, expensive, or unattainable. Here we use an indirect approach, a jackknife-corrected parametric bootstrap, for efficient approximation of growth rates using nearest living relatives with known age-size relationships. The estimate is developed by (1) collecting a sample of published growth rates of closely related species, (2) calculating the average growth curve using those published age-size relationships, (3) resampling iteratively these empirically known growth curves to estimate the standard errors and confidence bands around the average growth curve, and (4) applying the resulting estimate of uncertainty to bracket age-size relationships of the species of interest. This approach was applied to three monophyletic families (Donacidae, Mactridae, and Semelidae) of mollusk bivalves, a group characterized by indeterministic shell growth, but widely used in ecological, paleontological, and geochemical research. The resulting indirect estimates were tested against two previously published geochemical studies and, in both cases, yielded highly congruent age estimates. In addition, a case study in applied fisheries was used to illustrate the potential of the proposed approach for augmenting aquaculture management practices. The resulting estimates of growth rates place body size data in a constrained temporal context and confidence intervals associated with resampling estimates allow for assessing the statistical uncertainty around derived temporal ranges. The indirect approach should allow for improved evaluation of diverse research questions, from sustainability of industrial shellfish harvesting to climatic interpretations of stable isotope proxies extracted from fossil skeletons. PMID:24071629
Bootstrapping ${\\mathcal N}=2$ chiral correlators
Lemos, Madalena
2016-01-01
We apply the numerical bootstrap program to chiral operators in four-dimensional ${\\mathcal N}=2$ SCFTs. In the first part of this work we study four-point functions in which all fields have the same conformal dimension. We give special emphasis to bootstrapping a specific theory: the simplest Argyres-Douglas fixed point with no flavor symmetry. In the second part we generalize our setup and consider correlators of fields with unequal dimension. This is an example of a mixed correlator and allows us to probe new regions in the parameter space of ${\\mathcal N}=2$ SCFTs. In particular, our results put constraints on relations in the Coulomb branch chiral ring and on the curvature of the Zamolodchikov metric.
Extremal bootstrapping: go with the flow
El-Showk, Sheer
2016-01-01
The extremal functional method determines approximate solutions to the constraints of crossing symmetry, which saturate bounds on the space of unitary CFTs. We show that such solutions are characterized by extremality conditions, which may be used to flow continuously along the boundaries of parameter space. Along the flow there is generically no further need for optimization, which dramatically reduces computational requirements, bringing calculations from the realm of computing clusters to laptops. Conceptually, extremality sheds light on possible ways to bootstrap without positivity, extending the method to non-unitary theories, and implies that theories saturating bounds, and especially those sitting at kinks, have unusually sparse spectra. We discuss several applications, including the first high-precision bootstrap of a non-unitary CFT.
The $(2,0)$ superconformal bootstrap
Beem, Christopher; Rastelli, Leonardo; van Rees, Balt C
2016-01-01
We develop the conformal bootstrap program for six-dimensional conformal field theories with $(2,0)$ supersymmetry, focusing on the universal four-point function of stress tensor multiplets. We review the solution of the superconformal Ward identities and describe the superconformal block decomposition of this correlator. We apply numerical bootstrap techniques to derive bounds on OPE coefficients and scaling dimensions from the constraints of crossing symmetry and unitarity. We also derive analytic results for the large spin spectrum using the lightcone expansion of the crossing equation. Our principal result is strong evidence that the $A_1$ theory realizes the minimal allowed central charge $(c=25)$ for any interacting $(2,0)$ theory. This implies that the full stress tensor four-point function of the $A_1$ theory is the unique unitary solution to the crossing symmetry equation at $c=25$. For this theory, we estimate the scaling dimensions of the lightest unprotected operators appearing in the stress tenso...
The Correct Kriging Variance Estimated by Bootstrapping
den Hertog, D.; Kleijnen, J.P.C.; Siem, A.Y.D.
2004-01-01
The classic Kriging variance formula is widely used in geostatistics and in the design and analysis of computer experiments.This paper proves that this formula is wrong.Furthermore, it shows that the formula underestimates the Kriging variance in expectation.The paper develops parametric bootstrapping to estimate the Kriging variance.The new method is tested on several artificial examples and a real-life case study.These results demonstrate that the classic formula underestimates the true Kri...
TASI Lectures on the Conformal Bootstrap
Simmons-Duffin, David
2016-01-01
These notes are from courses given at TASI and the Advanced Strings School in summer 2015. Starting from principles of quantum field theory and the assumption of a traceless stress tensor, we develop the basics of conformal field theory, including conformal Ward identities, radial quantization, reflection positivity, the operator product expansion, and conformal blocks. We end with an introduction to numerical bootstrap methods, focusing on the 2d and 3d Ising models.
Bootstrapping Deep Lexical Resources: Resources for Courses
Baldwin, Timothy
2007-01-01
We propose a range of deep lexical acquisition methods which make use of morphological, syntactic and ontological language resources to model word similarity and bootstrap from a seed lexicon. The different methods are deployed in learning lexical items for a precision grammar, and shown to each have strengths and weaknesses over different word classes. A particular focus of this paper is the relative accessibility of different language resource types, and predicted ``bang for the buck'' associated with each in deep lexical acquisition applications.
Accidental symmetries and the conformal bootstrap
Chester, Shai M.; Giombi, Simone; Iliesiu, Luca V.; Klebanov, Igor R.; Pufu, Silviu S.; Yacoby, Ran
2016-01-01
We study an N=2 supersymmetric generalization of the three-dimensional critical O( N) vector model that is described by N + 1 chiral superfields with superpotential W = g 1 X∑ i Z 1 2 + g 2 X 3. By combining the tools of the conformal bootstrap with results obtained through supersymmetric localization, we argue that this model exhibits a symmetry enhancement at the infrared superconformal fixed point due to g 2 flowing to zero. This example is special in that the existence of an infrared fixed point with g 1 , g 2 ≠ 0, which does not exhibit symmetry enhancement, does not generally lead to any obvious unitarity violations or other inconsistencies. We do show, however, that the F-theorem excludes the models with g 1 , g 2 ≠ 0 for N > 5. The conformal bootstrap provides a stronger constraint and excludes such models for N > 2. We provide evidence that the g 2 = 0 models, which have the enhanced O( N) × U(1) symmetry, come close to saturating the bootstrap bounds. We extend our analysis to fractional dimensions where we can motivate the nonexistence of the g 1 , g 2 ≠ 0 models by studying them perturbatively in the 4 - ɛ expansion.
Moreno, Claudia E.; Guevara, Roger; Sánchez-Rojas, Gerardo; Téllez, Dianeis; Verdú, José R.
2008-01-01
Environmental assessment at the community level in highly diverse ecosystems is limited by taxonomic constraints and statistical methods requiring true replicates. Our objective was to show how diverse systems can be studied at the community level using higher taxa as biodiversity surrogates, and re-sampling methods to allow comparisons. To illustrate this we compared the abundance, richness, evenness and diversity of the litter fauna in a pine-oak forest in central Mexico among seasons, sites and collecting methods. We also assessed changes in the abundance of trophic guilds and evaluated the relationships between community parameters and litter attributes. With the direct search method we observed differences in the rate of taxa accumulation between sites. Bootstrap analysis showed that abundance varied significantly between seasons and sampling methods, but not between sites. In contrast, diversity and evenness were significantly higher at the managed than at the non-managed site. Tree regression models show that abundance varied mainly between seasons, whereas taxa richness was affected by litter attributes (composition and moisture content). The abundance of trophic guilds varied among methods and seasons, but overall we found that parasitoids, predators and detrivores decreased under management. Therefore, although our results suggest that management has positive effects on the richness and diversity of litter fauna, the analysis of trophic guilds revealed a contrasting story. Our results indicate that functional groups and re-sampling methods may be used as tools for describing community patterns in highly diverse systems. Also, the higher taxa surrogacy could be seen as a preliminary approach when it is not possible to identify the specimens at a low taxonomic level in a reasonable period of time and in a context of limited financial resources, but further studies are needed to test whether the results are specific to a system or whether they are general
Consistency of the Bootstrap Procedure in Individual Bioequivalence
Shao, J.; Kübler, J.; Pigeot, Iris
1999-01-01
Recently, new concepts have been proposed for assessing bioequivalence of two drug formulations, namely the so-called population and individual bioequivalence. Using moment-based and probability-based measures for evaluating the proposed bioequivalence concepts, criteria have been formulated to decide whether two formulations should be regarded as bioequivalent or not. This decision has of course to be based on an adequate statistical method where the Food and Drug Administration (FDA) guidan...
Comment on: ‘A Poisson resampling method for simulating reduced counts in nuclear medicine images’
de Nijs, Robin
2015-07-01
In order to be able to calculate half-count images from already acquired data, White and Lawson published their method based on Poisson resampling. They verified their method experimentally by measurements with a Co-57 flood source. In this comment their results are reproduced and confirmed by a direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all methods, and compared to the theoretical values for a Poisson distribution. Statistical parameters showed the same behavior as in the original note and showed the superiority of the Poisson resampling method. Rounding off before saving of the half count image had a severe impact on counting statistics for counts below 100. Only Poisson resampling was not affected by this, while Gaussian redrawing was less affected by it than Poisson redrawing. Poisson resampling is the method of choice, when simulating half-count (or less) images from full-count images. It simulates correctly the statistical properties, also in the case of rounding off of the images.
Stationary bootstrapping realized volatility under market microstructure noise
Hwang, Eunju; Shin, Dong Wan
2013-01-01
Large-sample validity is proved for stationary bootstrapping of a bias-corrected realized volatility under market microstructure noise, which enables us to construct a bootstrap confidence interval of integrated volatility. A finite-sample simulation shows that the stationary bootstrapping confidence interval outperforms existing ones which are constructed ignoring market microstructure noise or using asymptotic normality for the bias-corrected realized volatility.
Is Bootstrap Really Helpful in Point Process Statistics?
Snethlage, Martin
2000-01-01
There are some papers which describe the use of bootstrap techniques in point process statistics. The aim of the present paper is to show that the form in which bootstrap is used there is dubious. In case of variance estimation of pair correlation function estimators the used bootstrap techniques lead to results which can be obtained simpler without simulation; furthermore, they differ from the desired results. The problem to obtain confidence regions for the intensity function of inhomogeneo...
A PARAMETRIC BOOTSTRAP USING THE FIRST FOURMOMENTS OF THE RESIDUALS
Pierre-Eric Treyens
2007-01-01
We consider linear regression models and we suppose that disturbances are either Gaussian or non Gaussian. Until now, within the framework of the bootstrap, we thought that the error in rejection probability (ERP) had the same rate of convergence with the parametric bootstrap or the nonparametric bootstrap. For linear data generating processes (DGP) we show in this paper that this assertion is false if skewness and/or kurtosis coefficients of the distribution of the disturbances are nonnull. ...
Improving Coverage Accuracy of Block Bootstrap Confidence Intervals
Lee, Stephen M. S.; Lai, P. Y.
2008-01-01
The block bootstrap confidence interval based on dependent data can outperform the computationally more convenient normal approximation only with non-trivial Studentization which, in the case of complicated statistics, calls for highly specialist treatment. We propose two different approaches to improving the accuracy of the block bootstrap confidence interval under very general conditions. The first calibrates the coverage level by iterating the block bootstrap. The second calculates Student...
Regenerative block-bootstrap confidence intervals for tail and extremal indexes
Bertail, Patrice; Clémençon, Stéphan; Tressou, Jessica
2013-01-01
A theoretically sound bootstrap procedure is proposed for building accurate confidence intervals of parameters describing the extremal behavior of instantaneous functionals of a Harris Markov chain, namely the extremal and tail indexes. Regenerative properties of the chain (or of a Nummelin extension of the latter) are here exploited in order to construct consistent estimators of these parameters, following the approach developed in Bertail, Clémençon & Tressou (Extremes, 2009). Their asympto...
Bootstrap Results From the State Space From Representation of the Heath-Jarrow-Morton Model
Ram Bhar; Carl Chiarella
1996-01-01
This paper builds upon the authors' previous work on transformation of the Heath-Jarrow-Morton (HJM) model of the term structure of interest rates to state space form for a fairly general class of volatility specification including stochastic variables. Estimation of this volatility function is at the heart of the identification of the HJM model. The paper develops a bootstrap procedure for the HJM model cast into the non-linear filtering framework to analyse the statistical significance of t...
Testing for time-varying fractional cointegration using the bootstrap approach
Simwaka, Kisu
2012-01-01
Fractional cointegration has attracted interest in time series econometrics in recent years (see among others, Dittmann 2004). According to Engle and Granger (1987), the concept of fractional cointegration was introduced to generalize the traditional cointegration to the long memory framework. Although cointegration tests have been developed for the traditional cointegration framework, these tests do not take into account fractional cointegration. This paper proposes a bootstrap procedure to ...
Bootstrap confidence intervals for the process capability index under half-logistic distribution
Wararit Panichkitkosolkul
2012-01-01
This study concerns the construction of bootstrap confidence intervals for theprocess capability index in the case of half-logistic distribution. The bootstrap confidence intervals applied consist of standard bootstrap confidence interval, percentile bootstrap confidence interval and bias-corrected percentile bootstrap confidence interval. Using Monte Carlo simulations, the estimated coverage probabilities and average widths ofbootstrap confidence intervals are compared, with results showing ...
Bootstrap current fraction scaling for a tokamak reactor design study
International Nuclear Information System (INIS)
Highlights: • New bootstrap current fraction scalings for systems codes were derived by solving the Hirshman–Sigmar model. • Nine self-consistent MHD equilibria were constructed in order to compare the bootstrap current fraction values. • Wilson formula most successfully predicted the bootstrap current fraction, but it requires current density profile index. • The new scaling formulas and IPDG accurately estimated the fBS values for the normal and weakly reversed shear tokamaks. - Abstract: We have derived new bootstrap current fraction scalings for systems codes by solving the Hirshman–Sigmar model, which is valid for arbitrary aspect ratios and collision conditions. The bootstrap current density calculation module in the ACCOME code was used with the matrix inversion method without the large aspect ratio assumption. Nine self-consistent MHD equilibria, which cover conventional, advanced and spherical tokamaks with normal or reversed shear, were constructed using numerical calculations in order to compare the bootstrap current fraction values with those of the new model and all six existing models. The Wilson formula successfully predicted the bootstrap current fraction, but it requires current density profile index for the calculation. The new scaling formulas and IPDG accurately estimated the bootstrap current fraction for the normal and weakly reversed shear tokamaks, regardless of the aspect ratio. However, none of the existing models except the Wilson formula can accurately estimate the bootstrap current fraction for the reversed shear tokamaks, which is promising for the advanced tokamak operation mode
Metastability threshold for anisotropic bootstrap percolation in three dimensions
van Enter, Aernout
2011-01-01
In this paper we analyze several anisotropic bootstrap percolation models in three dimensions. We present the order of magnitude for the metastability threshold for a fairly general class of models. In our proofs we use an adaptation of the technique of dimensional reduction. We find that the order of the metastability threshold is generally determined by the "easiest growth direction" in the model. In contrast to the anisotropic bootstrap percolation in two dimensions, in three dimensions the order of the metatstability threshold for anisotropic bootstrap percolation can be equal to that of isotropic bootstrap percolation.
Confidence Intervals for the Mean: To Bootstrap or Not to Bootstrap
Calzada, Maria E.; Gardner, Holly
2011-01-01
The results of a simulation conducted by a research team involving undergraduate and high school students indicate that when data is symmetric the student's "t" confidence interval for a mean is superior to the studied non-parametric bootstrap confidence intervals. When data is skewed and for sample sizes n greater than or equal to 10, the results…
A bootstrap approach to bump hunting
Silverman, B. W.
1982-01-01
An important question in cluster analysis and pattern recognition is the determination of the number of clusters into which a given population should be divided. Frequently, particularly when certain specific clustering methods are being used, the number of clusters is taken to be equal to the number of modes, or local maxima, in the probability density function underlying the given data set. The use of kernal density estimates in mode estimation is discussed. The test statistic to be used is defined and a bootstrap technique for assessing significance is given. An illustrative application is followed by an examination of the asymptotic behavior of the test statistic.
van de Schoot, Rens; Strohmeier, Dagmar
2011-01-01
In the present paper, the application of a parametric bootstrap procedure, as described by van de Schoot, Hoijtink, and Dekovic (2010), will be applied to demonstrate that a direct test of an informative hypothesis offers more informative results compared to testing traditional null hypotheses against catch-all rivals. Also, more power can be…
Resampling of an Image by Block-Based Interpolation or Decimation with Compensation
Directory of Open Access Journals (Sweden)
M. Kapinos
2000-06-01
Full Text Available Due to multiple standards on digital coding of image it is expectedthat conversion from one picture format to another will be quitenecessary for display or recording of different format sources.Conventional approach of 2-D sampling rate conversion by polyphasefilters requires relatively large memory and computational power.Therefore, a new efficient method for image resampling has beenpresented. The proposed approach performs resampling block by blockwith overlap. To minimize the overlap special block interpolationkernels are used, with one pixel overlap gives satisfactory result formost of practical images. Proposed method can be efficiently applied toimage communication systems where block transforms are used for datacompression.
A Robust Kalman Framework with Resampling and Optimal Smoothing
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Thomas Kautz
2015-02-01
Full Text Available The Kalman filter (KF is an extremely powerful and versatile tool for signal processing that has been applied extensively in various fields. We introduce a novel Kalman-based analysis procedure that encompasses robustness towards outliers, Kalman smoothing and real-time conversion from non-uniformly sampled inputs to a constant output rate. These features have been mostly treated independently, so that not all of their benefits could be exploited at the same time. Here, we present a coherent analysis procedure that combines the aforementioned features and their benefits. To facilitate utilization of the proposed methodology and to ensure optimal performance, we also introduce a procedure to calculate all necessary parameters. Thereby, we substantially expand the versatility of one of the most widely-used filtering approaches, taking full advantage of its most prevalent extensions. The applicability and superior performance of the proposed methods are demonstrated using simulated and real data. The possible areas of applications for the presented analysis procedure range from movement analysis over medical imaging, brain-computer interfaces to robot navigation or meteorological studies.
Building Intuitions about Statistical Inference Based on Resampling
Watson, Jane; Chance, Beth
2012-01-01
Formal inference, which makes theoretical assumptions about distributions and applies hypothesis testing procedures with null and alternative hypotheses, is notoriously difficult for tertiary students to master. The debate about whether this content should appear in Years 11 and 12 of the "Australian Curriculum: Mathematics" has gone on for…
High βp bootstrap tokamak reactor
International Nuclear Information System (INIS)
Basic characteristics of a steady state tokamak fusion reactor is presented. The minimum required energy multiplication factor Q is found to be 20 to 30 for the feasibility of the fusion reactor. Such a high Q steady state tokamak operation is possible, within our present knowledge of the operational constraints and the current drive physics, when a large fraction of the plasma current is carried by the bootstrap current. Operation at high βp (≥2.0) and high qψ (=4-5) with relatively small εβp (3) and fusion output power (2.5 GW) and is consistent with the present knowledges of the plasma physics of the tokamak, namely the Troyon limit, the energy confinement scalings, the bootstrap current, the current drive efficiency (NB current drive with the total power of 70 MW and the beam energy of 1 MeV) with a favorable aspect on the formation of the cold and dense diverter plasma-condition. From the economical aspect of the tokamak fusion reactor, a more compact reactor is favorable. The use of the high field magnet with Bmax = 16T (for example Ti-doped Nb3Sn conductor) enables to reduce the total machine size to 50% of the above-described conventional design, namely Rp = 7m, Vp = 760m-3, PF = 2.8 GW. (author)
Physics issues of high bootstrap current tokamaks
International Nuclear Information System (INIS)
Physics issues of a tokamak plasma with a hollow current profile produced by a large bootstrap current are discussed based on experiments in JT-60U. An internal transport barrier for both ions and electrons was obtained just inside the radius of zero magnetic shear in JT-60U. Analysis of the toroidal ITG microinstability by toroidal particle simulation shows that weak and negative shear reduces the toroidal coupling and suppresses the ITG mode. A hard beta limit was observed in JT-60U negative shear experiments. Ideal MHD mode analysis shows that the n = 1 pressure-driven kink mode is a plausible candidate. One of the methods to improve the beta limit against the kink mode is to widen the negative shear region, which can induce a broader pressure profile resulting in a higher beta limit. The TAE mode for the hollow current profile is less unstable than that for the monotonic current profile. The reason is that the continuum gaps near the zero shear region are not aligned when the radius of qmin is close to the region of high ∇ne. Finally, a method for stable start-up for a plasma with a hollow current profile is describe, and stable sustainment of a steady-state plasma with high bootstrap current is discussed. (Author)
MHD equilibrium property with bootstrap current in heliotron plasmas
International Nuclear Information System (INIS)
We study the properties of MHD equilibrium with self-consistent bootstrap current for a heliotron type device. We show the possibility that MHD equilibrium beta limit with consistent bootstrap current might significantly decrease in the low collisional regime comparing with currentless case depending on the vertical field control methods in finite beta and magnetic configurations. (author)
Discharges with high bootstrap current fraction on Tore Supra
International Nuclear Information System (INIS)
This document deals with bootstrap current non-inductively driving a fraction of the total current. Non-inductive current density profile is determined on Tore Supra and high bootstrap current fraction regimes in Tore Supra are analysed. (TEC). 11 refs., 3 figs
FWEH induced high bootstrap current on Tore Supra
International Nuclear Information System (INIS)
Bootstrap current is regarded as a good candidate to sustain a large fraction of the plasma current, in the so-called open-quotes advancedclose quotes regimes of a tokamak reactor. It is thus important to study the stability of such discharges and to control them. By means of fast wave electron heating (FWEH, up to 9.5 MW), stationary high bootstrap discharges (during 5 seconds, ∼40%) were routinely obtained on Tore Supra. The bootstrap profile is computed with a matrix formulation (1,2) and is directly compared to the experimental determination of the non-inductive current. The simulation of the loop voltage either with the code CRONOS (1D current diffusion code) using the profile of bootstrap current, or with the knowledge of the resistivity, allows also a self consistent determination of the bootstrap current. The bootstrap induced by the FWEH is mainly due to the central pressure electron gradient (the central power deposition strongly peaks the electronic temperature). A 0D study shows that the bootstrap current (Ibs) varies linearly with the poloidal beta (Ibs/Ip∼Cbsβp). The effect of various plasma parameters (toroidal field Bt, line-integrated density nl, ion and electron temperature, plasma current Ip) on the bootstrap profile, and fraction are analysed. copyright 1997 American Institute of Physics
On bootstrap sample size in extreme value theory
J.L. Geluk (Jaap); L.F.M. de Haan (Laurens)
2002-01-01
textabstractIt has been known for a long time that for bootstrapping the probability distribution of the maximum of a sample consistently, the bootstrap sample size needs to be of smaller order than the original sample size. See Jun Shao and Dongsheng Tu (1995), Ex. 3.9,p. 123. We show that the same
Bootstrap Estimates of Standard Errors in Generalizability Theory
Tong, Ye; Brennan, Robert L.
2007-01-01
Estimating standard errors of estimated variance components has long been a challenging task in generalizability theory. Researchers have speculated about the potential applicability of the bootstrap for obtaining such estimates, but they have identified problems (especially bias) in using the bootstrap. Using Brennan's bias-correcting procedures…
Bootstrapping and Bartlett corrections in the cointegrated VAR model
P.H. Omtzigt; S. Fachin
2003-01-01
The small sample properties of tests on long-run coefficients in cointegrated systems are still a matter of concern to applied econometricians. We compare the performance of the Bartlett correction, the bootstrap and the fast double bootstrap for tests on ccointegration parameters in the maximum lik
Learning web development with Bootstrap and AngularJS
Radford, Stephen
2015-01-01
Whether you know a little about Bootstrap or AngularJS, or you're a complete beginner, this book will enhance your capabilities in both frameworks and you'll build a fully functional web app. A working knowledge of HTML, CSS, and JavaScript is required to fully get to grips with Bootstrap and AngularJS.
Resampling-based approaches to study variation in morphological modularity.
Directory of Open Access Journals (Sweden)
Carmelo Fruciano
Full Text Available Modularity has been suggested to be connected to evolvability because a higher degree of independence among parts allows them to evolve as separate units. Recently, the Escoufier RV coefficient has been proposed as a measure of the degree of integration between modules in multivariate morphometric datasets. However, it has been shown, using randomly simulated datasets, that the value of the RV coefficient depends on sample size. Also, so far there is no statistical test for the difference in the RV coefficient between a priori defined groups of observations. Here, we (1, using a rarefaction analysis, show that the value of the RV coefficient depends on sample size also in real geometric morphometric datasets; (2 propose a permutation procedure to test for the difference in the RV coefficient between a priori defined groups of observations; (3 show, through simulations, that such a permutation procedure has an appropriate Type I error; (4 suggest that a rarefaction procedure could be used to obtain sample-size-corrected values of the RV coefficient; and (5 propose a nearest-neighbor procedure that could be used when studying the variation of modularity in geographic space. The approaches outlined here, readily extendable to non-morphometric datasets, allow study of the variation in the degree of integration between a priori defined modules. A Java application--that will allow performance of the proposed test using a software with graphical user interface--has also been developed and is available at the Morphometrics at Stony Brook Web page (http://life.bio.sunysb.edu/morph/.
Bootstrap current due to shear of magnetic field stochasticity
International Nuclear Information System (INIS)
The 'bootstrap' current is a fundamental effect in toroidal magnetic confinement. It is shown that the electron current in stochastic magnetic field causes not only anomalous electron heat transport, but also novel currents, termed 'anomalous bootstrap' in order to bring up the analogy with the well-known effect in the neoclassical theory. Due to the magnetic fluctuations an additional bootstrap current appears. Its value is proportional to the derivative of square of the magnetic fluctuations, the radial electric field and ratio of streaming velocity to thermal one for collisionless case. The obtained bootstrap current can be comparable with the Ohmic current. In the collisional case, in contrast to the collisionless case, the value of bootstrap current does not depend on the magnitude of the averaged velocity, but its direction is determined by the streaming velocity sign. (J.P.N.)
Bootstrap performance profiles in stochastic algorithms assessment
International Nuclear Information System (INIS)
Optimization with stochastic algorithms has become a relevant research field. Due to its stochastic nature, its assessment is not straightforward and involves integrating accuracy and precision. Performance profiles for the mean do not show the trade-off between accuracy and precision, and parametric stochastic profiles require strong distributional assumptions and are limited to the mean performance for a large number of runs. In this work, bootstrap performance profiles are used to compare stochastic algorithms for different statistics. This technique allows the estimation of the sampling distribution of almost any statistic even with small samples. Multiple comparison profiles are presented for more than two algorithms. The advantages and drawbacks of each assessment methodology are discussed
Conformal bootstrap, universality and gravitational scattering
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Steven Jackson
2015-12-01
Full Text Available We use the conformal bootstrap equations to study the non-perturbative gravitational scattering between infalling and outgoing particles in the vicinity of a black hole horizon in AdS. We focus on irrational 2D CFTs with large c and only Virasoro symmetry. The scattering process is described by the matrix element of two light operators (particles between two heavy states (BTZ black holes. We find that the operator algebra in this regime is (i universal and identical to that of Liouville CFT, and (ii takes the form of an exchange algebra, specified by an R-matrix that exactly matches the scattering amplitude of 2+1 gravity. The R-matrix is given by a quantum 6j-symbol and the scattering phase by the volume of a hyperbolic tetrahedron. We comment on the relevance of our results to scrambling and the holographic reconstruction of the bulk physics near black hole horizons.
On Bootstrap Percolation in Living Neural Networks
Amini, Hamed
2009-01-01
Recent experimental studies of living neural networks reveal that their global activation induced by electrical stimulation can be explained using the concept of bootstrap percolation on a directed random network. The experiment consists in activating externally an initial random fraction of the neurons and observe the process of firing until its equilibrium. The final portion of neurons that are active depends in a non linear way on the initial fraction. The main result of this paper is a theorem which enables us to find the asymptotic of final proportion of the fired neurons in the case of random directed graphs with given node degrees as the model for interacting network. This gives a rigorous mathematical proof of a phenomena observed by physicists in neural networks.
Kapetanios, George; Weeks, Melvyn J.
2003-01-01
We consider an alternative use of simulation in the context of using the Likelihood-Ratio statistic to test non-nested models. To date simulation has been used to estimate the Kullback-Leibler measure of closeness between two densities, which in turn ?mean adjusts? the Likelihood-Ratio statistic. Given that this adjustment is still based upon asymptotic arguments, an alternative procedure is to utilise bootstrap procedures to construct the empirical density. To our knowledge this study re...
Bootstrap consistency for general semiparametric M-estimation
Cheng, Guang
2010-10-01
Consider M-estimation in a semiparametric model that is characterized by a Euclidean parameter of interest and an infinite-dimensional nuisance parameter. As a general purpose approach to statistical inferences, the bootstrap has found wide applications in semiparametric M-estimation and, because of its simplicity, provides an attractive alternative to the inference approach based on the asymptotic distribution theory. The purpose of this paper is to provide theoretical justifications for the use of bootstrap as a semiparametric inferential tool. We show that, under general conditions, the bootstrap is asymptotically consistent in estimating the distribution of the M-estimate of Euclidean parameter; that is, the bootstrap distribution asymptotically imitates the distribution of the M-estimate. We also show that the bootstrap confidence set has the asymptotically correct coverage probability. These general onclusions hold, in particular, when the nuisance parameter is not estimable at root-n rate, and apply to a broad class of bootstrap methods with exchangeable ootstrap weights. This paper provides a first general theoretical study of the bootstrap in semiparametric models. © Institute of Mathematical Statistics, 2010.
Properties of bootstrap tests for N-of-1 studies
Lin, Sharon Xiaowen; Morrison, Leanne; Smith, Peter; Hargood, Charlie; Weal, Mark; Yardley, Lucy
2016-01-01
N-of-1 study designs involve the collection and analysis of repeated measures data from an individual not using an intervention and using an intervention. This study explores the use of semi-parametric and parametric bootstrap tests in the analysis of N-of-1 studies under a single time series framework in the presence of autocorrelation. When the Type I error rates of bootstrap tests are compared to Wald tests, our results show that the bootstrap tests have more desirable properties. We compa...
Xu, Kuan-Man
2006-01-01
A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.
On a Second-Order Asymptotic Property of the Bayesian Bootstrap Mean
Weng, Chung-Sing
1989-01-01
It is shown that the Bayesian bootstrap approximation to the posterior distribution of the unknown mean (with respect to a Dirichlet process prior) is more accurate than both the standard normal approximation and the bootstrap approximation. It is also shown that the Bayesian bootstrap approximation to the sampling distribution of the sample average is not as accurate as the bootstrap approximation.
Classified-edge guided depth resampling for multi-view coding
Lu, Yu; Zhou, Yang; Chen, Hua-hua
2016-01-01
A new depth resampling for multi-view coding is proposed in this paper. At first, the depth video is downsampled by median filtering before encoding. After decoding, the classified edges, including credible edge and probable edge from the aligned texture image and the depth image, are interpolated by the selected diagonal pair, whose intensity difference is the minimum among four diagonal pairs around edge pixel. According to different category of edge, the intensity difference is measured by either real depth or percentage depth without any parameter setting. Finally, the resampled depth video and the decoded full-resolution texture video are synthesized into virtual views for the performance evaluation. Experiments on the platform of multi-view high efficiency video coding (HEVC) demonstrate that the proposed method is superior to the contrastive methods in terms of visual quality and rate distortion (RD) performance.
Re-sampling of continuous scanning LDV data for ODS extraction
Castellini, P.; Sopranzetti, F.; Martarelli, M.
2016-05-01
The paper presents a method for processing data obtained by Continuous Scanning Laser Doppler Vibrometry (CSLDV) that makes it possible to measure vibrations combining spatial and temporal information. Since the laser continuously scans the structure under test over time and space, it measures a vibration signal modulated by the Operational Deflection Shape (ODS) of the structure. CSLDV time history can then be re-sampled at an arbitrary spatial resolution in order to recover the vibration data at several positions on the trajectory swept by the laser. The main drawback of such method is that the actual sampling rate of the re-sampled vibration signals is dictated by frequencies of the mirrors, which determine the laser scanning speed. The paper presents a method for the automatic recognition of "aliased" natural frequencies and recovery of the actual un-aliased natural frequencies. Once those frequencies are determined, the corresponding ODSs are recovered.
Directory of Open Access Journals (Sweden)
Mourad Mroua
2014-06-01
Full Text Available This paper examines the impact of estimation errors on the financial portfolios optimization processes and investigates the controversy problem of the international and domestic optimal diversification strategies choice from an American investor’s point of view. We introduce the concept of portfolio resampling method and we use the nonparametric stochastic dominance approach based simulated p-values to define an optimal diversification choice. Estimation errors visualization shows that changes in input parameters imply large changes in portfolio composition and reveals considerably modification of MV efficient frontiers shape. The findings show that there exists substantial evidence of the international global diversification benefits. Risk-adverse American investor with an increasing utility function prefers the global international resampled diversification strategy. We find that domestic diversification beats only international major and emerging markets diversification. Dominance relationships between the entirely diversification strategies change according to the risk-aversion coefficient.
Compression, restoration, resampling, ‘compressive sensing’: fast transforms in digital imaging
International Nuclear Information System (INIS)
Transform image processing methods are methods that work in domains of image transforms, such as discrete fourier, discrete cosine, wavelet and alike. They are the basic tools in image compression, image restoration, image resampling and geometrical transformations and can be traced back to the early 1970s. The paper presents a review of these methods with emphasis on their comparison and relationships, from the very first steps of transform image compression methods to adaptive and local adaptive transform domain filters for image restoration, to methods of precise image resampling and image reconstruction from sparse samples and up to the ‘compressive sensing’ approach that has gained popularity in the last few years. The review has a tutorial character and purpose. (topical review)
Bootstrap current of fast ions in neutral beam injection heating
International Nuclear Information System (INIS)
The bootstrap current of fast ions produced by the neutral beam injection is investigated in a large aspect ratio tokamak with circular cross-section under specific parameters. The bootstrap current density distribution and the total bootstrap current are figured out. In addition, the beam bootstrap current always accompanies the electron return current due to the parallel momentum transfer from fast ions. With the electron return current considered, the net current density obviously decreases due to electron return current, at the same time the peak of current moves towards the centre plasma. Numerical results show that the value of the net current depends sensitively not only on the angle of the neutral beam injection but also on the ratio of the velocity of fast ions to the critical velocity: the value of net current is small for the neutral beam parallel injection but increases multipliedly for perpendicular injection, and increases with beam energy increasing. (authors)
Bootstrap current of fast ions in neutral beam injection heating
International Nuclear Information System (INIS)
The bootstrap current of fast ions produced by neutral beam injection (NBI) is investigated in a large-aspect-ratio tokamak with circular cross-section under specific parameters. The bootstrap current density distribution and the total bootstrap current are reported. In addition, the beam bootstrap current always accompanies the electron return current due to the parallel momentum transfer from fast ions. With the electron return current taken into consideration, the net current density obviously decreases; at the same time, the peak of the current moves towards the central plasma. Numerical results show that the value of the net current depends sensitively not only on the angle of the NBI but also on the ratio of the velocity of fast ions to the critical velocity: the value of the net current is small for neutral beam parallel injection, but increases severalfold for perpendicular injection, and increases with increasing beam energy. (paper)
'Bootstrap' Configuration for Multistage Pulse-Tube Coolers
Nguyen, Bich; Nguyen, Lauren
2008-01-01
A bootstrap configuration has been proposed for multistage pulse-tube coolers that, for instance, provide final-stage cooling to temperatures as low as 20 K. The bootstrap configuration supplants the conventional configuration, in which customarily the warm heat exchangers of all stages reject heat at ambient temperature. In the bootstrap configuration, the warm heat exchanger, the inertance tube, and the reservoir of each stage would be thermally anchored to the cold heat exchanger of the next warmer stage. The bootstrapped configuration is superior to the conventional setup, in some cases increasing the 20 K cooler's coefficient of performance two-fold over that of an otherwise equivalent conventional layout. The increased efficiency could translate into less power consumption, less cooler mass, and/or lower cost for a given amount of cooling.
Filter and modified stepwedge bootstrap sensitometry in medical radiography
Energy Technology Data Exchange (ETDEWEB)
Yoshida, Akira
1988-05-01
Two new bootstrap methods for determining characteristic curves of radiographic screen/film systems are presented : filter bootstrap sensitometry and modified stepwedge bootstrap sensitometry. Both are intensity-scale sensitometries since the radiation intensity can be varied through use of a combination of inverse square and metal filters. Characteristic curves obtained by these methods are compared with those from screen/film systems using inverse square sensitometry as a reference standard of accuracy. The precision of all three methods is better than +- 2 % with agreement among generally being within 3 % over the useful density range. By these bootstrap methods, it is possible to obtain characteristic curves agreeing well with those using the inverse square method for a relatively short distance, and make radiographic sensitometry practical and convenient at most medical institutions.
On the range of validity of the autoregressive sieve bootstrap
Kreiss, Jens-Peter; Politis, Dimitris N; 10.1214/11-AOS900
2012-01-01
We explore the limits of the autoregressive (AR) sieve bootstrap, and show that its applicability extends well beyond the realm of linear time series as has been previously thought. In particular, for appropriate statistics, the AR-sieve bootstrap is valid for stationary processes possessing a general Wold-type autoregressive representation with respect to a white noise; in essence, this includes all stationary, purely nondeterministic processes, whose spectral density is everywhere positive. Our main theorem provides a simple and effective tool in assessing whether the AR-sieve bootstrap is asymptotically valid in any given situation. In effect, the large-sample distribution of the statistic in question must only depend on the first and second order moments of the process; prominent examples include the sample mean and the spectral density. As a counterexample, we show how the AR-sieve bootstrap is not always valid for the sample autocovariance even when the underlying process is linear.
Robust parametric bootstrap test with MOM estimator: An alternative to independent sample t-test
Harun, Nurul Hanis; Yusof, Zahayu Md
2014-12-01
Normality and homogeneity are two major assumptions that need to be fulfilled when using independent sample t-test. However, not all data encompassed with these assumptions. Consequently, the result produced by independent sample t-test becomes invalid. Therefore, the alternative is to use robust statistical procedure in handling the problems of nonnormality and variances heterogeneity. This study proposed to use Parametric Bootstrap test with popular robust estimators, MADn and Tn which empirically determines the amount of trimming. The Type I error rates produced by each procedure were examined and compared with classical parametric test and nonparametric test namely independent sample t-test and Mann Whitney test, respectively. 5000 simulated data sets are used in this study in order to generate the Type I error for each procedure. The findings of this study indicate that the Parametric Bootstrap test with MADn and Tn produces the best Type I error control compared to the independent sample t-test and the Mann Whitney test under nonnormal distribution, heterogeneous variances and unbalanced design. Then, the performance of each procedure was demonstrated using real data.
Impacts of DEM resolution, source, and resampling technique on SWAT-simulated streamflow
Tan, M. L.; D. L. Ficklin; Dixon, B; Ibrahim, A. L.; Yusop, Z.; Chaplot, Vincent
2015-01-01
The sensitivity of streamflow simulated with the Soil and Water Assessment Tool (SWAT) model to Digital Elevation Model (DEM) resolution, DEM source and DEM resampling technique is still poorly understood. The objective of this study is to compare SWAT model streamflow estimates in the Johor River Basin ORB), Malaysia for DEMs differing in resolution (from 20 to 1500 m), sources (Shuttle Radar Topography Mission: SRTM v4.1, Advanced Space-borne Thermal Emission and Reflection Radiometer: ASTE...
Automotive FMCW Radar-enhanced Range Estimation via a Local Resampling Fourier Transform
Cailing Wang; Huajun Liu; Guang Han; Xiaoyuan Jing
2016-01-01
In complex traffic scenarios, more accurate measurement and discrimination for an automotive frequency-modulated continuous-wave (FMCW) radar is required for intelligent robots, driverless cars and driver-assistant systems. A more accurate range estimation method based on a local resampling Fourier transform (LRFT) for a FMCW radar is developed in this paper. Radar signal correlation in the phase space sees a higher signal-noise-ratio (SNR) to achieve more accurate ranging, and the LRFT - whi...
Bootstrapped Multinomial Logistic Regression on Apnea Detection Using ECG Data
Sanabila, Hadaiq R.; Fanany, Mohamad Ivan; Jatmiko, Wisnu; Arymurthy, Aniati Murni
2010-01-01
In designing a classification system, one of the most important considerations is how optimal the classifier will adapt and give best generalization when it is given data from unknown model distribution. Unlike linear regression, logistic regression has no simple formula to assess its generalization ability. In such cases, bootstrapping offers an advantage over analytical methods thanks to its simplicity. This paper presents an analysis of bootstrapped multinomial logistic regression appli...
Bootstrap transition to high beta equilibrium in helical system
International Nuclear Information System (INIS)
It is shown theoretically and computationally that helical magnetic field, produced by continuous winding helical coils and without the toroidal coil, can sustain MHD stable high beta plasma. Pressure driven toroidal current (bootstrap current) cancels the external magnetic field and reduces the MHD potential energy, depending on the plasma beta values. Ramp-up of heating power input induces bootstrap transition to higher beta plasmas with flat-top pressure profiles. Helical pitch parameter dependence of MHD stability is analyzed. (author)
Bootstrap current for tokamak plasma with anisotropic electron temperature
International Nuclear Information System (INIS)
The neoclassical bootstrap current for an anisotropic plasma has been studied in a large aspect-ratio tokamak. The enhancement factor due to the temperature anisotropy in the equilibrium electron distribution function is explicitly calculated, and is shown to reach to about 1.5 when the perpendicular temperature is twice as large as the parallel temperature. This bootstrap current is also predicted to have the component proportional to the radial electric field even in an axisymmetric magnetic field. (author)
Bootstrapping the statistical uncertainties of NN scattering data
International Nuclear Information System (INIS)
We use the Monte Carlo bootstrap as a method to simulate pp and np scattering data below pion production threshold from an initial set of over 6700 experimental mutually 3σ consistent data. We compare the results of the bootstrap, with 1020 statistically generated samples of the full database, with the standard covariance matrix method of error propagation. No significant differences in scattering observables and phase shifts are found. This suggests alternative strategies for propagating errors of nuclear forces in nuclear structure calculations
Generalized bootstrap equations and possible implications for the NLO Odderon
Energy Technology Data Exchange (ETDEWEB)
Bartels, J. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Vacca, G.P. [INFN, Sezione di Bologna (Italy)
2013-07-15
We formulate and discuss generalized bootstrap equations in nonabelian gauge theories. They are shown to hold in the leading logarithmic approximation. Since their validity is related to the self-consistency of the Steinmann relations for inelastic production amplitudes they can be expected to be valid also in NLO. Specializing to the N=4 SYM, we show that the validity in NLO of these generalized bootstrap equations allows to find the NLO Odderon solution with intercept exactly at one.
Bootstrap tests in linear models with many regressors
Patrick Richard
2014-01-01
This paper is concerned with bootstrap hypothesis testing in high dimensional linear regression models. Using a theoretical framework recently introduced by Anatolyev (2012), we show that bootstrap F, LR and LM tests are asymptotically valid even when the numbers of estimated parameters and tested restrictions are not asymptotically negligible fractions of the sample size. These results are derived for models with iid error terms, but Monte Carlo evidence suggests that they extend to the wild...
Spectrum of local boundary operators from boundary form factor bootstrap
Szots, M
2007-01-01
Using the recently introduced boundary form factor bootstrap equations, we map the complete space of their solutions for the boundary version of the scaling Lee-Yang model and sinh-Gordon theory. We show that the complete space of solutions, graded by the ultraviolet behaviour of the form factors can be brought into correspondence with the spectrum of local boundary operators expected from boundary conformal field theory, which is a major evidence for the correctness of the boundary form factor bootstrap framework.
BOOTSTRAP-BASED STATISTICAL THRESHOLDING FOR MEG SOURCE RECONSTRUCTION IMAGES
Sekihara, Kensuke; Sahani, Maneesh; Nagarajan, Srikantan S.
2004-01-01
This paper proposes a bootstrap-based statistical method for extracting target source activities from MEG/EEG source reconstruction results. The method requires measurements in a control condition, which contains only non-target source activities. The method derives, at each pixel location, an empirical probability distribution of the non-target source activity using bootstrapped reconstruction obtained from the control period. The statistical threshold that can extract the target source acti...
On the range of validity of the autoregressive sieve bootstrap
Kreiss, Jens-Peter; Paparoditis, Efstathios; Politis, Dimitris N.
2012-01-01
We explore the limits of the autoregressive (AR) sieve bootstrap, and show that its applicability extends well beyond the realm of linear time series as has been previously thought. In particular, for appropriate statistics, the AR-sieve bootstrap is valid for stationary processes possessing a general Wold-type autoregressive representation with respect to a white noise; in essence, this includes all stationary, purely nondeterministic processes, whose spectral density is everywhere positive....
Energy Technology Data Exchange (ETDEWEB)
Klan, M.S.; Shankle, S.A.; Kellogg, M.A.
1990-06-01
In this study a set of multicomponent case weights applicable to residential survey information were prepared for the Bonneville Power Administration (BPA) by the Pacific Northwest Laboratory (PNL). These case weights were prepared for the 1985 resample of respondents of an earlier BPA residential energy survey -- the original 1983 survey and subsequent surveys administered to the 1985 PNWRES resample were designed to gather information from households concerning their use of energy and related data. The PNWRES samples were drawn based on stratified random sampling techniques, that allow the survey results to represent the characteristics of the overall Pacific Northwest population of residential utility accounts. In order to determine the characteristics of the population, however, the survey results must be appropriately weighted. Case weights were developed for 1983 PNWRES by Lou Harris and Associates, Inc. This report briefly documents PNL's extension of the weighting methodology to the subsequent 1985 PNWRES resample, and describes the resulting caseweights generated by PNL. 9 refs., 5 tabs.
Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca
2015-01-01
Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights. PMID:26274960
He, Qingbo; Wang, Jun; Hu, Fei; Kong, Fanrang
2013-10-01
The diagnosis of train bearing defects plays a significant role to maintain the safety of railway transport. Among various defect detection techniques, acoustic diagnosis is capable of detecting incipient defects of a train bearing as well as being suitable for wayside monitoring. However, the wayside acoustic signal will be corrupted by the Doppler effect and surrounding heavy noise. This paper proposes a solution to overcome these two difficulties in wayside acoustic diagnosis. In the solution, a dynamically resampling method is firstly presented to reduce the Doppler effect, and then an adaptive stochastic resonance (ASR) method is proposed to enhance the defective characteristic frequency automatically by the aid of noise. The resampling method is based on a frequency variation curve extracted from the time-frequency distribution (TFD) of an acoustic signal by dynamically minimizing the local cost functions. For the ASR method, the genetic algorithm is introduced to adaptively select the optimal parameter of the multiscale noise tuning (MST)-based stochastic resonance (SR) method. The proposed wayside acoustic diagnostic scheme combines signal resampling and information enhancement, and thus is expected to be effective in wayside defective bearing detection. The experimental study verifies the effectiveness of the proposed solution.
Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping.
Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca
2015-01-01
Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights. PMID:26274960
Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping
Directory of Open Access Journals (Sweden)
Irene Borra-Serrano
2015-08-01
Full Text Available Unmanned aerial vehicles (UAVs combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights.
Conformal collider physics from the lightcone bootstrap
Li, Daliang; Meltzer, David; Poland, David
2016-02-01
We analytically study the lightcone limit of the conformal bootstrap equations for 4-point functions containing global symmetry currents and the stress tensor in 3d CFTs. We show that the contribution of the stress tensor to the anomalous dimensions of large spin double-twist states is negative if and only if the conformal collider physics bounds are satisfied. In the context of AdS/CFT these results indicate a relation between the attractiveness of AdS gravity and positivity of the CFT energy flux. We also study the contribution of non-Abelian conserved currents to the anomalous dimensions of double- twist operators, corresponding to the gauge binding energy of 2-particle states in AdS. We show that the representation of the double-twist state determines the sign of the gauge binding energy if and only if the coefficients appearing in the current 3-point function satisfies a similar bound, which is equivalent to an upper bound on the charge flux asymmetry of the CFT.
An Algebraic Approach to the Analytic Bootstrap
Alday, Luis F
2015-01-01
We develop an algebraic approach to the analytic bootstrap in CFTs. By acting with the Casimir operator on the crossing equation we map the problem of doing large spin sums to any desired order to the problem of solving a set of recursion relations. We compute corrections to the anomalous dimension of large spin operators due to the exchange of a primary and its descendants in the crossed channel and show that this leads to a Borel-summable expansion. We analyse higher order corrections to the microscopic CFT data in the direct channel and its matching to infinite towers of operators in the crossed channel. We apply this method to the critical $O(N)$ model. At large $N$ we reproduce the first few terms in the large spin expansion of the known two-loop anomalous dimensions of higher spin currents in the traceless symmetric representation of $O(N)$ and make further predictions. At small $N$ we present the results for the truncated large spin expansion series of anomalous dimensions of higher spin currents.
Bootstrap inference longitudinal semiparametric regression model
Pane, Rahmawati; Otok, Bambang Widjanarko; Zain, Ismaini; Budiantara, I. Nyoman
2016-02-01
Semiparametric regression contains two components, i.e. parametric and nonparametric component. Semiparametric regression model is represented by yt i=μ (x˜'ti,zt i)+εt i where μ (x˜'ti,zt i)=x˜'tiβ ˜+g (zt i) and yti is response variable. It is assumed to have a linear relationship with the predictor variables x˜'ti=(x1 i 1,x2 i 2,…,xT i r) . Random error εti, i = 1, …, n, t = 1, …, T is normally distributed with zero mean and variance σ2 and g(zti) is a nonparametric component. The results of this study showed that the PLS approach on longitudinal semiparametric regression models obtain estimators β˜^t=[X'H(λ)X]-1X'H(λ )y ˜ and g˜^λ(z )=M (λ )y ˜ . The result also show that bootstrap was valid on longitudinal semiparametric regression model with g^λ(b )(z ) as nonparametric component estimator.
Remarks on bootstrap percolation in metric networks
International Nuclear Information System (INIS)
We examine bootstrap percolation in d-dimensional, directed metric graphs in the context of recent measurements of firing dynamics in 2D neuronal cultures. There are two regimes depending on the graph size N. Large metric graphs are ignited by the occurrence of critical nuclei, which initially occupy an infinitesimal fraction, f* → 0, of the graph and then explode throughout a finite fraction. Smaller metric graphs are effectively random in the sense that their ignition requires the initial ignition of a finite, unlocalized fraction of the graph, f* > 0. The crossover between the two regimes is at a size N* which scales exponentially with the connectivity range λ like N* ∼ exp λd. The neuronal cultures are finite metric graphs of size N ≅ 105 - 106, which, for the parameters of the experiment, is effectively random since N *. This explains the seeming contradiction in the observed finite f* in these cultures. Finally, we discuss the dynamics of the firing front
Quantum bootstrapping via compressed quantum Hamiltonian learning
International Nuclear Information System (INIS)
A major problem facing the development of quantum computers or large scale quantum simulators is that general methods for characterizing and controlling are intractable. We provide a new approach to this problem that uses small quantum simulators to efficiently characterize and learn control models for larger devices. Our protocol achieves this by using Bayesian inference in concert with Lieb–Robinson bounds and interactive quantum learning methods to achieve compressed simulations for characterization. We also show that the Lieb–Robinson velocity is epistemic for our protocol, meaning that information propagates at a rate that depends on the uncertainty in the system Hamiltonian. We illustrate the efficiency of our bootstrapping protocol by showing numerically that an 8 qubit Ising model simulator can be used to calibrate and control a 50 qubit Ising simulator while using only about 750 kilobits of experimental data. Finally, we provide upper bounds for the Fisher information that show that the number of experiments needed to characterize a system rapidly diverges as the duration of the experiments used in the characterization shrinks, which motivates the use of methods such as ours that do not require short evolution times. (fast track communication)
Conformal Collider Physics from the Lightcone Bootstrap
Li, Daliang; Poland, David
2015-01-01
We analytically study the lightcone limit of the conformal bootstrap equations for 4-point functions containing global symmetry currents and the stress tensor in 3d CFTs. We show that the contribution of the stress tensor to the anomalous dimensions of large spin double-twist states is negative if and only if the conformal collider physics bounds are satisfied. In the context of AdS/CFT these results indicate a relation between the attractiveness of AdS gravity and positivity of the CFT energy flux. We also study the contribution of non-Abelian conserved currents to the anomalous dimensions of double-twist operators, corresponding to the gauge binding energy of 2-particle states in AdS. We show that the representation of the double-twist state determines the sign of the gauge binding energy if and only if the coefficient appearing in the current 3-point function satisfies a similar bound, which is equivalent to an upper bound on the charge flux asymmetry of the CFT.
Bootstrapping Object Coreferencing on the Semantic Web
Institute of Scientific and Technical Information of China (English)
Wei Hu; Yu-Zhong Qu; Xing-Zhi Sun
2011-01-01
An object on the Semantic Web is likely to be denoted with several URIs by different parties.Object coreferencing is a process to identify "equivalent" URIs of objects for achieving a better Data Web.In this paper,we propose a bootstrapping approach for object coreferencing on the Semantic Web.For an object URI,we firstly establish a kernel that consists of semantically equivalent URIs from the same-as,(inverse) functional properties and (max-)cardinalities,and then extend the kernel with respect to the textual descriptions (e.g.,labels and local names) of URIs.We also propose a trustworthiness-based method to rank the coreferent URIs in the kernel as well as a similarity-based method for ranking the URIs in the extension of the kernel.We implement the proposed approach,called ObjectCoref,on a large-scale dataset that contains 76 million URIs collected by the Falcons search engine until 2008.The evaluation on precision,relative recall and response time demonstrates the feasibility of our approach.Additionally,we apply the proposed approach to investigate the popularity of the URI alias phenomenon on the current Semantic Web.
Tie the straps: Uniform bootstrap con fidence bands for bounded influence curve estimators
Härdle, Wolfgang Karl; Ritov, Ya'Acov; Wang, Weining
2013-01-01
We consider theoretical bootstrap coupling techniques for nonparametric robust smoothers and quantile regression, and verify the bootstrap improvement. To cope with curse of dimensionality, a variant of coupling bootstrap techniques are developed for additive models with both symmetric error distributions and further extension to the quantile regression framework. Our bootstrap method can be used in many situations like constructing con dence intervals and bands. We demonstrate the bootstrap ...
Control of bootstrap current in the pedestal region of tokamaks
International Nuclear Information System (INIS)
The high confinement mode (H-mode) plasmas in the pedestal region of tokamaks are characterized by steep gradient of the radial electric field, and sonic poloidal Up,m flow that consists of poloidal components of the E×B flow and the plasma flow velocity that is parallel to the magnetic field B. Here, E is the electric field. The bootstrap current that is important for the equilibrium, and stability of the pedestal of H-mode plasmas is shown to have an expression different from that in the conventional theory. In the limit where ‖Up,m‖≫ 1, the bootstrap current is driven by the electron temperature gradient and inductive electric field fundamentally different from that in the conventional theory. The bootstrap current in the pedestal region can be controlled through manipulating Up,m and the gradient of the radial electric. This, in turn, can control plasma stability such as edge-localized modes. Quantitative evaluations of various coefficients are shown to illustrate that the bootstrap current remains finite when ‖Up,m‖ approaches infinite and to provide indications how to control the bootstrap current. Approximate analytic expressions for viscous coefficients that join results in the banana and plateau-Pfirsch-Schluter regimes are presented to facilitate bootstrap and neoclassical transport simulations in the pedestal region
Control of bootstrap current in the pedestal region of tokamaks
Energy Technology Data Exchange (ETDEWEB)
Shaing, K. C. [Institute for Space and Plasma Sciences, National Cheng Kung University, Tainan City 70101, Taiwan (China); Department of Engineering Physics, University of Wisconsin, Madison, Wisconsin 53796 (United States); Lai, A. L. [Institute for Space and Plasma Sciences, National Cheng Kung University, Tainan City 70101, Taiwan (China)
2013-12-15
The high confinement mode (H-mode) plasmas in the pedestal region of tokamaks are characterized by steep gradient of the radial electric field, and sonic poloidal U{sub p,m} flow that consists of poloidal components of the E×B flow and the plasma flow velocity that is parallel to the magnetic field B. Here, E is the electric field. The bootstrap current that is important for the equilibrium, and stability of the pedestal of H-mode plasmas is shown to have an expression different from that in the conventional theory. In the limit where ‖U{sub p,m}‖≫ 1, the bootstrap current is driven by the electron temperature gradient and inductive electric field fundamentally different from that in the conventional theory. The bootstrap current in the pedestal region can be controlled through manipulating U{sub p,m} and the gradient of the radial electric. This, in turn, can control plasma stability such as edge-localized modes. Quantitative evaluations of various coefficients are shown to illustrate that the bootstrap current remains finite when ‖U{sub p,m}‖ approaches infinite and to provide indications how to control the bootstrap current. Approximate analytic expressions for viscous coefficients that join results in the banana and plateau-Pfirsch-Schluter regimes are presented to facilitate bootstrap and neoclassical transport simulations in the pedestal region.
Energy Technology Data Exchange (ETDEWEB)
Urbanski, P.; Kowalska, E.
1997-12-31
The principle of the bootstrap methodology applied for the assessment of parameters and prediction ability of the linear regression models was presented. Application of this method was shown on the example of calibration of the radioisotope sulphuric acid concentration gauge. The bootstrap method allows to determine not only the numerical values of the regression coefficients, but also enables to investigate their distributions. (author). 11 refs, 12 figs, 3 tabs.
Performance of mutual equity funds in Brazil – A bootstrap analysis
Directory of Open Access Journals (Sweden)
Marco Antonio Laes
2014-09-01
Full Text Available This article reports a study on the performance of mutual equity funds in Brazil from January 2002 to August 2012. For the analyses, Carhart's four-factor model is used as the benchmark for performance, and bootstrap procedures are applied to separate skill from luck. The results show that returns of the best performers are more due to luck than skill of their managers. For the bottom ranked funds, on the contrary, there is statistical evidence that their poor performance is caused mainly by bad management, rather than by bad luck. It is also showed that the largest funds perform better than the small or middle-sized funds.
Performance of mutual equity funds in Brazil – A bootstrap analysis
Marco Antonio Laes; Marcos Eugênio da Silva
2014-01-01
This article reports a study on the performance of mutual equity funds in Brazil from January 2002 to August 2012. For the analyses, Carhart's four-factor model is used as the benchmark for performance, and bootstrap procedures are applied to separate skill from luck. The results show that returns of the best performers are more due to luck than skill of their managers. For the bottom ranked funds, on the contrary, there is statistical evidence that their poor performance is caused mainly by ...
Plaza, D. A; Keyser, R.; G. J. M. De Lannoy; L. Giustarini; Matgen, P.; Pauwels, V. R. N.
2012-01-01
The Sequential Importance Sampling with Resampling (SISR) particle filter and the SISR with parameter resampling particle filter (SISR-PR) are evaluated for their performance in soil moisture assimilation and the consequent effect on baseflow generation. With respect to the resulting soil moisture time series, both filters perform appropriately. However, the SISR filter has a negative effect on the baseflow due to inconsistency between the parameter values and the states after the assimilatio...
Stability of response characteristics of a Delphi panel: application of bootstrap data expansion
Directory of Open Access Journals (Sweden)
Cole Bryan R
2005-12-01
Full Text Available Abstract Background Delphi surveys with panels of experts in a particular area of interest have been widely utilized in the fields of clinical medicine, nursing practice, medical education and healthcare services. Despite this wide applicability of the Delphi methodology, there is no clear identification of what constitutes a sufficient number of Delphi survey participants to ensure stability of results. Methods The study analyzed the response characteristics from the first round of a Delphi survey conducted with 23 experts in healthcare quality and patient safety. The panel members had similar training and subject matter understanding of the Malcolm Baldrige Criteria for Performance Excellence in Healthcare. The raw data from the first round sampling, which usually contains the largest diversity of responses, were augmented via bootstrap sampling to obtain computer-generated results for two larger samples obtained by sampling with replacement. Response characteristics (mean, trimmed mean, standard deviation and 95% confidence intervals for 54 survey items were compared for the responses of the 23 actual study participants and two computer-generated samples of 1000 and 2000 resampling iterations. Results The results from this study indicate that the response characteristics of a small expert panel in a well-defined knowledge area are stable in light of augmented sampling. Conclusion Panels of similarly trained experts (who possess a general understanding in the field of interest provide effective and reliable utilization of a small sample from a limited number of experts in a field of study to develop reliable criteria that inform judgment and support effective decision-making.
A Bootstrap Approach to Martian Manufacturing
Dorais, Gregory A.
2004-01-01
In-Situ Resource Utilization (ISRU) is an essential element of any affordable strategy for a sustained human presence on Mars. Ideally, Martian habitats would be extremely massive to allow plenty of room to comfortably live and work, as well as to protect the occupants from the environment. Moreover, transportation and power generation systems would also require significant mass if affordable. For our approach to ISRU, we use the industrialization of the U.S. as a metaphor. The 19th century started with small blacksmith shops and ended with massive steel mills primarily accomplished by blacksmiths increasing their production capacity and product size to create larger shops, which produced small mills, which produced the large steel mills that industrialized the country. Most of the mass of a steel mill is comprised of steel in simple shapes, which are produced and repaired with few pieces of equipment also mostly made of steel in basic shapes. Due to this simplicity, we expect that the 19th century manufacturing growth can be repeated on Mars in the 21st century using robots as the primary labor force. We suggest a "bootstrap" approach to manufacturing on Mars that uses a "seed" manufacturing system that uses regolith to create major structural components and spare parts. The regolith would be melted, foamed, and sintered as needed to fabricate parts using casting and solid freeform fabrication techniques. Complex components, such as electronics, would be brought from Earth and integrated as needed. These parts would be assembled to create additional manufacturing systems, which can be both more capable and higher capacity. These subsequent manufacturing systems could refine vast amounts of raw materials to create large components, as well as assemble equipment, habitats, pressure vessels, cranes, pipelines, railways, trains, power generation stations, and other facilities needed to economically maintain a sustained human presence on Mars.
Wendt, Herwig; Abry, Patrice
2007-01-01
Scaling analysis is nowadays becoming a standard tool in statistical signal processing. It mostly consists of estimating scaling attributes which in turns are involved in standard tasks such as detection, identification or classification. Recently, we proposed that confidence interval or hypothesis test design for scaling analysis could be based on non parametric bootstrap approaches. We showed that such procedures are efficient to decide whether data are better modeled with Gaussian fraction...
DEFF Research Database (Denmark)
Dehlholm, Christian; Brockhoff, Per B.; Bredie, Wender L. P.
2012-01-01
A new way of parametric bootstrapping allows similar construction of confidence ellipses applicable on all results from Multiple Factor Analysis obtained from the FactoMineR package in the statistical program R. With this procedure, a similar approach will be applied to Multiple Factor Analysis...... in different studies performed on the same set of products. In addition, the graphical display of confidence ellipses eases interpretation and communication of results....
International Nuclear Information System (INIS)
Soil erosion and both its on-site and off-site impacts are increasingly seen as a serious environmental problem across the world. The need for an improved evidence base on soil loss and soil redistribution rates has directed attention to the use of fallout radionuclides, and particularly 137Cs, for documenting soil redistribution rates. This approach possesses important advantages over more traditional means of documenting soil erosion and soil redistribution. However, one key limitation of the approach is the time-averaged or lumped nature of the estimated erosion rates. In nearly all cases, these will relate to the period extending from the main period of bomb fallout to the time of sampling. Increasing concern for the impact of global change, particularly that related to changing land use and climate change, has frequently directed attention to the need to document changes in soil redistribution rates within this period. Re-sampling techniques, which should be distinguished from repeat-sampling techniques, have the potential to meet this requirement. As an example, the use of a re-sampling technique to derive estimates of the mean annual net soil loss from a small (1.38 ha) forested catchment in southern Italy is reported. The catchment was originally sampled in 1998 and samples were collected from points very close to the original sampling points again in 2013. This made it possible to compare the estimate of mean annual erosion for the period 1954–1998 with that for the period 1999–2013. The availability of measurements of sediment yield from the catchment for parts of the overall period made it possible to compare the results provided by the 137Cs re-sampling study with the estimates of sediment yield for the same periods. In order to compare the estimates of soil loss and sediment yield for the two different periods, it was necessary to establish the uncertainty associated with the individual estimates. In the absence of a generally accepted procedure
High bootstrap current in RF-heated discharges
International Nuclear Information System (INIS)
Purely non-inductive steady-state discharges in tokamak reactors will require a large bootstrap current, Ibtot, in order to minimize the amounts of power in external current drive systems. In present day tokamaks, high bootstrap current discharges are produced under various conditions. It has been demonstrated that the on-axis RF heatings are good candidates for producing a large bootstrap current, especially the fast magnetosonic wave direct electron heating (FWEH), for which power deposition is centrally peaked. Moreover, the heating and current drive methods using RF waves could be used as external sources to optimize Iboot through the current profile control. In this paper, the dependence of Iboot on the profiles of the plasma density, temperature, pressure and current density is analysed using a theoretical approach with a matrix formulation. Examples of quasi-steady-state discharges with large bootstrap current fraction using FWEH on Tore Supra are given. Examples of high bootstrap current fractions on reverse shear discharges (TFTR, DIII-D, ...) are also mentioned. Purely non-inductive discharges with improved confinement by combination of FWEH and lower hybrid current drive are analysed and the extrapolation to the so-called 'Tore Supra CIEL phase' is reported. (author)
Locality, bulk equations of motion and the conformal bootstrap
Kabat, Daniel
2016-01-01
We develop an approach to construct local bulk operators in a CFT to order 1/N^2. Since 4-point functions are not fixed by conformal invariance we use the OPE to categorize possible forms for a bulk operator. Using previous results on 3-point functions we construct a local bulk operator in each OPE channel. We then impose the condition that the bulk operators constructed in different channels agree, and hence give rise to a well-defined bulk operator. We refer to this condition as the "bulk bootstrap." We argue and explicitly show in some examples that the bulk bootstrap leads to some of the same results as the regular conformal bootstrap. In fact the bulk bootstrap provides an easier way to determine some CFT data, since it does not require knowing the form of the conformal blocks. This analysis clarifies previous results on the relation between bulk locality and the bootstrap for theories with a 1/N expansion, and it identifies a simple and direct way in which OPE coefficients and anomalous dimensions deter...
Zhu, Feng; Feng, Weiyue; Wang, Huajian; Huang, Shaosen; Lv, Yisong; Chen, Yong
2013-01-01
X-ray spectral imaging provides quantitative imaging of trace elements in biological sample with high sensitivity. We propose a novel algorithm to promote the signal-to-noise ratio (SNR) of X-ray spectral images that have low photon counts. Firstly, we estimate the image data area that belongs to the homogeneous parts through confidence interval testing. Then, we apply the Poisson regression through its maximum likelihood estimation on this area to estimate the true photon counts from the Poisson noise corrupted data. Unlike other denoising methods based on regression analysis, we use the bootstrap resampling methods to ensure the accuracy of regression estimation. Finally, we use a robust local nonparametric regression method to estimate the baseline and subsequently subtract it from the X-ray spectral data to further improve the SNR of the data. Experiments on several real samples show that the proposed method performs better than some state-of-the-art approaches to ensure accuracy and precision for quantit...
A resampling-based meta-analysis for detection of differential gene expression in breast cancer
International Nuclear Information System (INIS)
Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results. The
Jackknife resampling technique on mocks: an alternative method for covariance matrix estimation
Escoffier, S; Tilquin, A; Pisani, A; Aguichine, A; de la Torre, S; Ealet, A; Gillard, W; Jullo, E
2016-01-01
We present a fast and robust alternative method to compute covariance matrix in case of cosmology studies. Our method is based on the jackknife resampling applied on simulation mock catalogues. Using a set of 600 BOSS DR11 mock catalogues as a reference, we find that the jackknife technique gives a similar galaxy clustering covariance matrix estimate by requiring a smaller number of mocks. A comparison of convergence rates show that $\\sim$7 times fewer simulations are needed to get a similar accuracy on variance. We expect this technique to be applied in any analysis where the number of available N-body simulations is low.
A resampling-based meta-analysis for detection of differential gene expression in breast cancer
Directory of Open Access Journals (Sweden)
Ergul Gulusan
2008-12-01
Full Text Available Abstract Background Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. Methods A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC, and invasive lobular carcinoma (ILC samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. Results The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively. The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real
Implementation of bootstrap current effects in the PIES code
International Nuclear Information System (INIS)
The PIES code (Princeton Iterative Equilibrium Solver) has been modified to take into account the effects of bootstrap current. A simple bootstrap current model, applicable to tokamaks, is presently being employed. Pressure flattening, caused by the evolution of islands, has an important effect on the bootstrap current, which in turn has an important large effect on the island width. Analytic models have shown that the overall result of this interaction is, for negative shear, a destabilization of the islands. Recently, Chang et al., has shown that good agreement exists between the analytic expression proposed by reference and experiments on TFTR. Approximations used in this analytic expression, such as the expressions for Δ'(w), axe avoided in the calculations done with the PIES code. A comparison of the two results will be presented
Point Set Denoising Using Bootstrap-Based Radial Basis Function
Ramli, Ahmad; Abd. Majid, Ahmad
2016-01-01
This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study. PMID:27315105
A Bootstrap Algebraic Multilevel method for Markov Chains
Bolten, M; Brannick, J; Frommer, A; Kahl, K; Livshits, I
2010-01-01
This work concerns the development of an Algebraic Multilevel method for computing stationary vectors of Markov chains. We present an efficient Bootstrap Algebraic Multilevel method for this task. In our proposed approach, we employ a multilevel eigensolver, with interpolation built using ideas based on compatible relaxation, algebraic distances, and least squares fitting of test vectors. Our adaptive variational strategy for computation of the state vector of a given Markov chain is then a combination of this multilevel eigensolver and associated multilevel preconditioned GMRES iterations. We show that the Bootstrap AMG eigensolver by itself can efficiently compute accurate approximations to the state vector. An additional benefit of the Bootstrap approach is that it yields an accurate interpolation operator for many other eigenmodes. This in turn allows for the use of the resulting AMG hierarchy to accelerate the MLE steps using standard multigrid correction steps. The proposed approach is applied to a rang...
No unitary bootstrap for the fractal Ising model
Golden, John
2015-01-01
We consider the conformal bootstrap for spacetime dimension $1
Addressing the P2P Bootstrap Problem for Small Networks
Wolinsky, David Isaac; Boykin, P Oscar; Figueiredo, Renato
2010-01-01
P2P overlays provide a framework for building distributed applications consisting of few to many resources with features including self-configuration, scalability, and resilience to node failures. Such systems have been successfully adopted in large-scale services for content delivery networks, file sharing, and data storage. In small-scale systems, they can be useful to address privacy concerns and for network applications that lack dedicated servers. The bootstrap problem, finding an existing peer in the overlay, remains a challenge to enabling these services for small-scale P2P systems. In large networks, the solution to the bootstrap problem has been the use of dedicated services, though creating and maintaining these systems requires expertise and resources, which constrain their usefulness and make them unappealing for small-scale systems. This paper surveys and summarizes requirements that allow peers potentially constrained by network connectivity to bootstrap small-scale overlays through the use of e...
Design and Implementation of a Bootstrap Trust Chain
Institute of Scientific and Technical Information of China (English)
YU Fajiang; ZHANG Huanguo
2006-01-01
The chain of trust in bootstrap process is the basis of whole system trust in the trusted computing group (TCG) definition. This paper presents a design and implementation of a bootstrap trust chain in PC based on the Windows and today' commodity hardware, merely depends on availability of an embedded security module (ESM). ESM and security enhanced BIOS is the root of trust, PMBR (Pre-MBR) checks the integrity of boot data and Windows kernel, which is a checking agent stored in ESM. In the end, the paper analyzed the mathematic expression of the chain of trust and the runtime performance compared with the common booting process. The trust chain bootstrap greatly strengthens the security of personal computer system, and affects the runtime performance with only adding about 12% booting time.
Beam-driven and bootstrap currents in JT-60 upgrade
International Nuclear Information System (INIS)
We recently performed beam-driven current-drive experiments with a low fraction of bootstrap currents in a wide range of plasma parameters in JT-60 upgrade. The evidence of current profile modification by the beam-driven current with tangential neutral beam injectors. A high βN, high βp and ELMy H-mode plasma with possibly fully non-inductive current-drive by beam-driven and bootstrap currents was maintained for a considerably long duration with the combined injection of quasi-perpendicular and co-tangential beams. (author) 4 refs., 7 figs
Generalized bootstrap equations and possible implications for the NLO odderon
International Nuclear Information System (INIS)
We formulate and discuss generalized bootstrap equations in nonabelian gauge theories. They are shown to hold in the leading logarithmic approximation. Since their validity is related to the self-consistency of the Steinmann relations for inelastic production amplitudes they can be expected to be valid also in NLO. Specializing to the N=4 SYM, we show that the validity in NLO of these generalized bootstrap equations allows to find the NLO odderon solution with intercept exactly at one, a result which is valid also for the planar limit of QCD. (orig.)
Experimental evidence for the bootstrap current in a tokamak
International Nuclear Information System (INIS)
The bootstrap current is a plasma current associated with trapped particles in a toroidal plasma. Magnetic measurements, such as the surface voltage, the internal inductance, and the Faraday rotation, are consistent with the existence of the neoclassical bootstrap current in tokamaks. The neoclassical trapped-particle correction to the electrical conductivity is also systematically validated against experiments. These results support the assertion that the generalized Ohm's law along the magnetic field is valid, as predicted by the neoclassical transport theory, while the perpendicular transport deviates from the neoclassical transport theory. (Author)
Bootstrap current increment after siliconization on the HT-7 tokamak
International Nuclear Information System (INIS)
The authors present some results for the estimation of the bootstrap current after siliconization on the HT-7 tokamak. After siliconization, the plasma pressure gradient and the electron temperature near the boundary are larger than before siliconization. These factors influence the ratio of the bootstrap current to the total plasma current which increases from several per cent to above 10%. The results are expected to explain the previous experimental phenomena that, after siliconization, the plasma current profile is broadened and the higher current can be obtained easily on the HT-7 tokamak experiment
Modelos alternativos de simulación Bootstrap
Pino Mejías, Rafael
1992-01-01
Se describen las características fundamentales de los métodos Bootstrap. Se analizan diversas problemáticas que presentan tales métodos, por lo que se presentan dos métodos alternativos dentro del método Bootstrap basado en la simulación de muestras (método II de Efron). En el primero se presenta un método, que a partir de un estudio de las propiedades algebraicas y estadísticas del conjunto de posibles muestras, utiliza un criterio probabilístico para detectar muestras "outliers". En el segu...
Bootstrapped efficiency measures of oil blocks in Angola
International Nuclear Information System (INIS)
This paper investigates the technical efficiency of Angola oil blocks over the period 2002-2007. A double bootstrap data envelopment analysis (DEA) model is adopted composed in the first stage of a DEA-variable returns to scale (VRS) model and then followed in the second stage by a bootstrapped truncated regression. Results showed that on average, the technical efficiency has fluctuated over the period of study, but deep and ultradeep oil blocks have generally maintained a consistent efficiency level. Policy implications are derived.
Bootstrapping Critical Ising Model on Three Dimensional Real Projective Space
Nakayama, Yu
2016-04-01
Given conformal data on a flat Euclidean space, we use crosscap conformal bootstrap equations to numerically solve the Lee-Yang model as well as the critical Ising model on a three dimensional real projective space. We check the rapid convergence of our bootstrap program in two dimensions from the exact solutions available. Based on the comparison, we estimate that our systematic error on the numerically solved one-point functions of the critical Ising model on a three dimensional real projective space is less than 1%. Our method opens up a novel way to solve conformal field theories on nontrivial geometries.
PyCFTBoot: A flexible interface for the conformal bootstrap
Behan, Connor
2016-01-01
We introduce PyCFTBoot, a wrapper designed to reduce the barrier to entry in conformal bootstrap calculations that require semidefinite programming. Symengine and SDPB are used for the most intensive symbolic and numerical steps respectively. After reviewing the built-in algorithms for conformal blocks, we explain how to use the code through a number of examples that verify past results. As an application, we show that the multi-correlator bootstrap still appears to single out the Wilson-Fisher fixed points as special theories in dimensions between 3 and 4 despite the recent proof that they violate unitarity.
International Nuclear Information System (INIS)
This study investigates whether ‘pencil beam resampling’, i.e. iterative selection and weight optimization of randomly placed pencil beams (PBs), reduces optimization time and improves plan quality for multi-criteria optimization in intensity-modulated proton therapy, compared with traditional modes in which PBs are distributed over a regular grid. Resampling consisted of repeatedly performing: (1) random selection of candidate PBs from a very fine grid, (2) inverse multi-criteria optimization, and (3) exclusion of low-weight PBs. The newly selected candidate PBs were added to the PBs in the existing solution, causing the solution to improve with each iteration. Resampling and traditional regular grid planning were implemented into our in-house developed multi-criteria treatment planning system ‘Erasmus iCycle’. The system optimizes objectives successively according to their priorities as defined in the so-called ‘wish-list’. For five head-and-neck cancer patients and two PB widths (3 and 6 mm sigma at 230 MeV), treatment plans were generated using: (1) resampling, (2) anisotropic regular grids and (3) isotropic regular grids, while using varying sample sizes (resampling) or grid spacings (regular grid). We assessed differences in optimization time (for comparable plan quality) and in plan quality parameters (for comparable optimization time). Resampling reduced optimization time by a factor of 2.8 and 5.6 on average (7.8 and 17.0 at maximum) compared with the use of anisotropic and isotropic grids, respectively. Doses to organs-at-risk were generally reduced when using resampling, with median dose reductions ranging from 0.0 to 3.0 Gy (maximum: 14.3 Gy, relative: 0%–42%) compared with anisotropic grids and from −0.3 to 2.6 Gy (maximum: 11.4 Gy, relative: −4%–19%) compared with isotropic grids. Resampling was especially effective when using thin PBs (3 mm sigma). Resampling plans contained on average fewer PBs, energy layers and protons than
Resampling nucleotide sequences with closest-neighbor trimming and its comparison to other methods.
Directory of Open Access Journals (Sweden)
Kouki Yonezawa
Full Text Available A large number of nucleotide sequences of various pathogens are available in public databases. The growth of the datasets has resulted in an enormous increase in computational costs. Moreover, due to differences in surveillance activities, the number of sequences found in databases varies from one country to another and from year to year. Therefore, it is important to study resampling methods to reduce the sampling bias. A novel algorithm-called the closest-neighbor trimming method-that resamples a given number of sequences from a large nucleotide sequence dataset was proposed. The performance of the proposed algorithm was compared with other algorithms by using the nucleotide sequences of human H3N2 influenza viruses. We compared the closest-neighbor trimming method with the naive hierarchical clustering algorithm and [Formula: see text]-medoids clustering algorithm. Genetic information accumulated in public databases contains sampling bias. The closest-neighbor trimming method can thin out densely sampled sequences from a given dataset. Since nucleotide sequences are among the most widely used materials for life sciences, we anticipate that our algorithm to various datasets will result in reducing sampling bias.
A genetic resampling particle filter for freeway traffic-state estimation
Institute of Scientific and Technical Information of China (English)
Bi Jun; Guan Wei; Qi Long-Tao
2012-01-01
On-line estimation of the state of traffic based on data sampled by electronic detectors is important for intelligent traffic management and control.Because a nonlinear feature exists in the traffic state,and because particle filters have good characteristics when it comes to solving the nonlinear problem,a genetic resampling particle filter is proposed to estimate the state of freeway traffic.In this paper,a freeway section of the northern third ring road in the city of Beijing in China is considered as the experimental object.By analysing the traffic-state characteristics of the freeway,the traffic is modeled based on the second-order validated macroscopic traffic flow model.In order to solve the particle degeneration issue in the performance of the particle filter,a genetic mechanism is introduced into the resampling process.The realization of a genetic particle filter for freeway traffic-state estimation is discussed in detail,and the filter estimation performance is validated and evaluated by the achieved experimental data.
Bootstrap Tests and Confidence Regions for Functions of a Covariance Matrix
Beran, Rudolf; Srivastava, Muni S.
1985-01-01
Bootstrap tests and confidence regions for functions of the population covariance matrix have the desired asymptotic levels, provided model restrictions, such as multiple eigenvalues in the covariance matrix, are taken into account in designing the bootstrap algorithm.
Il bootstrap. Un'applicazione informatica per un problema di ricampionamento
Morana, Maria Teresa; Porcu, Mariano
2002-01-01
The aim of this paper is to give a simple introduction to the bootstrap techniques showing a basic computer algorithm. The algorithm displays, step by step, how to determinate a bootstrap confidence interval.
Study of EC current drive efficiency and bootstrap current by power modulation experiments
International Nuclear Information System (INIS)
In Stellarators, the absence of a strong 'obscuring' Ohmic component permits the experimental investigation of small non-inductive currents with a precision difficult to be obtained in an equivalent Tokamak. In the W7-AS Stellarator (R = 2 m, ≤0.18 m, PECRH ≤ 800 kW) we have performed a systematic study of Electron Cyclotron Current Drive. Uncertainties in the measurements of the ECCD efficiency, ηECCD, are introduced by the unavoidable presence of the bootstrap current (and, eventually, an Ohmic one) and by the strong coupling between confinement properties and rotational transform, which is typical for low-shear vacuum magnetic field configurations, as W7-AS. To improve the accuracy, we have applied a new perturbative procedure for the determination of ηECCD. The method is based on the independent launch of two microwave beams. While one of the two beams is launched with a toroidal angle of injection corresponding to co-current drive (with respect to the bootstrap current direction) the second one is injected in the opposite direction (counter-current drive). In absence of effects perturbing the symmetry (e.g., strong E|| as in Tokamaks, or strong anisotropic electron distribution functions as in presence of LHCD) the two r.f. beams are equivalently absorbed and the two driven currents compensate. Through a modulation of the powers in both beam with same amplitude but opposite phase, the modulated ECCD contribution can be discriminated from the unaffected bootstrap and Ohmic ones. Furthermore, the time delay between the modulated power and the response of the loop voltage contains information about the radial localization of the modulated ECCD-current. (author) 6 refs., 5 figs
A frequency domain bootstrap for ratio statistics in time series analysis
Dahlhaus, R.; Janas, D.
1996-01-01
The asymptotic properties of the bootstrap in the frequency domain based on Studentized periodogram ordinates are studied. It is proved that this bootstrap approximation is valid for ratio statistics such as autocorrelations. By using Edgeworth expansions it is shown that the bootstrap approximation even outperforms the normal approximation. The results carry over to Whittle estimates. In a simulation study the behavior of the bootstrap is studied for empirical correlations and Whittle estima...
Siana Halim; Herman Mallian
2006-01-01
The Bootstrap is a lively research area. A lot Of ideas are around and have let to quiet different proposals. In this paper we sketch briefly some Bootstrap methods for independent and dependent data. Finally we give an Bootstrap example for constructing confidence interval in the forecasting for stationer data. Abstract in Bahasa Indonesia : Bootstrap merupakan area penelitian yang terus berkembang. Ada banyak ide dan proposal-proposal yang berbeda telah diberikan oleh para peneliti. Namun d...
First and second order analysis for periodic random arrays using block bootstrap methods
Dudek, Anna E.
2016-01-01
In the paper row-wise periodically correlated triangular arrays are considered. The period length is assumed to grow in time. The Fourier decomposition of the mean and autocovariance functions for each row of the matrix is presented. To construct bootstrap estimators of the Fourier coefficients two block bootstrap techniques are used. These are the circular version of the Generalized Seasonal Block Bootstrap and the Circular Block Bootstrap. Consistency results for both methods are presented....
International Nuclear Information System (INIS)
Many of the neurodegenerative diseases associated with a decrease in regional cerebral blood flow (rCBF) are untreatable, and the appropriate therapeutic strategy is to slow the progression of the disease. Therefore, it is important that a definitive diagnosis is made as soon as possible when such diseases are suspected. Diagnostic imaging methods, such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT), play an important role in such a definitive diagnosis. Since several problems arise when evaluating these images visually, a procedure to evaluate them objectively is necessary, and studies of image analyses using statistical evaluations have been suggested. However, the assumed data distribution in a statistical procedure may occasionally be inappropriate. Therefore, to evaluate the decrease of rCBF, it is important to use a statistical procedure without assumptions about the data distribution. In this study, we propose a new procedure that uses nonparametric or smoothed bootstrap methods to calculate a standardized distribution of the Z-score without assumptions about the data distribution. To test whether the judgment of the proposed procedure is equivalent to that of an evaluation based on the Z-score with a fixed threshold, the procedure was applied to a sample data set whose size was large enough to be appropriate for the assumption of the Z-score. As a result, the evaluations of the proposed procedure were equivalent to that of an evaluation based on the Z-score. (author)
Normal Limits, Nonnormal Limits, and the Bootstrap for Quantiles of Dependent Data
Sharipov, O. Sh.; Wendler, M.
2012-01-01
We will show under very weak conditions on differentiability and dependence that the central limit theorem for quantiles holds and that the block bootstrap is weakly consistent. Under slightly stronger conditions, the bootstrap is strongly consistent. Without the differentiability condition, quantiles might have a non-normal asymptotic distribution and the bootstrap might fail.
Spinella, Sarah
2011-01-01
As result replicability is essential to science and difficult to achieve through external replicability, the present paper notes the insufficiency of null hypothesis statistical significance testing (NHSST) and explains the bootstrap as a plausible alternative, with a heuristic example to illustrate the bootstrap method. The bootstrap relies on…
Noncentral limit theorem and the bootstrap for quantiles of dependent data
Sharipov, Olimjon S.; Wendler, Martin
2012-01-01
We will show under minimal conditions on differentiability and dependence that the central limit theorem for quantiles holds and that the block bootstrap is weakly consistent. Under slightly stronger conditions, the bootstrap is strongly consistent. Without the differentiability condition, quantiles might have a non-normal asymptotic distribution and the bootstrap might fail.
RANDOM QUADRATIC-FORMS AND THE BOOTSTRAP FOR U-STATISTICS
DEHLING, H; MIKOSCH, T
1994-01-01
We study the bootstrap distribution for U-statistics with special emphasis on the degenerate case. For the Efron bootstrap we give a short proof of the consistency using Mallows' metrics. We also study the i.i.d. weighted bootstrap [GRAPHICS] where (X(i)) and (xi(i)) are two i.i.d. sequences, indepe
Sidecoin: a snapshot mechanism for bootstrapping a blockchain
Krug, Joseph; Peterson, Jack
2015-01-01
Sidecoin is a mechanism that allows a snapshot to be taken of Bitcoin's blockchain. We compile a list of Bitcoin's unspent transaction outputs, then use these outputs and their corresponding balances to bootstrap a new blockchain. This allows the preservation of Bitcoin's economic state in the context of a new blockchain, which may provide new features and technical innovations.
Automatic bootstrapping of a morphable face model using multiple components
Haar, F.B. ter; Veltkamp, R.C.
2009-01-01
We present a new bootstrapping algorithm to automatically enhance a 3D morphable face model with new face data. Our algorithm is based on a morphable model fitting method that uses a set of predefined face components. This fitting method produces accurate model fits to 3D face data with noise and ho
Metastability Thresholds for Anisotropic Bootstrap Percolation in Three Dimensions
Van Enter, A.C.D.; Fey, A.
2012-01-01
In this paper we analyze several anisotropic bootstrap percolation models in three dimensions. We present the order of magnitude for the metastability thresholds for a fairly general class of models. In our proofs, we use an adaptation of the technique of dimensional reduction. We find that the orde
A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages
DEFF Research Database (Denmark)
Malzahn, Dorthe; Opper, Manfred
2003-01-01
We apply the replica method of Statistical Physics combined with a variational method to the approximate analytical computation of bootstrap averages for estimating the generalization error. We demonstrate our approach on regression with Gaussian processes and compare our results with averages...
Metastability thresholds for anisotropic bootstrap percolation in three dimensions
Van Enter, A.C.D.; Fey, A.
2012-01-01
In this paper we analyze several anisotropic bootstrap percolation models in three dimensions. We present the order of magnitude for the metastability thresholds for a fairly general class of models. In our proofs, we use an adaptation of the technique of dimensional reduction. We find that the orde
More on analytic bootstrap for O(N) models
Dey, Parijat; Sen, Kallol
2016-01-01
This note is an extension of a recent work on the analytical bootstrapping of $O(N)$ models. An additonal feature of the $O(N)$ model is that the OPE contains trace and antisymmetric operators apart from the symmetric-traceless objects appearing in the OPE of the singlet sector. This in addition to the stress tensor $(T_{\\mu\
Bootstrapping rapidity anomalous dimension for transverse-momentum resummation
Li, Ye
2016-01-01
Soft function relevant for transverse-momentum resummation for Drell-Yan or Higgs production at hadron colliders are computed through to three loops in the expansion of strong coupling, with the help of bootstrap technique and supersymmetric decomposition. The corresponding rapidity anomalous dimension is extracted. An intriguing relation between anomalous dimensions for transverse-momentum resummation and threshold resummation is found.
Bootstrapping Rapidity Anomalous Dimension for Transverse-Momentum Resummation
Energy Technology Data Exchange (ETDEWEB)
Li, Ye [Fermilab; Zhu, Hua Xing [MIT, Cambridge, CTP
2016-04-05
Soft function relevant for transverse-momentum resummation for Drell-Yan or Higgs production at hadron colliders are computed through to three loops in the expansion of strong coupling, with the help of bootstrap technique and supersymmetric decomposition. The corresponding rapidity anomalous dimension is extracted. An intriguing relation between anomalous dimensions for transverse-momentum resummation and threshold resummation is found.
A neural network based reputation bootstrapping approach for service selection
Wu, Quanwang; Zhu, Qingsheng; Li, Peng
2015-10-01
With the concept of service-oriented computing becoming widely accepted in enterprise application integration, more and more computing resources are encapsulated as services and published online. Reputation mechanism has been studied to establish trust on prior unknown services. One of the limitations of current reputation mechanisms is that they cannot assess the reputation of newly deployed services as no record of their previous behaviours exists. Most of the current bootstrapping approaches merely assign default reputation values to newcomers. However, by this kind of methods, either newcomers or existing services will be favoured. In this paper, we present a novel reputation bootstrapping approach, where correlations between features and performance of existing services are learned through an artificial neural network (ANN) and they are then generalised to establish a tentative reputation when evaluating new and unknown services. Reputations of services published previously by the same provider are also incorporated for reputation bootstrapping if available. The proposed reputation bootstrapping approach is seamlessly embedded into an existing reputation model and implemented in the extended service-oriented architecture. Empirical studies of the proposed approach are shown at last.
A bootstrapping soft shrinkage approach for variable selection in chemical modeling.
Deng, Bai-Chuan; Yun, Yong-Huan; Cao, Dong-Sheng; Yin, Yu-Long; Wang, Wei-Ting; Lu, Hong-Mei; Luo, Qian-Yi; Liang, Yi-Zeng
2016-02-18
In this study, a new variable selection method called bootstrapping soft shrinkage (BOSS) method is developed. It is derived from the idea of weighted bootstrap sampling (WBS) and model population analysis (MPA). The weights of variables are determined based on the absolute values of regression coefficients. WBS is applied according to the weights to generate sub-models and MPA is used to analyze the sub-models to update weights for variables. The optimization procedure follows the rule of soft shrinkage, in which less important variables are not eliminated directly but are assigned smaller weights. The algorithm runs iteratively and terminates until the number of variables reaches one. The optimal variable set with the lowest root mean squared error of cross-validation (RMSECV) is selected. The method was tested on three groups of near infrared (NIR) spectroscopic datasets, i.e. corn datasets, diesel fuels datasets and soy datasets. Three high performing variable selection methods, i.e. Monte Carlo uninformative variable elimination (MCUVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm partial least squares (GA-PLS) are used for comparison. The results show that BOSS is promising with improved prediction performance. The Matlab codes for implementing BOSS are freely available on the website: http://www.mathworks.com/matlabcentral/fileexchange/52770-boss. PMID:26826688
Use of Monte Carlo Bootstrap Method in the Analysis of Sample Sufficiency for Radioecological Data
International Nuclear Information System (INIS)
There are operational difficulties in obtaining samples for radioecological studies. Population data may no longer be available during the study and obtaining new samples may not be possible. These problems do the researcher sometimes work with a small number of data. Therefore, it is difficult to know whether the number of samples will be sufficient to estimate the desired parameter. Hence, it is critical do the analysis of sample sufficiency. It is not interesting uses the classical methods of statistic to analyze sample sufficiency in Radioecology, because naturally occurring radionuclides have a random distribution in soil, usually arise outliers and gaps with missing values. The present work was developed aiming to apply the Monte Carlo Bootstrap method in the analysis of sample sufficiency with quantitative estimation of a single variable such as specific activity of a natural radioisotope present in plants. The pseudo population was a small sample with 14 values of specific activity of 226Ra in forage palm (Opuntia spp.). Using the R software was performed a computational procedure to calculate the number of the sample values. The re sampling process with replacement took the 14 values of original sample and produced 10,000 bootstrap samples for each round. Then was calculated the estimated average θ for samples with 2, 5, 8, 11 and 14 values randomly selected. The results showed that if the researcher work with only 11 sample values, the average parameter will be within a confidence interval with 90% probability . (Author)
Kinetic effects on a tokamak pedestal ion flow, ion heat transport and bootstrap current
International Nuclear Information System (INIS)
We consider the effects of a finite radial electric field on ion orbits in a subsonic pedestal. Using a procedure that makes a clear distinction between a transit average and a flux surface average we are able to solve the kinetic equation to retain the modifications due to finite E-vector x B-vector drift orbit departures from flux surfaces. Our approach properly determines the velocity space localized, as well as the nonlocal, portion of the ion distribution function in the banana and plateau regimes in the small aspect ratio limit. The rapid variation of the poloidal ion flow coefficient and the electrostatic potential in the total energy modify previous banana regime evaluations of the ion flow, the bootstrap current, and the radial ion heat flux in a subsonic pedestal. In the plateau regime, the rapid variation of the poloidal flow coefficient alters earlier results for the ion flow and bootstrap current, while leaving the ion heat flux unchanged since the rapid poloidal variation of the total energy was properly retained. (paper)
A Bootstrap Approach to Computing Uncertainty in Inferred Oil and Gas Reserve Estimates
International Nuclear Information System (INIS)
This study develops confidence intervals for estimates of inferred oil and gas reserves based on bootstrap procedures. Inferred reserves are expected additions to proved reserves in previously discovered conventional oil and gas fields. Estimates of inferred reserves accounted for 65% of the total oil and 34% of the total gas assessed in the U.S. Geological Survey's 1995 National Assessment of oil and gas in US onshore and State offshore areas. When the same computational methods used in the 1995 Assessment are applied to more recent data, the 80-year (from 1997 through 2076) inferred reserve estimates for pre-1997 discoveries located in the lower 48 onshore and state offshore areas amounted to a total of 39.7 billion barrels of oil (BBO) and 293 trillion cubic feet (TCF) of gas. The 90% confidence interval about the oil estimate derived from the bootstrap approach is 22.4 BBO to 69.5 BBO. The comparable 90% confidence interval for the inferred gas reserve estimate is 217 TCF to 413 TCF. The 90% confidence interval describes the uncertainty that should be attached to the estimates. It also provides a basis for developing scenarios to explore the implications for energy policy analysis
BOOTSTRAP WAVELET IN THE NONPARAMETRIC REGRESSION MODEL WITH WEAKLY DEPENDENT PROCESSES
Institute of Scientific and Technical Information of China (English)
林路; 张润楚
2004-01-01
This paper introduces a method of bootstrap wavelet estimation in a nonparametric regression model with weakly dependent processes for both fixed and random designs. The asymptotic bounds for the bias and variance of the bootstrap wavelet estimators are given in the fixed design model. The conditional normality for a modified version of the bootstrap wavelet estimators is obtained in the fixed model. The consistency for the bootstrap wavelet estimator is also proved in the random design model. These results show that the bootstrap wavelet method is valid for the model with weakly dependent processes.
Farmer, W. H.; Over, T. M.; Vogel, R. M.; Archfield, S. A.; Kiang, J. E.
2014-12-01
In ungaged basins, predictions of daily streamflow are essential to responsible and effective management and design of water resources systems. Transfer-based methods are widely used for prediction in ungaged basins (PUB) within a gaged network. Such methods rely on the transfer of information from an index gage to an ungaged site. In what is known as the nearest-neighbor algorithm, the index gage is selected based on geospatial proximity. The predictions offered by any PUB method can be highly uncertain, and it is often difficult to characterize this uncertainty. In the development of predicted streamflow records, understanding the uncertainty of estimates would greatly improve water resources management in ungaged basins. It is proposed that by resampling the sites of the gaged network, with replacement, a set of equally-probable streamflow predictions can be produced for any ungaged site. For a particular day in the record, the percentiles of the distribution of the resampled, predicted streamflows can be used to estimate confidence intervals of the original daily streamflow predictions. This approach is explored in the Southeast United States with a nearest-neighbor application of non-linear spatial interpolation using flow duration curves (QPPQ), a common PUB method. Though some interval re-centering is required to ensure that the best-case prediction falls within the confidence intervals, it is shown that this technique provides a reasonable first-order approximation of prediction uncertainty. Still, the best estimated confidence intervals are shown to consistently under-estimate the nominal confidence. It is hypothesized that this interval contraction is a result of temporal and spatial correlation within the gaged network. Additionally, implications of prediction uncertainty are explored and alternative estimators are considered.
Hieke, Stefanie; Benner, Axel; Schlenk, Richard F.; Schumacher, Martin; Bullinger, Lars; Binder, Harald
2016-01-01
Clinical cohorts with time-to-event endpoints are increasingly characterized by measurements of a number of single nucleotide polymorphisms that is by a magnitude larger than the number of measurements typically considered at the gene level. At the same time, the size of clinical cohorts often is still limited, calling for novel analysis strategies for identifying potentially prognostic SNPs that can help to better characterize disease processes. We propose such a strategy, drawing on univariate testing ideas from epidemiological case-controls studies on the one hand, and multivariable regression techniques as developed for gene expression data on the other hand. In particular, we focus on stable selection of a small set of SNPs and corresponding genes for subsequent validation. For univariate analysis, a permutation-based approach is proposed to test at the gene level. We use regularized multivariable regression models for considering all SNPs simultaneously and selecting a small set of potentially important prognostic SNPs. Stability is judged according to resampling inclusion frequencies for both the univariate and the multivariable approach. The overall strategy is illustrated with data from a cohort of acute myeloid leukemia patients and explored in a simulation study. The multivariable approach is seen to automatically focus on a smaller set of SNPs compared to the univariate approach, roughly in line with blocks of correlated SNPs. This more targeted extraction of SNPs results in more stable selection at the SNP as well as at the gene level. Thus, the multivariable regression approach with resampling provides a perspective in the proposed analysis strategy for SNP data in clinical cohorts highlighting what can be added by regularized regression techniques compared to univariate analyses. PMID:27159447
International Nuclear Information System (INIS)
A method to prepare a set of four climate scenarios for the Netherlands is presented. These scenarios for climate change in 2050 and 2085 (compared to present-day) are intended for general use in climate change adaptation in the Netherlands. An ensemble of eight simulations with the global model EC-Earth and the regional climate model RACMO2 (run at 12 km resolution) is used. For each scenario time horizon, two target values of the global mean temperature rise are chosen based on the spread in the CMIP5 simulations. Next, the corresponding time periods in the EC-Earth/RACMO2 simulations are selected in which these target values of the global temperature rise are reached. The model output for these periods is then resampled using blocks of 5 yr periods. The rationale of resampling is that natural variations in the EC-Earth/RACMO2 ensemble are used to represent (part of the) uncertainty in the CMIP5 projections. Samples are then chosen with the aim of reconstructing the spread in seasonal temperature and precipitation changes in CMIP5 for the Netherlands. These selected samples form the basis of the scenarios. The resulting four scenarios represent 50–80% of the CMIP5 spread for summer and winter changes in seasonal means as well as a limited number of monthly statistics (warm, cold, wet and dry months). The strong point of the method—also in relation to the previous set of the climate scenarios for the Netherlands issued in 2006—is that it preserves nearly all physical inter-variable consistencies as they exist in the original model output in both space and time. (paper)
Directory of Open Access Journals (Sweden)
Rohin Anhal
2013-10-01
Full Text Available The aim of this paper is to examine the direction of causality between real GDP on the one hand and final energy and coal consumption on the other in India, for the period from 1970 to 2011. The methodology adopted is the non-parametric bootstrap procedure, which is used to construct the critical values for the hypothesis of causality. The results of the bootstrap tests show that for total energy consumption, there exists no causal relationship in either direction with GDP of India. However, if coal consumption is considered, we find evidence in support of unidirectional causality running from coal consumption to GDP. This clearly has important implications for the Indian economy. The most important implication is that curbing coal consumption in order to reduce carbon emissions would in turn have a limiting effect on economic growth. Our analysis contributes to the literature in three distinct ways. First, this is the first paper to use the bootstrap method to examine the growth-energy connection for the Indian economy. Second, we analyze data for the time period 1970 to 2011, thereby utilizing recently available data that has not been used by others. Finally, in contrast to the recently done studies, we adopt a disaggregated approach for the analysis of the growth-energy nexus by considering not only aggregate energy consumption, but coal consumption as well.
International Nuclear Information System (INIS)
We investigated the effect on image data resampling in an evaluation of the basic imaging properties for a digital radiographic system based on a flat panel detector (FPD). One of the latest digital radiographic systems was used in this study. This system was based on a direct-conversion FPD of amorphous selenium. The basic imaging properties of the system were evaluated by measuring characteristic curve, presampled modulation transfer function (MTF), and Wiener spectrum (WS) using Digital Imaging and Communications in Medicine (DICOM) image with a matrix size of 2048 x 2048. The evaluations were performed under two conditions because matrix size automatically changes according to the selection of imaging size. One of the conditions was a different matrix size between image data acquired on the FPD and the output image (DICOM image for which resampling was performed). The other condition was that these matrices be the same size (DICOM image with no resampling performed). Resampling did not affect the characteristic curves. However, MTF and the WS obtained from the resampled data were different from those of the one not resampled, which is considered to be the 'inherent' basic imaging properties, and this phenomenon was remarkable, especially in terms of the MTFs. Our study indicates that the effect on resampling should not be disregarded in evaluating the basic imaging properties of digital radiographic systems. Therefore, it is mandatory to use DICOM images for which no resampling was performed in order to evaluate the inherent basic imaging properties for digital radio graphic systems. (author)
Five dimensional O(N)-symmetric CFTs from conformal bootstrap
International Nuclear Information System (INIS)
We investigate the conformal bootstrap approach to O(N) symmetric CFTs in five dimensions with particular emphasis on the lower bound on the current central charge. The bound has a local minimum for all N>1, and in the large N limit we propose that the minimum is saturated by the critical O(N) vector model at the UV fixed point, the existence of which has been recently argued by Fei, Giombi, and Klebanov. The location of the minimum is generically different from the minimum of the lower bound of the energy–momentum tensor central charge when it exists for smaller N. To better understand the situation, we examine the lower bounds of the current central charge of O(N) symmetric CFTs in three dimensions to compare. We find the similar agreement in the large N limit but the discrepancy for smaller N with the other sectors of the conformal bootstrap
A proof of fulfillment of the strong bootstrap condition
International Nuclear Information System (INIS)
It is shown that the kernel of the BFKL equation for the octet color state of two Reggeized gluons satisfies the strong bootstrap condition in the next-to-leading order. This condition is much more restrictive than the one obtained from the requirement of the Reggeized form for the elastic scattering amplitudes in the next-to-leading approximation. It is necessary, however, for self-consistency of the assumption of the Reggeized form of the production amplitudes in multi-Regge kinematics, which are used in the derivation of the BFKL equation. The fulfillment of the strong bootstrap condition for the kernel opens the way to a rigorous proof of the BFKL equation in the next-to-leading approximation. (orig.)
Self-consistent ECCD calculations with bootstrap current
International Nuclear Information System (INIS)
To achieve high performance, steady-state operation in tokamaks, it is increasingly important to find the appropriate means for modifying and sustaining the pressure and magnetic shear profiles in the plasma. In such advanced scenarios, especially in the vicinity of internal transport barrier, RF induced currents have to be calculated self-consistently with the bootstrap current, thus taking into account possible synergistic effects resulting from the momentum space distortion of the electron distribution function fe. Since RF waves can cause the distribution of electrons to become non-Maxwellian, the associated changes in parallel diffusion of momentum between trapped and passing particles can be expected to modify the bootstrap current fraction; conversely, the bootstrap current distribution function can enhance the current driven by RF waves. For this purpose, a new, fast and fully implicit solver has been recently developed to carry out computations including new and detailed evaluations of the interactions between bootstrap current (BC) and Electron Cyclotron current drive (ECCD). Moreover, Ohkawa current drive (OKCD) appears to be an efficient method for driving current when the fraction of trapped particles is large. OKCD in the presence of BC is also investigated. Here, results are illustrated around projected tokamak parameters in high performance scenarios of AlcatorC-MOD. It is shown that by increasing n//, the EC wave penetration into the bulk of the electron distribution is greater, and since the resonance extends up to high p// values, this situation is the usual ECCD based on the Fisch-Boozer mechanism concerning passing particles. However, because of the close vicinity of the trapped boundary at r/a=0.7, this process is counterbalanced by the Ohkawa effect, possibly leading to a negative net current. Therefore, by injecting the EC wave in the opposite toroidal direction (n// RF by OKCD may be 70% larger than that of ECCD, with a choice of EC wave
Combined RF current drive and bootstrap current in tokamaks
International Nuclear Information System (INIS)
By calculating radio frequency current drive (RFCD) and the bootstrap current in a consistent kinetic manner, we find synergistic effects in the total noninductive current density in tokamaks [1]. We include quasilinear diffusion in the Drift Kinetic Equation (DKE) in order to generalize neoclassical theory to highly non-Maxwellian electron distributions due to RFCD. The parallel plasma current is evaluated numerically with the help of the FASTEP Fokker-Planck code [2]. Current drive efficiency is found to be significantly affected by neoclassical effects, even in cases where only circulating electrons interact with the waves. Predictions of the current drive efficiency are made for lower hybrid and electron cyclotron wave current drive scenarios in the presence of bootstrap current. (c) 1999 American Institute of Physics
Thermal energy and bootstrap current in fusion reactor plasmas
International Nuclear Information System (INIS)
For DT fusion reactors with prescribed alpha particle heating power Pα, plasma volume V and burn temperature i> ∼ 10 keV specific relations for the thermal energy content, bootstrap current, central plasma pressure and other quantities are derived. It is shown that imposing Pα and V makes these relations independent of the magnitudes of the density and temperature, i.e. they only depend on Pα, V and shape factors or profile parameters. For model density and temperature profiles analytic expressions for these shape factors and for the factor Cbs in the bootstrap current formula Ibs ∼ Cbs(a/R)1/2βpIp are given. In the design of next-step devices and fusion reactors, the fusion power is a fixed quantity. Prescription of the alpha particle heating power and plasma volume results in specific relations which can be helpful for interpreting computer simulations and for the design of fusion reactors. (author) 5 refs
Bootstrap bound for conformal multi-flavor QCD on lattice
Nakayama, Yu
2016-07-01
The recent work by Iha et al. shows an upper bound on mass anomalous dimension γ m of multi-flavor massless QCD at the renormalization group fixed point from the conformal bootstrap in SU( N F ) V symmetric conformal field theories under the assumption that the fixed point is realizable with the lattice regularization based on staggered fermions. We show that the almost identical but slightly stronger bound applies to the regularization based on Wilson fermions (or domain wall fermions) by studying the conformal bootstrap in SU( N f ) L × SU( N f ) R symmetric conformal field theories. For N f = 8, our bound implies γ m < 1 .31 to avoid dangerously irrelevant operators that are not compatible with the lattice symmetry.
A bootstrap lunar base: Preliminary design review 2
1987-01-01
A bootstrap lunar base is the gateway to manned solar system exploration and requires new ideas and new designs on the cutting edge of technology. A preliminary design for a Bootstrap Lunar Base, the second provided by this contractor, is presented. An overview of the work completed is discussed as well as the technical, management, and cost strategies to complete the program requirements. The lunar base design stresses the transforming capabilities of its lander vehicles to aid in base construction. The design also emphasizes modularity and expandability in the base configuration to support the long-term goals of scientific research and profitable lunar resource exploitation. To successfully construct, develop, and inhabit a permanent lunar base, however, several technological advancements must first be realized. Some of these technological advancements are also discussed.
Bootstrap bound for conformal multi-flavor QCD on lattice
Nakayama, Yu
2016-01-01
The recent work by Iha et al shows an upper bound on mass anomalous dimension $\\gamma_m$ of multi-flavor massless QCD at the renormalization group fixed point from the conformal bootstrap in $SU(N_F)_V$ symmetric conformal field theories under the assumption that the fixed point is realizable with the lattice regularization based on staggered fermions. We show that the almost identical but slightly stronger bound applies to the regularization based on Wilson fermions (or domain wall fermions) by studying the conformal bootstrap in $SU(N_f)_L \\times SU(N_f)_R$ symmetric conformal field theories. For $N_f=8$, our bound implies $\\gamma_m < 1.31$ to avoid dangerously irrelevant operators that are not compatible with the lattice symmetry.
Conformal bootstrap: non-perturbative QFT's under siege
CERN. Geneva
2016-01-01
[Exceptionally in Council Chamber] Originally formulated in the 70's, the conformal bootstrap is the ambitious idea that one can use internal consistency conditions to carve out, and eventually solve, the space of conformal field theories. In this talk I will review recent developments in the field which have boosted this program to a new level. I will present a method to extract quantitative informations in strongly-interacting theories, such as 3D Ising, O(N) vector model and even systems without a Lagrangian formulation. I will explain how these techniques have led to the world record determination of several critical exponents. Finally, I will review exact analytical results obtained using bootstrap techniques.
Bootstrapping a Five-Loop Amplitude from Steinmann Relations
Caron-Huot, Simon; McLeod, Andrew; von Hippel, Matt
2016-01-01
The analytic structure of scattering amplitudes is restricted by Steinmann relations, which enforce the vanishing of certain discontinuities of discontinuities. We show that these relations dramatically simplify the function space for the hexagon function bootstrap in planar maximally supersymmetric Yang-Mills theory. Armed with this simplification, along with the constraints of dual conformal symmetry and Regge exponentiation, we obtain the complete five-loop six-particle amplitude.
Directed rigidity and bootstrap percolation in (1+1) dimensions
de Menezes, Marcio Argollo; Moukarzel, Cristian F.
1999-01-01
We study directed rigidity percolation (equivalent to directed bootstrap percolation) on three different lattices: square, triangular, and augmented triangular. The first two of these display a first-order transition at p=1, while the augmented triangular lattice shows a continuous transition at a non-trivial p_c. On the augmented triangular lattice we find, by extensive numerical simulation, that the directed rigidity percolation transition belongs to the same universality class as directed ...
Bootstrapping an empty repertoire of experience: the design case
Saliou, Philippe; Ribaud, Vincent
2009-01-01
Performing good design is a difficult task. To take up this challenge, practitioners rely on their repertoire of experience. Students, however, do not have any such repertoire. We propose an approach aimed at bootstrapping the repertoire. The approach is generally accomplished in two steps: tailoring the activity - acquiring a minimal structure through a deductive approach, then initializing the repertoire through an inductive approach; and performing the activity - to begin filling the reper...
Educational efficiency in a dea-bootstrap approach
Francesca Giambona; Erasmo Vassallo; Elli Vassiliadis
2010-01-01
We use the PISA 2006 results to analyse the students' proficiencies in 24 European Countries with regard to two indexes that represent the educational resources available at home and the family background of students. Many factors affect the proficiencies and therefore, using a DEA-bootstrap method, we intend to measure the efficiency of the European educational systems as capability to ensure high students' competencies despite adverse conditions about the educational resources available in ...
'Bootstrap' charging of surfaces composed of multiple materials
Stannard, P. R.; Katz, I.; Parks, D. E.
1981-01-01
The paper examines the charging of a checkerboard array of two materials, only one of which tends to acquire a negative potential alone, using the NASA Charging Analyzer Program (NASCAP). The influence of the charging material's field causes the otherwise 'non-charging' material to acquire a negative potential due to the suppression of its secondary emission ('bootstrap' charging). The NASCAP predictions for the equilibrium potential difference between the two materials are compared to results based on an analytical model.
Higgs Critical Exponents and Conformal Bootstrap in Four Dimensions
DEFF Research Database (Denmark)
Antipin, Oleg; Mølgaard, Esben; Sannino, Francesco
2015-01-01
We investigate relevant properties of composite operators emerging in nonsupersymmetric, four-dimensional gauge-Yukawa theories with interacting conformal fixed points within a precise framework. The theories investigated in this work are structurally similar to the standard model of particle int...... bootstrap results are then compared to precise four dimensional conformal field theoretical results. To accomplish this, it was necessary to calculate explicitly the crossing symmetry relations for the global symmetry group SU($N$)$\\times$SU($N$)....
Spectrum of local boundary operators from boundary form factor bootstrap
Szots, M.; Takacs, G.
2007-01-01
Using the recently introduced boundary form factor bootstrap equations, we map the complete space of their solutions for the boundary version of the scaling Lee-Yang model and sinh-Gordon theory. We show that the complete space of solutions, graded by the ultraviolet behaviour of the form factors can be brought into correspondence with the spectrum of local boundary operators expected from boundary conformal field theory, which is a major evidence for the correctness of the boundary form fact...
Bootstrap and the physical values of $\\pi N$ resonance parameters
Semenov-Tian-Shansky, Kirill M.; Vereshagin, Alexander V.; Vereshagin, Vladimir V.
2007-01-01
This is the 6th paper in the series developing the formalism to manage the effective scattering theory of strong interactions. Relying on the theoretical scheme suggested in our previous publications we concentrate here on the practical aspect and apply our technique to the elastic pion-nucleon scattering amplitude. We test numerically the pion-nucleon spectrum sum rules that follow from the tree level bootstrap constraints. We show how these constraints can be used to estimate the tensor and...
Study and Integrate Bootstrap 3 for OpixManager
Tapani, Zhejia
2010-01-01
ABSTRACT This bachelor thesis is about how to study and integrate Bootstrap 3 into OpixManager. The purpose is to improve user interface of OpixManager application. OpixManager is constructed by using CodeIgniter and Model-View-Controller (MVC) framework. OpixManager application is for project management. It includes staff augmentation, customer management, report management and so on. It is to support both scrum and traditional software development process. There are two major parts...
Addressing the P2P Bootstrap Problem for Small Networks
Wolinsky, David Isaac; Juste, Pierre St.; Boykin, P. Oscar; Figueiredo, Renato
2010-01-01
P2P overlays provide a framework for building distributed applications consisting of few to many resources with features including self-configuration, scalability, and resilience to node failures. Such systems have been successfully adopted in large-scale services for content delivery networks, file sharing, and data storage. In small-scale systems, they can be useful to address privacy concerns and for network applications that lack dedicated servers. The bootstrap problem, finding an existi...
A conformal bootstrap approach to critical percolation in two dimensions
Picco, Marco; Santachiara, Raoul
2016-01-01
We study four-point functions of critical percolation in two dimensions, and more generally of the Potts model. We propose an exact ansatz for the spectrum: an infinite, discrete and non-diagonal combination of representations of the Virasoro algebra. Based on this ansatz, we compute four-point functions using a numerical conformal bootstrap approach. The results agree with Monte-Carlo computations of connectivities of random clusters.
Bootstrapping Security Policies for Wearable Apps Using Attributed Structural Graphs
González-Tablas, Ana I.; Tapiador, Juan E.
2016-01-01
We address the problem of bootstrapping security and privacy policies for newly-deployed apps in wireless body area networks (WBAN) composed of smartphones, sensors and other wearable devices. We introduce a framework to model such a WBAN as an undirected graph whose vertices correspond to devices, apps and app resources, while edges model structural relationships among them. This graph is then augmented with attributes capturing the features of each entity together with user-defined tags. We...
Current profile control for high bootstrap current operation in ITER
International Nuclear Information System (INIS)
For the achievement of steady-state fusion power plant, non-inductively current-driven plasma operation should be maintained in tokamak fusion reactors. Total non-inductive current is a summation of bootstrap current proportional to the plasma pressure gradient and externally driven non-inductive current such as neutral beam driven current. Especially in order to establish a commercial reactor, it is necessary to reduce the amount of external current-drive power and to maintain the majority of the plasma current with bootstrap current. Burning plasma has high autonomy, so the change in current density profile including changes in particle and heat transports should be checked. In this study time-evolution analysis of the current density profile for burning plasmas in the ITER machine has been conducted by using 2.0-dimensional equilibrium, 1.5-dimensional-transport code (TOTAL code). Here current-diffusive ballooning mode model was adopted as a heat transport model. It is concluded that external current-drive is required both in the center and near the periphery of the plasma in order to maintain steady-state profiles of temperature and density with high bootstrap current fraction. (author)
Truncatable bootstrap equations in algebraic form and critical surface exponents
Gliozzi, Ferdinando
2016-01-01
We describe examples of drastic truncations of conformal bootstrap equations encoding much more information than that obtained by a direct numerical approach. A three-term truncation of the four point function of a free scalar in any space dimensions provides algebraic identities among conformal block derivatives which generate the exact spectrum of the infinitely many primary operators contributing to it. In boundary conformal field theories, we point out that the appearance of free parameters in the solutions of bootstrap equations is not an artifact of truncations, rather it reflects a physical property of permeable conformal interfaces which are described by the same equations. Surface transitions correspond to isolated points in the parameter space. We are able to locate them in the case of 3d Ising model, thanks to a useful algebraic form of 3d boundary bootstrap equations. It turns out that the low-lying spectra of the surface operators in the ordinary and the special transitions of 3d Ising model form...
Comparison Of Modified Bootstrap And Conventional Sensitometry In Medical Radiography
Bednarek, Daniel R.; Rudin, Stephen
1980-08-01
A new modified bootstrap approach to sensitometry is presented which provides H and D curves that show almost exact agreement with those obtained using conventional methods. Two bootstrap techniques are described; both involve a combination of inverse-square and step-ped wedge modulation of the radiation field and provide intensity-scale sensitometric curves as appropriate for medical radiography. H and D curves obtained with these modified techniques are compared with those obtained for screen-film combinations using inverse-square sensitometry as well as with those obtained for direct x-ray film using time-scale sensitometry. The stepped-wedge of the Wisconsin X-Ray Test Cassette was used in the boot-strap approach since it provides sufficient exposure latitude to encompass the useful den-sity range of medical x-ray film. This approach makes radiographic sensitometry quick and convenient, allowing accurate characteristic curves to be obtained for any screen-film cassette using standard diagnostic equipment.
Using minimum bootstrap support for splits to construct confidence regions for trees
Directory of Open Access Journals (Sweden)
Edward Susko
2006-01-01
Full Text Available Many of the estimated topologies in phylogenetic studies are presented with the bootstrap support for each of the splits in the topology indicated. If phylogenetic estimation is unbiased, high bootstrap support for a split suggests that there is a good deal of certainty that the split actually is present in the tree and low bootstrap support suggests that one or more of the taxa on one side of the estimated split might in reality be located with taxa on the other side. In the latter case the follow-up questions about how many and which of the taxa could reasonably be incorrectly placed as well as where they might alternatively be placed are not addressed through the presented bootstrap support. We present here an algorithm that finds the set of all trees with minimum bootstrap support for their splits greater than some given value. The output is a ranked list of trees, ranked according to the minimum bootstrap supports for splits in the trees. The number of such trees and their topologies provides useful supplementary information in bootstrap analyses about the reasons for low bootstrap support for splits. We also present ways of quantifying low bootstrap support by considering the set of all topologies with minimum bootstrap greater than some quantity as providing a confidence region of topologies. Using a double bootstrap we are able to choose a cutoff so that the set of topologies with minimum bootstrap support for a split greater than that cutoff gives an approximate 95% confidence region. As with bootstrap support one advantage of the methods is that they are generally applicable to the wide variety of phylogenetic estimation methods.
Parks, Nathan A; Gannon, Matthew A; Long, Stephanie M; Young, Madeleine E
2016-01-01
Analysis of event-related potential (ERP) data includes several steps to ensure that ERPs meet an appropriate level of signal quality. One such step, subject exclusion, rejects subject data if ERP waveforms fail to meet an appropriate level of signal quality. Subject exclusion is an important quality control step in the ERP analysis pipeline as it ensures that statistical inference is based only upon those subjects exhibiting clear evoked brain responses. This critical quality control step is most often performed simply through visual inspection of subject-level ERPs by investigators. Such an approach is qualitative, subjective, and susceptible to investigator bias, as there are no standards as to what constitutes an ERP of sufficient signal quality. Here, we describe a standardized and objective method for quantifying waveform quality in individual subjects and establishing criteria for subject exclusion. The approach uses bootstrap resampling of ERP waveforms (from a pool of all available trials) to compute a signal-to-noise ratio confidence interval (SNR-CI) for individual subject waveforms. The lower bound of this SNR-CI (SNRLB ) yields an effective and objective measure of signal quality as it ensures that ERP waveforms statistically exceed a desired signal-to-noise criterion. SNRLB provides a quantifiable metric of individual subject ERP quality and eliminates the need for subjective evaluation of waveform quality by the investigator. We detail the SNR-CI methodology, establish the efficacy of employing this approach with Monte Carlo simulations, and demonstrate its utility in practice when applied to ERP datasets. PMID:26903849
Optimization of bootstrap current in a large helical system with L = 2
International Nuclear Information System (INIS)
Neoclassical bootstrap currents in the banana and plateau regions are evaluated for an L = 2 large helical system with the major radius of 5 m. Various vacuum magnetic field configurations are invoked to optimize the bootstrap current. In the banana region shifting the magnetic axis and shaping magnetic surfaces have remarkable effects on the bootstrap current and it is clarified that a small outward shift of the magnetic axis and vertically elongated magnetic surfaces are favourable to reduce the bootstrap current. On the contrary, the bootstrap current in the plateau region depends strongly on the toroidal pitch number of helical winding coils but shifting the axis and shaping magnetic surfaces are not effective. The magnitude of bootstrap current is estimated for plasmas in the large helical system predicted by a one dimensional transport code. (author)
Better confidence intervals for left censored data using bias corrected bootstrap method
International Nuclear Information System (INIS)
Estimation of the 95% confidence intervals of the population parameters of small sized (say <= 30) environmental data samples under conventional statistical methodologies are error prone because the probability density function associated with the specified data sets, most of the times, is questionable. Therefore, in instances when the distribution of a statistic is unknown, nonparametric methods such as bootstrap override the conventional ones. The nonparametric (percentile) bootstrap method has been used to evaluate the confidence intervals of the mean. This paper describes the application of bias-corrected percentile bootstrap method that yields better confidence intervals than the percentile bootstrap method. An inter-comparative study of the two methods is also carried out. A case study with air activity data recorded from a specific Indian nuclear power plant is presented to support the superiority of bias corrected bootstrap method over the percentile bootstrap method and the conventional students -t method. (author)
Asal Bileşenler Analizine Bootstrap Yaklaşımı
AKTÜKÜN, Dr. Aylin
2011-01-01
Bu çalışmada, bootstrap yöntemlerin asal bileşenler analizine uygulanma sürecini sunduk. Hipotetik bir veri ile asal bileşenler analizinde başvurulan bazı güven aralıklarının bootstrap yöntemlerle nasıl gerçekleştirilebileceğini gösterdik. Makaledeki tüm bootstrap süreçleri Mathematica dilinde yazdığımız bir programla gerçekleştirdik. Anahtar Kelimeler: Asal bileşenler analizi, Bootstrap, Bootstrap kantiller, Bootstrap Güven Aralıkları, Mathematica. ABSRACT In this paper, we apply ...
An EMD based method for detrending RR interval series without resampling
Institute of Scientific and Technical Information of China (English)
曾超; 蒋奇云; 陈朝阳; 徐敏
2015-01-01
Slow trends in the RR interval (RRI) series should be removed in the preprocessing step to get a reliable result of heart rate variability (HRV) analysis. Re-sampling is required to convert the unevenly sampled RRI series into evenly sampled time series when using the widely accepted smoothness priors approach (SPA). Noise is introduced in this process and the information quality is thus compromised. Empirical mode decomposition (EMD) and its variants, were introduced to directly process the unevenly sampled RRI series. Besides, a RR interval model was proposed to fascinate the introduction of standard metrics for the evaluation of the detrending performance. Based on standard metrics including signal-to-noise-ratio in dB (ISNR), mean square error (EMS), and percent root square difference (DPRS), the effectiveness of detrending methods in RR interval analysis were determined. Results demonstrate that complementary ensemble EMD (CEEMD, a variant of EMD) based method has a higherISNR, a lowerEMS and a lowerDPRS as well as a better RRI series detrending performance compared with the SPA method, which would in turn lead to a more accurate HRV analysis.
Mansour, Khalid; Mutanga, Onisimo; Everson, Terry; Adam, Elhadi
2012-06-01
The development of techniques to estimate and map increaser grass species is critical for better understanding the condition of the rangeland and levels of rangeland degradation. This paper investigates whether canopy reflectance spectra, resampled to AISA Eagle resolution can discriminate among four increaser species representing different levels of rangeland degradation. Canopy spectral measurements were taken from the four indicator species: Hyparrhenia hirta (HH), Eragrostis curvula (EC), Sporobolus africanus (SA), and Aristida diffusa (AD). The random forest algorithm and a forward variable selection technique were used to identify optimal wavelengths for discriminating the species. Results revealed that the optimal number of wavelengths (n = 8) that yielded the lowest OOB error (11.36%) in discriminating among the four increaser species are located in 966.7, 877.6, 691.9, 718.7, 902.7, 854.8, 674.1 and 703 nm. These wavelengths are located in the visible, red-edge and near-infrared regions of the electromagnetic spectrum. The random forest algorithm can accurately discriminate species with an overall accuracy of 88.64% and a KHAT value of 0.85. The study demonstrated the possibility to upscale the method to airborne sensors such as AISA Eagle for mapping indicator species of rangeland degradation. A rotational grazing management plan should be considered as a way to create sustainable rangeland management in degraded areas.
Depth inloop resampling using dilation filter for free viewpoint video system
Lee, Seok; Lee, Seungsin; Wey, Hocheon; Lee, Jaejoon; Park, Dusik
2013-03-01
A depth dilation filter is proposed for free viewpoint video system based on mixed resolution multi-view video plus depth (MVD). By applying gray scale dilation filter to depth images, foreground regions are extended to background region, and synthesis artifacts occur out of boundary edge. Thus, objective and subjective quality of view synthesis result is improved. A depth dilation filter is applied to inloop resampling part in encoding/decoding, and post processing part after decoding. Accurate view synthesis is important in virtual view generation for autostereoscopic display, moreover there are many coding tools which use view synthesis to reduce interview redundancy in 3D video coding such as view synthesis prediction (VSP) and depth based motion vector prediction (DMVP), and compression efficiency can be improved by accurate view synthesis. Coding and synthesis experiments are performed for performance evaluation of a dilation filter with MPEG test sequences. Dilation filter was implemented on the top of the MPEG reference software for AVC based 3D video coding. By applying a depth dilation filter, BD-rate gains of 0.5% and 6.0% in terms of PSNR of decoded views and synthesized views, respectively.
A Poisson resampling method for simulating reduced counts in nuclear medicine images
White, Duncan; Lawson, Richard S.
2015-05-01
Nuclear medicine computers now commonly offer resolution recovery and other software techniques which have been developed to improve image quality for images with low counts. These techniques potentially mean that these images can give equivalent clinical information to a full-count image. Reducing the number of counts in nuclear medicine images has the benefits of either allowing reduced activity to be administered or reducing acquisition times. However, because acquisition and processing parameters vary, each user should ideally evaluate the use of images with reduced counts within their own department, and this is best done by simulating reduced-count images from the original data. Reducing the counts in an image by division and rounding off to the nearest integer value, even if additional Poisson noise is added, is inadequate because it gives incorrect counting statistics. This technical note describes how, by applying Poisson resampling to the original raw data, simulated reduced-count images can be obtained while maintaining appropriate counting statistics. The authors have developed manufacturer independent software that can retrospectively generate simulated data with reduced counts from any acquired nuclear medicine image.
Resampling technique in the orthogonal direction for down-looking Synthetic Aperture Imaging Ladar
Li, Guangyuan; Sun, Jianfeng; Lu, Zhiyong; Zhang, Ning; Cai, Guangyu; Sun, Zhiwei; Liu, Liren
2015-09-01
The implementation of down-looking Synthetic Aperture Imaging Ladar(SAIL) uses quadratic phase history reconstruction in the travel direction and linear phase modulation reconstruction in the orthogonal direction. And the linear phase modulation in the orthogonal direction is generated by the shift of two cylindrical lenses in the two polarization-orthogonal beams. Therefore, the fast-moving of two cylindrical lenses is necessary for airborne down-looking SAIL to match the aircraft flight speed and to realize the compression of the orthogonal direction, but the quick start and the quick stop of the cylindrical lenses must greatly damage the motor and make the motion trail non-uniform. To reduce the damage and get relatively well trajectory, we make the motor move like a sinusoidal curve to make it more realistic movement, and through a resampling interpolation imaging algorithm, we can transform the nonlinear phase to linear phase, and get good reconstruction results of point target and area target in laboratory. The influences on imaging quality in different sampling positions when the motor make a sinusoidal motion and the necessity of the algorithm are analyzed. At last, we perform a comparison of the results of two cases in resolution.
A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data
Liang, Faming
2013-03-01
The Gaussian geostatistical model has been widely used in modeling of spatial data. However, it is challenging to computationally implement this method because it requires the inversion of a large covariance matrix, particularly when there is a large number of observations. This article proposes a resampling-based stochastic approximation method to address this challenge. At each iteration of the proposed method, a small subsample is drawn from the full dataset, and then the current estimate of the parameters is updated accordingly under the framework of stochastic approximation. Since the proposed method makes use of only a small proportion of the data at each iteration, it avoids inverting large covariance matrices and thus is scalable to large datasets. The proposed method also leads to a general parameter estimation approach, maximum mean log-likelihood estimation, which includes the popular maximum (log)-likelihood estimation (MLE) approach as a special case and is expected to play an important role in analyzing large datasets. Under mild conditions, it is shown that the estimator resulting from the proposed method converges in probability to a set of parameter values of equivalent Gaussian probability measures, and that the estimator is asymptotically normally distributed. To the best of the authors\\' knowledge, the present study is the first one on asymptotic normality under infill asymptotics for general covariance functions. The proposed method is illustrated with large datasets, both simulated and real. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Reduced bias and threshold choice in the extremal index estimation through resampling techniques
Gomes, Dora Prata; Neves, Manuela
2013-10-01
In Extreme Value Analysis there are a few parameters of particular interest among which we refer to the extremal index, a measure of extreme events clustering. It is of great interest for initial dependent samples, the common situation in many practical situations. Most semi-parametric estimators of this parameter show the same behavior: nice asymptotic properties but a high variance for small values of k, the number of upper order statistics used in the estimation and a high bias for large values of k. The Mean Square Error, a measure that encompasses bias and variance, usually shows a very sharp plot, needing an adequate choice of k. Using classical extremal index estimators considered in the literature, the emphasis is now given to derive reduced bias estimators with more stable paths, obtained through resampling techniques. An adaptive algorithm for estimating the level k for obtaining a reliable estimate of the extremal index is used. This algorithm has shown good results, but some improvements are still required. A simulation study will illustrate the properties of the estimators and the performance of the adaptive algorithm proposed.
Transport simulation of a large-bootstrap-current Tokamak plasma driven by the ohmic seed current
International Nuclear Information System (INIS)
A large-bootstrap-current tokamak plasma driven by the ohmic seed current has been studied for inductively-operated ultra-long-pulse tokamak fusion reactors. The safety factor profile with the negative magnetic shear has been demonstrated only by the combination of the ohmic and bootstrap currents, by adjusting the density profile, and the bootstrap current fraction more than 80% is realized with the help of the increased q(0) value. 7 refs., 4 figs., 1 tab
On variance estimation and a goodness-of-fit test using the bootstrap method
Amiri, Saeid
2009-01-01
This thesis deals with the study of variance estimation using the bootstrap method, including the problem of choosing between nonparametric and parametric bootstrap methods. Paper I compares the two approaches, determines which method is preferable and analyses the accuracy of the approximations. The underlying concept of parametric bootstrap is based on the assumption of correct choice of parametric distribution. Paper II therefore considers goodness-of-fit tests and presents a new test base...
Full Hirshman-Sigmar model for bootstrap current estimate in the ETE small aspect ratio Tokamak
International Nuclear Information System (INIS)
An estimate of the bootstrap current through the full Hirshman-Sigmar model, which is the most accurate available for thermal plasmas up to now, will be carried out the ETE tokamak. These results will be compared to previous calculations performed with the single-ion collisionless Hirshman model in order to check possible limitations imposed by this model on the bootstrap current estimate. The dependences of the bootstrap current profile upon the plasma parameters will also be briefly illustrated. (author)
Performance of the bootstrap for DEA estimators and iterating the principle
Simar, Léopold; Wilson, Paul
2000-01-01
This paper further examines the bootstrap method proposed by Simar and Wilson (1998) for DEA efficiency estimators. Some simplifications are provided, and we provide Monte Carlo evidence on the coverage probabilities of confidence intervals estimated by the method. In addition, we provide similar evidence for confidence intervals estimate with the so-called naive bootstrap, which is known to be inconsistent in the DEA setting. Finally, we propose an interated version of the bootstrap which ma...
Higher-order accuracy of multiscale-double bootstrap for testing regions
Shimodaira, Hidetoshi
2013-01-01
We consider hypothesis testing for the null hypothesis being represented as an arbitrary-shaped region in the parameter space. We compute an approximate p-value by counting how many times the null hypothesis holds in bootstrap replicates. This frequency, known as bootstrap probability, is widely used in evolutionary biology, but often reported as biased in the literature. Based on the asymptotic theory of bootstrap confidence intervals, there have been some new attempts for adjusting the bias...
A PARAMETRIC BOOTSTRAP USING THE FIRST FOUR
MOMENTS OF THE RESIDUALS
Treyens, Pierre-Eric
2007-01-01
We consider linear regression models and we suppose that disturbances are either Gaussian or non Gaussian. Until now, within the framework of the bootstrap, we thought that the error in rejection probability (ERP) had the same rate of convergence with the parametric bootstrap or the nonparametric bootstrap. For linear data generating processes (DGP) we show in this paper that this assertion is false if skewness and/or kurtosis coefficients of the distribution of the disturbances are nonnull. ...
Bootstrap Co-integration Rank Testing: The Effect of Bias-Correcting Parameter Estimates
Cavaliere, Giuseppe; Taylor, A. M. Robert; Trenkler, Carsten
2013-01-01
In this paper we investigate bootstrap-based methods for bias-correcting the first-stage parameter estimates used in some recently developed bootstrap implementations of the co-integration rank tests of Johansen (1996). In order to do so we adapt the framework of Kilian (1998) which estimates the bias in the original parameter estimates using the average bias in the corresponding parameter esti- mates taken across a large number of auxiliary bootstrap replications. A number of possible imp...
Learning robust cell signalling models from high throughput proteomic data
Koch, Mitchell; Broom, Bradley M.; Subramanian, Devika
2009-01-01
We propose a framework for learning robust Bayesian network models of cell signalling from high-throughput proteomic data. We show that model averaging using Bayesian bootstrap resampling generates more robust structures than procedures that learn structures using all of the data. We also develop an algorithm for ranking the importance of network features using bootstrap resample data. We apply our algorithms to derive the T-cell signalling network from the flow cytometry data of Sachs et al....
First estimate of bootstrap current in the ETE small aspect ratio tokamak
International Nuclear Information System (INIS)
A first estimate of the bootstrap current in the ETE (Experimento Tokamak Esferico) small aspect ratio tokamak using the Hirshman single-ion collisionless model shows that we can expect a ratio of 15 to 30% of total bootstrap current in relation to the total equilibrium current depending on the optimization level of the plasma profile parameters. Bootstrap current levels basically depend on the βp values which must be kept under a critical level due to stability conditions and current alignment requirements. Preliminary studies of Shaing's predictions regarding bootstrap current calculations in collisional plasmas are briefly described and different methods for the trapped particle fraction calculation are also illustrated. (Author)
Dale Poirier
2008-01-01
This paper provides Bayesian rationalizations for White’s heteroskedastic consistent (HC) covariance estimator and various modifications of it. An informed Bayesian bootstrap provides the statistical framework.
A Bootstrap Approach to an Affordable Exploration Program
Oeftering, Richard C.
2011-01-01
This paper examines the potential to build an affordable sustainable exploration program by adopting an approach that requires investing in technologies that can be used to build a space infrastructure from very modest initial capabilities. Human exploration has had a history of flight programs that have high development and operational costs. Since Apollo, human exploration has had very constrained budgets and they are expected be constrained in the future. Due to their high operations costs it becomes necessary to consider retiring established space facilities in order to move on to the next exploration challenge. This practice may save cost in the near term but it does so by sacrificing part of the program s future architecture. Human exploration also has a history of sacrificing fully functional flight hardware to achieve mission objectives. An affordable exploration program cannot be built when it involves billions of dollars of discarded space flight hardware, instead, the program must emphasize preserving its high value space assets and building a suitable permanent infrastructure. Further this infrastructure must reduce operational and logistics cost. The paper examines the importance of achieving a high level of logistics independence by minimizing resource consumption, minimizing the dependency on external logistics, and maximizing the utility of resources available. The approach involves the development and deployment of a core suite of technologies that have minimum initial needs yet are able expand upon initial capability in an incremental bootstrap fashion. The bootstrap approach incrementally creates an infrastructure that grows and becomes self sustaining and eventually begins producing the energy, products and consumable propellants that support human exploration. The bootstrap technologies involve new methods of delivering and manipulating energy and materials. These technologies will exploit the space environment, minimize dependencies, and
Two novel applications of bootstrap currents: snakes and jitter stabilization
International Nuclear Information System (INIS)
Both neoclassical theory and certain turbulence theories of particle transport in tokamaks predict the existence of bootstrap (i.e., pressure-driven) currents. Two new applications of this form of non-inductive current are considered in this work. The first is an explanation of the 'snake' phenomenon observed in JET based on steady-state nonlinear tearing theory. The second is an active method of dynamic stabilization of the m=1 mode using the 'jitter' approach suggested by Thyagaraja et al in a recent paper. (author) 11 refs
Characteristics of the bootstrap estimate of discrepant data sets
International Nuclear Information System (INIS)
We present in this paper a Bootstrap Method to estimate a best value and its standard deviation for a discrepant set of data. The method is applied to the determination of the half-lives of 137Cs, 90Sr, 252Cf, Tritium, 35S, 55Fe, and 99Mo. The self-consistency of the method and its capability to reject outliers was tested with good results. The application of the method to the determination of covariance matrices was tried, with poor results. (author)
Microcanonical statistics of black holes and bootstrap condition
Huang, Wung-Hong
2000-01-01
The microcanonical statistics of the Schwarzschild black holes as well as the Reissner-Nordstr$\\sf \\ddot{o}$m black holes are analyzed. In both cases we set up the inequalities in the microcanonical density of states. These are then used to show that the most probable configuration in the gases of black holes is that one black hole acquires all of the mass and all of the charge at high energy limit. Thus the black holes obey the statistical bootstrap condition and, in contrast to the other in...
The S-matrix Bootstrap II: Two Dimensional Amplitudes
Paulos, Miguel F; Toledo, Jonathan; van Rees, Balt C; Vieira, Pedro
2016-01-01
We consider constraints on the S-matrix of any gapped, Lorentz invariant quantum field theory in 1 + 1 dimensions due to crossing symmetry and unitarity. In this way we establish rigorous bounds on the cubic couplings of a given theory with a fixed mass spectrum. In special cases we identify interesting integrable theories saturating these bounds. Our analytic bounds match precisely with numerical bounds obtained in a companion paper where we consider massive QFT in an AdS box and study boundary correlators using the technology of the conformal bootstrap.
Bootstrapped Oblivious Transfer and Secure Two-Party Function Computation
Wang, Ye
2009-01-01
We propose an information theoretic framework for the secure two-party function computation (SFC) problem and introduce the notion of SFC capacity. We study and extend string oblivious transfer (OT) to sample-wise OT. We propose an efficient, perfectly private OT protocol utilizing the binary erasure channel or source. We also propose the bootstrap string OT protocol which provides disjoint (weakened) privacy while achieving a multiplicative increase in rate, thus trading off security for rate. Finally, leveraging our OT protocol, we construct a protocol for SFC and establish a general lower bound on SFC capacity of the binary erasure channel and source.
Bootstrap framework : web-suunnittelun työkaluna
Peltomäki, Veera
2014-01-01
Pienen näytön omaavat mobiililaitteet kasvattavat suosiotaan Internetin selaamisessa. Samaan aikaan modernit pelikonsolit ja SmartTV:t yleistyvät kuluttajien keskuudessa, jolloin Internetiä voi selata suuren näyttötarkkuuden omaavilla laitteilla. Responsiivinen web-suunnittelu vastaa nykypäivän vaatimuksiin, jossa käyttäjät odottavat sivustoilta yhdenmukaista käyttökokemusta, päätelaitteesta riippumatta. Tämä opinnäytetyö käsittelee responsiivisen Bootstrap frameworkin valintaa web-suunni...
Convergence rates of empirical block length selectors for block bootstrap
Nordman, Daniel J.; Lahiri, Soumendra N.
2014-01-01
We investigate the accuracy of two general non-parametric methods for estimating optimal block lengths for block bootstraps with time series – the first proposed in the seminal paper of Hall, Horowitz and Jing (Biometrika 82 (1995) 561–574) and the second from Lahiri et al. (Stat. Methodol. 4 (2007) 292–321). The relative performances of these general methods have been unknown and, to provide a comparison, we focus on rates of convergence for these block length selectors for the moving block ...
Comparing groups randomization and bootstrap methods using R
Zieffler, Andrew S; Long, Jeffrey D
2011-01-01
A hands-on guide to using R to carry out key statistical practices in educational and behavioral sciences research Computing has become an essential part of the day-to-day practice of statistical work, broadening the types of questions that can now be addressed by research scientists applying newly derived data analytic techniques. Comparing Groups: Randomization and Bootstrap Methods Using R emphasizes the direct link between scientific research questions and data analysis. Rather than relying on mathematical calculations, this book focus on conceptual explanations and the use of statistica
A survey of bootstrap methods in finite population sampling
Directory of Open Access Journals (Sweden)
Zeinab Mashreghi
2016-03-01
Full Text Available We review bootstrap methods in the context of survey data where the effect of the sampling design on the variability of estimators has to be taken into account. We present the methods in a unified way by classifying them in three classes: pseudo-population, direct, and survey weights methods. We cover variance estimation and the construction of confidence intervals for stratified simple random sampling as well as some unequal probability sampling designs. We also address the problem of variance estimation in presence of imputation to compensate for item non-response.
Two new data-dependent choices of m when applying the m-out-of-n bootstrap to hypothesis testing
Allison, James Samuel; Santana, Leonard; Swanepoel, Jan Willem Hendrik
2011-01-01
The traditional non-parametric bootstrap (referred to as the n-out-of-n bootstrap) is a widely applicable and powerful tool for statistical inference, but in important situations it can fail. It is well known that by using a bootstrap sample of size m, different from n, the resulting m-out-of-n bootstrap provides a method for rectifying the traditional bootstrap inconsistency. Moreover, recent studies have shown that interesting cases exist where it is better to use the m-out-of-n bootstrap i...
Current drive and sustain experiments with the bootstrap current in JT-60
International Nuclear Information System (INIS)
The current drive and sustain experiments with the neoclassical bootstrap current are performed in the JT-60 tokamak. It is shown that up to 80% of total plasma current is driven by the bootstrap current in extremely high βp regime (βp = 3.2) and the current drive product Ip (bootstrap) n-bareRp up to 4.4 x 1019 MAm-2 has been attained with the bootstrap current. The experimental resistive loop voltages are compared with the calculations using the neoclassical resistivity with and without the bootstrap current and the Spitzer resistivity for a wide range of the plasma current (Ip = 0.5 -2 MA) and the poloidal beta (βp = 0.1 - 3.2). The calculated resistive loop voltage is consistent with the neoclassical prediction including the bootstrap current. Current sustain with the bootstrap current is tested by terminating the Ip feedback control during the high power neutral beam heating. An enhancement of the L/R decay time than those expected from the plasma resistivity with measured Te and Zeff has been confirmed experimentally supporting the large non-inductive current in the plasma and is consistent with the neoclassical prediction. A new technique to calculate the bootstrap current in multi-collisionality regime for finite aspect ratio tokamak has bee developed. The neoclassical bootstrap current is calculated directly through the force balance equations between viscous and friction forces according to the Hirshman-Sigmar theory. The bootstrap current driven by the fast ion component is also included. Ballooning stability of the high βp plasma are analyzed using the current profiles including the bootstrap current. The plasma pressure is close to the ballooning limit in high βp discharges. (author)
Resampling method for applying density-dependent habitat selection theory to wildlife surveys.
Directory of Open Access Journals (Sweden)
Olivia Tardy
Full Text Available Isodar theory can be used to evaluate fitness consequences of density-dependent habitat selection by animals. A typical habitat isodar is a regression curve plotting competitor densities in two adjacent habitats when individual fitness is equal. Despite the increasing use of habitat isodars, their application remains largely limited to areas composed of pairs of adjacent habitats that are defined a priori. We developed a resampling method that uses data from wildlife surveys to build isodars in heterogeneous landscapes without having to predefine habitat types. The method consists in randomly placing blocks over the survey area and dividing those blocks in two adjacent sub-blocks of the same size. Animal abundance is then estimated within the two sub-blocks. This process is done 100 times. Different functional forms of isodars can be investigated by relating animal abundance and differences in habitat features between sub-blocks. We applied this method to abundance data of raccoons and striped skunks, two of the main hosts of rabies virus in North America. Habitat selection by raccoons and striped skunks depended on both conspecific abundance and the difference in landscape composition and structure between sub-blocks. When conspecific abundance was low, raccoons and striped skunks favored areas with relatively high proportions of forests and anthropogenic features, respectively. Under high conspecific abundance, however, both species preferred areas with rather large corn-forest edge densities and corn field proportions. Based on random sampling techniques, we provide a robust method that is applicable to a broad range of species, including medium- to large-sized mammals with high mobility. The method is sufficiently flexible to incorporate multiple environmental covariates that can reflect key requirements of the focal species. We thus illustrate how isodar theory can be used with wildlife surveys to assess density-dependent habitat selection
Resampling method for applying density-dependent habitat selection theory to wildlife surveys.
Tardy, Olivia; Massé, Ariane; Pelletier, Fanie; Fortin, Daniel
2015-01-01
Isodar theory can be used to evaluate fitness consequences of density-dependent habitat selection by animals. A typical habitat isodar is a regression curve plotting competitor densities in two adjacent habitats when individual fitness is equal. Despite the increasing use of habitat isodars, their application remains largely limited to areas composed of pairs of adjacent habitats that are defined a priori. We developed a resampling method that uses data from wildlife surveys to build isodars in heterogeneous landscapes without having to predefine habitat types. The method consists in randomly placing blocks over the survey area and dividing those blocks in two adjacent sub-blocks of the same size. Animal abundance is then estimated within the two sub-blocks. This process is done 100 times. Different functional forms of isodars can be investigated by relating animal abundance and differences in habitat features between sub-blocks. We applied this method to abundance data of raccoons and striped skunks, two of the main hosts of rabies virus in North America. Habitat selection by raccoons and striped skunks depended on both conspecific abundance and the difference in landscape composition and structure between sub-blocks. When conspecific abundance was low, raccoons and striped skunks favored areas with relatively high proportions of forests and anthropogenic features, respectively. Under high conspecific abundance, however, both species preferred areas with rather large corn-forest edge densities and corn field proportions. Based on random sampling techniques, we provide a robust method that is applicable to a broad range of species, including medium- to large-sized mammals with high mobility. The method is sufficiently flexible to incorporate multiple environmental covariates that can reflect key requirements of the focal species. We thus illustrate how isodar theory can be used with wildlife surveys to assess density-dependent habitat selection over large
Bootstrap current for small aspect ratio TOKAMAK equilibria
International Nuclear Information System (INIS)
Full text. We present equilibrium features of the very small ratio tokamak, TBR-2 E, with the aspect ratio of 1.6, which is being designed in Brazil - a joint project with the participation of the University of Sao Paulo, the State University of Campinas, and the National Institute for Space Research. The equilibria have been studied by using the SELENE-J code developed at JAERI, Japan, by Tokuda et al. We have concentrated our study on the determination of the stability limit by using the critical pressure criterion for ballooning stability and Mercier criterion for other MHD modes. The β-limit values were calculated for the case of the non-inductive current and found that its maximum lies at elongation of 1.7. Increasing the triangularity, the β-limit values increase, but the maximum continues to stay at the same value of elongation. We have also studied the effect of the neo-classical transport properties by changing the plasma temperature (or β values). In particular, we have studied the trapped particles and bootstrap current. We have found that at temperatures as low as 600 eV the transport is already in banana regime and that the bootstrap current may account for a significant part of the total plasma current. (author)
Interaction of bootstrap-current-driven magnetic islands
International Nuclear Information System (INIS)
The formation and interaction of fluctuating neoclassical pressure gradient driven magnetic islands is examined. The interaction of magnetic islands produces a stochastic region around the separatrices of the islands. This interaction causes the island pressure profile to be broadened, reducing the island bootstrap current and drive for the magnetic island. A model is presented that describes the magnetic topology as a bath of interacting magnetic islands with low to medium poloidal mode number (m congruent 3-30). The islands grow by the bootstrap current effect and damp due to the flattening of the pressure profile near the island separatrix caused by the interaction of the magnetic islands. The effect of this sporadic growth and decay of the islands (''magnetic bubbling'') is not normally addressed in theories of plasma transport due to magnetic fluctuations. The nature of the transport differs from statistical approaches to magnetic turbulence since the radial step size of the plasma transport is now given by the characteristic island width. This model suggests that tokamak experiments have relatively short-lived, coherent, long wavelength magnetic oscillations present in the steep pressure-gradient regions of the plasma. 42 refs
Cluster expansion in the truncated bootstrap model and linear graphs theory
International Nuclear Information System (INIS)
Using the formalism of linear graphs theory, we obtain the cluster expansion for the grand potential of interacting hadronic systems in the framework of the truncated bootstrap model. We show that the coefficients of the expansion are constructed from two classes of Cayley-tree graphs contributing with opposite sign, related to the two-phase nature of the truncated bootstrap model. (orig.)
Bootstrap current in toroidal systems in the presence of a nonuniform radial electric field
International Nuclear Information System (INIS)
The sheared toroidal rotation driven by non-uniform radial electric field can essentially affect on a bootstrap current profile near the edge E-shear layer in the toroidal systems. The high Eγ and pressure gradients would generate the strong peaking off-axis bootstrap current and naturally sustain the hollow current density profile. (author)
Institute of Scientific and Technical Information of China (English)
2000-01-01
In this paper,the author studies the asymptotic accuracies of the one-term Edgeworth expansions and the bootstrap approximation for the studentized MLE from randomly censored exponential population.It is shown that the Edgeworth expansions and the bootstrap approximation are asymptotically close to the exact distribution of the studentized MLE with a rate.
MEAN SQUARED ERRORS OF BOOTSTRAP VARIANCE ESTIMATORS FOR U-STATISTICS
Mizuno, Masayuki; Maesono, Yoshihiko
2011-01-01
In this paper, we obtain an asymptotic representation of the bootstrap variance estimator for a class of U-statistics. Using the representation of the estimator, we will obtain a mean squared error of the variance estimator until the order n^. Also we compare the bootstrap and the jackknife variance estimators, theoretically.
A Bootstrap Generalization of Modified Parallel Analysis for IRT Dimensionality Assessment
Finch, Holmes; Monahan, Patrick
2008-01-01
This article introduces a bootstrap generalization to the Modified Parallel Analysis (MPA) method of test dimensionality assessment using factor analysis. This methodology, based on the use of Marginal Maximum Likelihood nonlinear factor analysis, provides for the calculation of a test statistic based on a parametric bootstrap using the MPA…
Cui, Zhongmin; Kolen, Michael J.
2008-01-01
This article considers two methods of estimating standard errors of equipercentile equating: the parametric bootstrap method and the nonparametric bootstrap method. Using a simulation study, these two methods are compared under three sample sizes (300, 1,000, and 3,000), for two test content areas (the Iowa Tests of Basic Skills Maps and Diagrams…
Bootstrapping to Test for Nonzero Population Correlation Coefficients Using Univariate Sampling
Beasley, William Howard; DeShea, Lise; Toothaker, Larry E.; Mendoza, Jorge L.; Bard, David E.; Rodgers, Joseph Lee
2007-01-01
This article proposes 2 new approaches to test a nonzero population correlation ([rho]): the hypothesis-imposed univariate sampling bootstrap (HI) and the observed-imposed univariate sampling bootstrap (OI). The authors simulated correlated populations with various combinations of normal and skewed variates. With [alpha[subscript "set"
DEFF Research Database (Denmark)
Hounyo, Ulrich
-studentized statistics, our results justify using the bootstrap to esitmate the covariance matrix of a broad class of covolatility estimators. The bootstrap variance estimator is positive semi-definite by construction, an appealing feature that is not always shared by existing variance estimators of the integrated...
The critical behavior of hadronic matter: Comparison of lattice and bootstrap model calculations
Turko, L.
2015-01-01
Statistical bootstrap model and the related concept of the limiting temperature begun the discussion about phase transitions in the hadronic matter. This was also the origin of the quark-gluon plazma concept. We discuss here to which extend lattice studies of QCD critical behavior at non-zero chemical potential are compatible with the statistical bootstrap model calculations.
Bootstrapping the Small Sample Critical Values of the Rescaled Range Statistic
Marwan Izzeldin; Anthony Murphy
2000-01-01
Finite sample critical values of the rescaled range or R/S statistic may be obtained by bootstrapping. The empirical size and power performance of these critical values is good. Using the post blackened, moving block bootstrap helps to replicate the time dependencies in the original data. The Monte Carlo results show that the asymptotic critical values in Lo (1991) should not be used.
Bootstrapping realized volatility and realized beta under a local Gaussianity assumption
DEFF Research Database (Denmark)
Hounyo, Ulrich
The main contribution of this paper is to propose a new bootstrap method for statistics based on high frequency returns. The new method exploits the local Gaussianity and the local constancy of volatility of high frequency returns, two assumptions that can simplify inference in the high frequency...... context, as recently explained by Mykland and Zhang (2009). Our main contributions are as follows. First, we show that the local Gaussian bootstrap is firstorder consistent when used to estimate the distributions of realized volatility and ealized betas. Second, we show that the local Gaussian bootstrap...... matches accurately the first four cumulants of realized volatility, implying that this method provides third-order refinements. This is in contrast with the wild bootstrap of Gonçalves and Meddahi (2009), which is only second-order correct. Third, we show that the local Gaussian bootstrap is able to...
Boundary and Interface CFTs from the Conformal Bootstrap
Gliozzi, F; Meineri, M; Rago, A
2015-01-01
We explore some consequences of the crossing symmetry for defect conformal field theories, focusing on codimension one defects like flat boundaries or interfaces. We study surface transitions of the 3d Ising and other O(N) models through numerical solutions to the crossing equations with the method of determinants. In the extraordinary transition, where the low-lying spectrum of the surface operators is known, we use the bootstrap equations to obtain information on the bulk spectrum of the theory. In the ordinary transition the knowledge of the low-lying bulk spectrum allows to calculate the scale dimension of the relevant surface operator, which compares well with known results of two-loop calculations in 3d. Estimates of various OPE coefficients are also obtained. We also analyze in 4-epsilon dimensions the renormalization group interface between the O(N) model and the free theory and check numerically the results in 3d.
Bootstrapping Security Policies for Wearable Apps Using Attributed Structural Graphs
González-Tablas, Ana I.; Tapiador, Juan E.
2016-01-01
We address the problem of bootstrapping security and privacy policies for newly-deployed apps in wireless body area networks (WBAN) composed of smartphones, sensors and other wearable devices. We introduce a framework to model such a WBAN as an undirected graph whose vertices correspond to devices, apps and app resources, while edges model structural relationships among them. This graph is then augmented with attributes capturing the features of each entity together with user-defined tags. We then adapt available graph-based similarity metrics to find the closest app to a new one to be deployed, with the aim of reusing, and possibly adapting, its security policy. We illustrate our approach through a detailed smartphone ecosystem case study. Our results suggest that the scheme can provide users with a reasonably good policy that is consistent with the user’s security preferences implicitly captured by policies already in place. PMID:27187385
Higgs critical exponents and conformal bootstrap in four dimensions
Antipin, Oleg; Mølgaard, Esben; Sannino, Francesco
2015-06-01
We investigate relevant properties of composite operators emerging in non-supersymmetric, four-dimensional gauge-Yukawa theories with interacting conformal fixed points within a precise framework. The theories investigated in this work are structurally similar to the standard model of particle interactions, but differ by developing perturbative interacting fixed points. We investigate the physical properties of the singlet and the adjoint composite operators quadratic in the Higgs field, and discover, via a direct computation, that the singlet anomalous dimension is substantially larger than the adjoint one. The numerical bootstrap results are, when possible, compared to our precise findings associated to the four dimensional conformal field theoretical results. To accomplish this, it was necessary to calculate explicitly the crossing symmetry relations for the global symmetry group SU( N ) × SU( N ).
Higgs Critical Exponents and Conformal Bootstrap in Four Dimensions
Antipin, Oleg; Sannino, Francesco
2014-01-01
Within a precise framework, we investigate relevant properties of composite operators emerging in nonsupersymmetric, four-dimensional gauge-Yukawa theories with interacting conformal fixed points. The theories investigated in this work are structurally similar to the standard model of particle interactions, but differ from the standard model by developing perturbative interacting fixed points. We investigate the physical properties of the singlet and the adjoint composite operators quadratic in the Higgs field. We show that, in the Veneziano limit, and at the highest known order in perturbation theory, the singlet sector decouples from the other operators. This fact allows us to test the numerical bootstrap constraints against precise four dimensional conformal field theoretical results.
Bootstrap and the physical values of $\\pi N$ resonance parameters
Semenov-Tian-Shansky, Kirill M; Vereshagin, Vladimir V
2007-01-01
This is the 6th paper in the series developing the formalism to manage the effective scattering theory of strong interactions. Relying on the theoretical scheme suggested in our previous publications we concentrate here on the practical aspect and apply our technique to the elastic pion-nucleon scattering amplitude. We test numerically the pion-nucleon spectrum sum rules that follow from the tree level bootstrap constraints. We show how these constraints can be used to estimate the tensor and vector $NN\\rho$ coupling constants. At last, we demonstrate that the tree-level low energy expansion coefficients computed in the framework of our approach show nice agreement with known experimental data. These results allow us to claim that the extended perturbation scheme is quite reasonable from the computational point of view.
The Analytic Bootstrap and AdS Superhorizon Locality
Fitzpatrick, A Liam; Poland, David; Simmons-Duffin, David
2012-01-01
We take an analytic approach to the CFT bootstrap, studying the 4-pt correlators of d > 2 dimensional CFTs in an Eikonal-type limit, where the conformal cross ratios satisfy |u| 2\\Delta_\\phi\\ + 2n for each integer n as l -> infinity. We show how the rate of approach is controlled by the twist and OPE coefficient of the leading twist operator in the \\phi\\ x \\phi\\ OPE, and we discuss SCFTs and the 3d Ising Model as examples. Additionally, we show that the OPE coefficients of other large spin operators appearing in the OPE are bounded as l -> infinity. We interpret these results as a statement about superhorizon locality in AdS for general CFTs.
Bootstrapping Security Policies for Wearable Apps Using Attributed Structural Graphs.
González-Tablas, Ana I; Tapiador, Juan E
2016-01-01
We address the problem of bootstrapping security and privacy policies for newly-deployed apps in wireless body area networks (WBAN) composed of smartphones, sensors and other wearable devices. We introduce a framework to model such a WBAN as an undirected graph whose vertices correspond to devices, apps and app resources, while edges model structural relationships among them. This graph is then augmented with attributes capturing the features of each entity together with user-defined tags. We then adapt available graph-based similarity metrics to find the closest app to a new one to be deployed, with the aim of reusing, and possibly adapting, its security policy. We illustrate our approach through a detailed smartphone ecosystem case study. Our results suggest that the scheme can provide users with a reasonably good policy that is consistent with the user's security preferences implicitly captured by policies already in place. PMID:27187385
Bootstrapping Security Policies for Wearable Apps Using Attributed Structural Graphs
Directory of Open Access Journals (Sweden)
Ana I. González-Tablas
2016-05-01
Full Text Available We address the problem of bootstrapping security and privacy policies for newly-deployed apps in wireless body area networks (WBAN composed of smartphones, sensors and other wearable devices. We introduce a framework to model such a WBAN as an undirected graph whose vertices correspond to devices, apps and app resources, while edges model structural relationships among them. This graph is then augmented with attributes capturing the features of each entity together with user-defined tags. We then adapt available graph-based similarity metrics to find the closest app to a new one to be deployed, with the aim of reusing, and possibly adapting, its security policy. We illustrate our approach through a detailed smartphone ecosystem case study. Our results suggest that the scheme can provide users with a reasonably good policy that is consistent with the user’s security preferences implicitly captured by policies already in place.
Performance of Bootstrap MCEWMA: Study case of Sukuk Musyarakah data
Safiih, L. Muhamad; Hila, Z. Nurul
2014-07-01
Sukuk Musyarakah is one of several instruments of Islamic bond investment in Malaysia, where the form of this sukuk is actually based on restructuring the conventional bond to become a Syariah compliant bond. The Syariah compliant is based on prohibition of any influence of usury, benefit or fixed return. Despite of prohibition, daily returns of sukuk are non-fixed return and in statistic, the data of sukuk returns are said to be a time series data which is dependent and autocorrelation distributed. This kind of data is a crucial problem whether in statistical and financing field. Returns of sukuk can be statistically viewed by its volatility, whether it has high volatility that describing the dramatically change of price and categorized it as risky bond or else. However, this crucial problem doesn't get serious attention among researcher compared to conventional bond. In this study, MCEWMA chart in Statistical Process Control (SPC) is mainly used to monitor autocorrelated data and its application on daily returns of securities investment data has gained widespread attention among statistician. However, this chart has always been influence by inaccurate estimation, whether on base model or its limit, due to produce large error and high of probability of signalling out-of-control process for false alarm study. To overcome this problem, a bootstrap approach used in this study, by hybridise it on MCEWMA base model to construct a new chart, i.e. Bootstrap MCEWMA (BMCEWMA) chart. The hybrid model, BMCEWMA, will be applied to daily returns of sukuk Musyarakah for Rantau Abang Capital Bhd. The performance of BMCEWMA base model showed that its more effective compare to real model, MCEWMA based on smaller error estimation, shorter the confidence interval and smaller false alarm. In other word, hybrid chart reduce the variability which shown by smaller error and false alarm. It concludes that the application of BMCEWMA is better than MCEWMA.
Monte Carlo δf simulation of the bootstrap current in the presence of a magnetic island
International Nuclear Information System (INIS)
In the theoretical description of the neoclassical tearing mode the bootstrap current is assumed to completely vanish inside the magnetic island if finite perpendicular transport can be neglected. In this paper, the effects due to both the finite-orbit width of the trapped ions and their toroidal precession (not included in the standard analytic theory) on the island current are investigated. The evolution of the ion distribution function in toroidal geometry in the presence of a perturbed magnetic equilibrium is computed numerically employing the δf method, collisions being implemented by means of a Monte Carlo procedure. It is shown that a significant fraction of the (ion) bootstrap current survives inside the island when the ion banana width wb approaches the island width W, and no loss is observed for wb/W≥1. This effect is reduced when the collision time becomes longer than the toroidal drift time. The value of the current is found to be inconsistent with the local gradients in the island region. The finite-banana-width effect leads to a linear scaling of the value of the poloidal β at the mode onset with the normalized ion poloidal gyroradius ρ*p, in agreement with the experimental results of ASDEX Upgrade
Langella, Giuliano; Basile, Angelo; Bonfante, Antonello; Manna, Piero; Terribile, Fabio
2013-04-01
Digital soil mapping procedures are widespread used to build two-dimensional continuous maps about several pedological attributes. Our work addressed a regression kriging (RK) technique and a bootstrapped artificial neural network approach in order to evaluate and compare (i) the accuracy of prediction, (ii) the susceptibility of being included in automatic engines (e.g. to constitute web processing services), and (iii) the time cost needed for calibrating models and for making predictions. Regression kriging is maybe the most widely used geostatistical technique in the digital soil mapping literature. Here we tried to apply the EBLUP regression kriging as it is deemed to be the most statistically sound RK flavor by pedometricians. An unusual multi-parametric and nonlinear machine learning approach was accomplished, called BAGAP (Bootstrap aggregating Artificial neural networks with Genetic Algorithms and Principal component regression). BAGAP combines a selected set of weighted neural nets having specified characteristics to yield an ensemble response. The purpose of applying these two particular models is to ascertain whether and how much a more cumbersome machine learning method could be much promising in making more accurate/precise predictions. Being aware of the difficulty to handle objects based on EBLUP-RK as well as BAGAP when they are embedded in environmental applications, we explore the susceptibility of them in being wrapped within Web Processing Services. Two further kinds of aspects are faced for an exhaustive evaluation and comparison: automaticity and time of calculation with/without high performance computing leverage.
JuliBootS: a hands-on guide to the conformal bootstrap
Paulos, Miguel F
2014-01-01
We introduce {\\tt JuliBootS}, a package for numerical conformal bootstrap computations coded in {\\tt Julia}. The centre-piece of {\\tt JuliBootS} is an implementation of Dantzig's simplex method capable of handling arbitrary precision linear programming problems with continuous search spaces. Current supported features include conformal dimension bounds, OPE bounds, and bootstrap with or without global symmetries. The code is trivially parallelizable on one or multiple machines. We exemplify usage extensively with several real-world applications. In passing we give a pedagogical introduction to the numerical bootstrap methods.
Ion-Banana-Orbit-Width Effect on Bootstrap Current for Small Magnetic Islands
International Nuclear Information System (INIS)
A simple and direct theoretical method has been proposed to investigate the so-called ion-banana-orbit-width (IBW) effect on the bootstrap current in the region of magnetic islands generated by the neoclassical tearing mode (NTM). The result shows that, when the IBW approaches the island width, the (ion) bootstrap current can be partly restored inside the island while the pressure profile is flattened. This can lead to the reduction of the bootstrap current drive on the NTM. The strength of the IBW effect on the NTM is related to the safety factor and the inverse aspect ratio on the rational surface
Bootstrap current in low aspect ratio tokamaks using Maschke equilibrium model
International Nuclear Information System (INIS)
A study of relevant aspects of equilibrium and bootstrap current in low-aspect-ratio tokamaks is made using the Maschke equilibrium model, which provides analytic and exact solution of the Grad-Shafranov equation. The current profile in the Maschke model is parabolic, which is a good approximation for actual experimentally observed ones. The results are compared with the Soloviev equilibrium model, that has the current profile almost flat. It is shown that the bootstrap current depends on the geometrical parameter of the plasma column, that is, elongation. The bootstrap current increases with the inverse aspect ratio for elongated cross-section of the plasma column. (author). 6 refs., 2 figs
Bootstrap confidence intervals in a complex situation: A sequential paired clinical trial
International Nuclear Information System (INIS)
This paper considers the problem of determining a confidence interval for the difference between two treatments in a simplified sequential paired clinical trial, which is analogous to setting an interval for the drift of a random walk subject to a parabolic stopping boundary. Three bootstrap methods of construction are applied: Efron's accelerated bias-covered, the DiCiccio-Romano, and the bootstrap-t. The results are compared with a theoretical approximate interval due to Siegmund. Difficulties inherent in the use of these bootstrap methods in a complex situations are illustrated. The DiCiccio-Romano method is shown to be the easiest to apply and to work well. 13 refs
Francq, Bernard G; Cartiaux, Olivier
2016-09-10
Resecting bone tumors requires good cutting accuracy to reduce the occurrence of local recurrence. This issue is considerably reduced with a navigated technology. The estimation of extreme proportions is challenging especially with small or moderate sample sizes. When no success is observed, the commonly used binomial proportion confidence interval is not suitable while the rule of three provides a simple solution. Unfortunately, these approaches are unable to differentiate between different unobserved events. Different delta methods and bootstrap procedures are compared in univariate and linear mixed models with simulations and real data by assuming the normality. The delta method on the z-score and parametric bootstrap provide similar results but the delta method requires the estimation of the covariance matrix of the estimates. In mixed models, the observed Fisher information matrix with unbounded variance components should be preferred. The parametric bootstrap, easier to apply, outperforms the delta method for larger sample sizes but it may be time costly. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26990871
Bootstrapping de-shadowing and self-calibration for scanning electron microscope photometric stereo
International Nuclear Information System (INIS)
In this paper, we present a novel approach that addresses the blind reconstruction problem in scanning electron microscope (SEM) photometric stereo. Using only two observed images that suffer from shadowing effects, our method automatically calibrates the parameter and resolves shadowing errors for estimating an accurate three-dimensional (3D) shape and underlying shadowless images. We introduce a novel shadowing compensation model using image intensities for both cases of presence and absence of shadowing. With this model, the proposed de-shadowing algorithm iteratively compensates for image intensities and modifies the corresponding 3D surface. Besides de-shadowing, we introduce a practically useful self-calibration criterion by enforcing a good reconstruction. We show that incorrect parameters will engender significant distortions of 3D reconstructions in shadowed regions during the de-shadowing procedure. This motivated us to design the self-calibration criterion by utilizing shadowing to pursue the proper parameter that produces the best reconstruction with least distortions. As a result, we develop a bootstrapping approach for simultaneous de-shadowing and self-calibration in SEM photometric stereo. Extensive experiments on real image data demonstrate the effectiveness of our method. (paper)