Hadronic equation of state in the statistical bootstrap model and linear graph theory
International Nuclear Information System (INIS)
Fre, P.; Page, R.
1976-01-01
Taking a statistical mechanical point og view, the statistical bootstrap model is discussed and, from a critical analysis of the bootstrap volume comcept, it is reached a physical ipothesis, which leads immediately to the hadronic equation of state provided by the bootstrap integral equation. In this context also the connection between the statistical bootstrap and the linear graph theory approach to interacting gases is analyzed
Efficient bootstrap estimates for tail statistics
Breivik, Øyvind; Aarnes, Ole Johan
2017-03-01
Bootstrap resamples can be used to investigate the tail of empirical distributions as well as return value estimates from the extremal behaviour of the sample. Specifically, the confidence intervals on return value estimates or bounds on in-sample tail statistics can be obtained using bootstrap techniques. However, non-parametric bootstrapping from the entire sample is expensive. It is shown here that it suffices to bootstrap from a small subset consisting of the highest entries in the sequence to make estimates that are essentially identical to bootstraps from the entire sample. Similarly, bootstrap estimates of confidence intervals of threshold return estimates are found to be well approximated by using a subset consisting of the highest entries. This has practical consequences in fields such as meteorology, oceanography and hydrology where return values are calculated from very large gridded model integrations spanning decades at high temporal resolution or from large ensembles of independent and identically distributed model fields. In such cases the computational savings are substantial.
Statistical bootstrap approach to hadronic matter and multiparticle reactions
International Nuclear Information System (INIS)
Ilgenfritz, E.M.; Kripfganz, J.; Moehring, H.J.
1977-01-01
The authors present the main ideas behind the statistical bootstrap model and recent developments within this model related to the description of fireball cascade decay. Mathematical methods developed in this model might be useful in other phenomenological schemes of strong interaction physics; they are described in detail. The present status of applications of the model to various hadronic reactions is discussed. When discussing the relations of the statistical bootstrap model to other models of hadron physics the authors point out possibly fruitful analogies and dynamical mechanisms which are modelled by the bootstrap dynamics under definite conditions. This offers interpretations for the critical temperature typical for the model and indicates futher fields of application. (author)
Solution of the statistical bootstrap with Bose statistics
International Nuclear Information System (INIS)
Engels, J.; Fabricius, K.; Schilling, K.
1977-01-01
A brief and transparent way to introduce Bose statistics into the statistical bootstrap of Hagedorn and Frautschi is presented. The resulting bootstrap equation is solved by a cluster expansion for the grand canonical partition function. The shift of the ultimate temperature due to Bose statistics is determined through an iteration process. We discuss two-particle spectra of the decaying fireball (with given mass) as obtained from its grand microcanonical level density
Off-critical statistical models: factorized scattering theories and bootstrap program
International Nuclear Information System (INIS)
Mussardo, G.
1992-01-01
We analyze those integrable statistical systems which originate from some relevant perturbations of the minimal models of conformal field theories. When only massive excitations are present, the systems can be efficiently characterized in terms of the relativistic scattering data. We review the general properties of the factorizable S-matrix in two dimensions with particular emphasis on the bootstrap principle. The classification program of the allowed spins of conserved currents and of the non-degenerate S-matrices is discussed and illustrated by means of some significant examples. The scattering theories of several massive perturbations of the minimal models are fully discussed. Among them are the Ising model, the tricritical Ising model, the Potts models, the series of the non-unitary minimal models M 2,2n+3 , the non-unitary model M 3,5 and the scaling limit of the polymer system. The ultraviolet limit of these massive integrable theories can be exploited by the thermodynamics Bethe ansatz, in particular the central charge of the original conformal theories can be recovered from the scattering data. We also consider the numerical method based on the so-called conformal space truncated approach which confirms the theoretical results and allows a direct measurement of the scattering data, i.e. the masses and the S-matrix of the particles in bootstrap interaction. The problem of computing the off-critical correlation functions is discussed in terms of the form-factor approach
RANDOM QUADRATIC-FORMS AND THE BOOTSTRAP FOR U-STATISTICS
DEHLING, H; MIKOSCH, T
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,
Bootstrap prediction and Bayesian prediction under misspecified models
Fushiki, Tadayoshi
2005-01-01
We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...
Computerized statistical analysis with bootstrap method in nuclear medicine
International Nuclear Information System (INIS)
Zoccarato, O.; Sardina, M.; Zatta, G.; De Agostini, A.; Barbesti, S.; Mana, O.; Tarolo, G.L.
1988-01-01
Statistical analysis of data samples involves some hypothesis about the features of data themselves. The accuracy of these hypotheses can influence the results of statistical inference. Among the new methods of computer-aided statistical analysis, the bootstrap method appears to be one of the most powerful, thanks to its ability to reproduce many artificial samples starting from a single original sample and because it works without hypothesis about data distribution. The authors applied the bootstrap method to two typical situation of Nuclear Medicine Department. The determination of the normal range of serum ferritin, as assessed by radioimmunoassay and defined by the mean value ±2 standard deviations, starting from an experimental sample of small dimension, shows an unacceptable lower limit (ferritin plasmatic levels below zero). On the contrary, the results obtained by elaborating 5000 bootstrap samples gives ans interval of values (10.95 ng/ml - 72.87 ng/ml) corresponding to the normal ranges commonly reported. Moreover the authors applied the bootstrap method in evaluating the possible error associated with the correlation coefficient determined between left ventricular ejection fraction (LVEF) values obtained by first pass radionuclide angiocardiography with 99m Tc and 195m Au. The results obtained indicate a high degree of statistical correlation and give the range of r 2 values to be considered acceptable for this type of studies
Kepler Planet Detection Metrics: Statistical Bootstrap Test
Jenkins, Jon M.; Burke, Christopher J.
2016-01-01
This document describes the data produced by the Statistical Bootstrap Test over the final three Threshold Crossing Event (TCE) deliveries to NExScI: SOC 9.1 (Q1Q16)1 (Tenenbaum et al. 2014), SOC 9.2 (Q1Q17) aka DR242 (Seader et al. 2015), and SOC 9.3 (Q1Q17) aka DR253 (Twicken et al. 2016). The last few years have seen significant improvements in the SOC science data processing pipeline, leading to higher quality light curves and more sensitive transit searches. The statistical bootstrap analysis results presented here and the numerical results archived at NASAs Exoplanet Science Institute (NExScI) bear witness to these software improvements. This document attempts to introduce and describe the main features and differences between these three data sets as a consequence of the software changes.
Bootstrapping pronunciation models
CSIR Research Space (South Africa)
Davel, M
2006-07-01
Full Text Available -scarce language. During the procedure known as ‘bootstrapping’, a model is improved iteratively via a controlled series of increments, at each stage using the previous model to generate the next. This self- improving circularity distinguishes bootstrapping...-to-phoneme rules (the second representation) can be used to identify possible errors that require re-verification. In contrast, during the bootstrapping of acoustic models for speech recognition, both representations are amenable to automated analysis...
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...
Bootstrap-based confidence estimation in PCA and multivariate statistical process control
DEFF Research Database (Denmark)
Babamoradi, Hamid
be used to detect outliers in the data since the outliers can distort the bootstrap estimates. Bootstrap-based confidence limits were suggested as alternative to the asymptotic limits for control charts and contribution plots in MSPC (Paper II). The results showed that in case of the Q-statistic......Traditional/Asymptotic confidence estimation has limited applicability since it needs statistical theories to estimate the confidences, which are not available for all indicators/parameters. Furthermore, in case the theories are available for a specific indicator/parameter, the theories are based....... The goal was to improve process monitoring by improving the quality of MSPC charts and contribution plots. Bootstrapping algorithm to build confidence limits was illustrated in a case study format (Paper I). The main steps in the algorithm were discussed where a set of sensible choices (plus...
Efficient bootstrap with weakly dependent processes
Bravo, Francesco; Crudu, Federico
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
Statistical error estimation of the Feynman-α method using the bootstrap method
International Nuclear Information System (INIS)
Endo, Tomohiro; Yamamoto, Akio; Yagi, Takahiro; Pyeon, Cheol Ho
2016-01-01
Applicability of the bootstrap method is investigated to estimate the statistical error of the Feynman-α method, which is one of the subcritical measurement techniques on the basis of reactor noise analysis. In the Feynman-α method, the statistical error can be simply estimated from multiple measurements of reactor noise, however it requires additional measurement time to repeat the multiple times of measurements. Using a resampling technique called 'bootstrap method' standard deviation and confidence interval of measurement results obtained by the Feynman-α method can be estimated as the statistical error, using only a single measurement of reactor noise. In order to validate our proposed technique, we carried out a passive measurement of reactor noise without any external source, i.e. with only inherent neutron source by spontaneous fission and (α,n) reactions in nuclear fuels at the Kyoto University Criticality Assembly. Through the actual measurement, it is confirmed that the bootstrap method is applicable to approximately estimate the statistical error of measurement results obtained by the Feynman-α method. (author)
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...
A bootstrap based space-time surveillance model with an application to crime occurrences
Kim, Youngho; O'Kelly, Morton
2008-06-01
This study proposes a bootstrap-based space-time surveillance model. Designed to find emerging hotspots in near-real time, the bootstrap based model is characterized by its use of past occurrence information and bootstrap permutations. Many existing space-time surveillance methods, using population at risk data to generate expected values, have resulting hotspots bounded by administrative area units and are of limited use for near-real time applications because of the population data needed. However, this study generates expected values for local hotspots from past occurrences rather than population at risk. Also, bootstrap permutations of previous occurrences are used for significant tests. Consequently, the bootstrap-based model, without the requirement of population at risk data, (1) is free from administrative area restriction, (2) enables more frequent surveillance for continuously updated registry database, and (3) is readily applicable to criminology and epidemiology surveillance. The bootstrap-based model performs better for space-time surveillance than the space-time scan statistic. This is shown by means of simulations and an application to residential crime occurrences in Columbus, OH, year 2000.
Soybean yield modeling using bootstrap methods for small samples
Energy Technology Data Exchange (ETDEWEB)
Dalposso, G.A.; Uribe-Opazo, M.A.; Johann, J.A.
2016-11-01
One of the problems that occur when working with regression models is regarding the sample size; once the statistical methods used in inferential analyzes are asymptotic if the sample is small the analysis may be compromised because the estimates will be biased. An alternative is to use the bootstrap methodology, which in its non-parametric version does not need to guess or know the probability distribution that generated the original sample. In this work we used a set of soybean yield data and physical and chemical soil properties formed with fewer samples to determine a multiple linear regression model. Bootstrap methods were used for variable selection, identification of influential points and for determination of confidence intervals of the model parameters. The results showed that the bootstrap methods enabled us to select the physical and chemical soil properties, which were significant in the construction of the soybean yield regression model, construct the confidence intervals of the parameters and identify the points that had great influence on the estimated parameters. (Author)
Warton, David I; Thibaut, Loïc; Wang, Yi Alice
2017-01-01
Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)-common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of "model-free bootstrap", adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods.
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.
DEFF Research Database (Denmark)
Malzahn, Dorthe; Opper, Manfred
2003-01-01
We employ the replica method of statistical physics to study the average case performance of learning systems. The new feature of our theory is that general distributions of data can be treated, which enables applications to real data. For a class of Bayesian prediction models which are based...... on Gaussian processes, we discuss Bootstrap estimates for learning curves....
Bootstrap consistency for general semiparametric M-estimation
Cheng, Guang; Huang, Jianhua Z.
2010-01-01
, 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.
Directory of Open Access Journals (Sweden)
Elias Chaibub Neto
Full Text Available In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson's sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling.
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.
Karian, Zaven A
2000-01-01
Throughout the physical and social sciences, researchers face the challenge of fitting statistical distributions to their data. Although the study of statistical modelling has made great strides in recent years, the number and variety of distributions to choose from-all with their own formulas, tables, diagrams, and general properties-continue to create problems. For a specific application, which of the dozens of distributions should one use? What if none of them fit well?Fitting Statistical Distributions helps answer those questions. Focusing on techniques used successfully across many fields, the authors present all of the relevant results related to the Generalized Lambda Distribution (GLD), the Generalized Bootstrap (GB), and Monte Carlo simulation (MC). They provide the tables, algorithms, and computer programs needed for fitting continuous probability distributions to data in a wide variety of circumstances-covering bivariate as well as univariate distributions, and including situations where moments do...
Bootstrapping a time series model
International Nuclear Information System (INIS)
Son, M.S.
1984-01-01
The bootstrap is a methodology for estimating standard errors. The idea is to use a Monte Carlo simulation experiment based on a nonparametric estimate of the error distribution. The main objective of this dissertation was to demonstrate the use of the bootstrap to attach standard errors to coefficient estimates and multi-period forecasts in a second-order autoregressive model fitted by least squares and maximum likelihood estimation. A secondary objective of this article was to present the bootstrap in the context of two econometric equations describing the unemployment rate and individual income tax in the state of Oklahoma. As it turns out, the conventional asymptotic formulae (both the least squares and maximum likelihood estimates) for estimating standard errors appear to overestimate the true standard errors. But there are two problems: 1) the first two observations y 1 and y 2 have been fixed, and 2) the residuals have not been inflated. After these two factors are considered in the trial and bootstrap experiment, both the conventional maximum likelihood and bootstrap estimates of the standard errors appear to be performing quite well. At present, there does not seem to be a good rule of thumb for deciding when the conventional asymptotic formulae will give acceptable results
Bootstrap Power of Time Series Goodness of fit tests
Directory of Open Access Journals (Sweden)
Sohail Chand
2013-10-01
Full Text Available In this article, we looked at power of various versions of Box and Pierce statistic and Cramer von Mises test. An extensive simulation study has been conducted to compare the power of these tests. Algorithms have been provided for the power calculations and comparison has also been made between the semi parametric bootstrap methods used for time series. Results show that Box-Pierce statistic and its various versions have good power against linear time series models but poor power against non linear models while situation reverses for Cramer von Mises test. Moreover, we found that dynamic bootstrap method is better than xed design bootstrap method.
Improving Web Learning through model Optimization using Bootstrap for a Tour-Guide Robot
Directory of Open Access Journals (Sweden)
Rafael León
2012-09-01
Full Text Available We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology applied to pattern model classifier optimization and verification for Supervised Learning for Tour-Guide Robot knowledge repository management. It is virtually impossible to test thoroughly Web Page Classifiers and many other Internet Applications with pure empirical data, due to the need for human intervention to generate training sets and test sets. We propose using the computer-based Bootstrap paradigm to design a test environment where they are checked with better reliability
Bootstrapping pronunciation models: a South African case study
CSIR Research Space (South Africa)
Davel, M
2006-02-27
Full Text Available Bootstrapping techniques can accelerate the development of language technology for new languages. The authors define a framework for the analysis of a general bootstrapping process whereby a model is improved through a controlled series...
The use of vector bootstrapping to improve variable selection precision in Lasso models
Laurin, C.; Boomsma, D.I.; Lubke, G.H.
2016-01-01
The Lasso is a shrinkage regression method that is widely used for variable selection in statistical genetics. Commonly, K-fold cross-validation is used to fit a Lasso model. This is sometimes followed by using bootstrap confidence intervals to improve precision in the resulting variable selections.
The nonparametric bootstrap for the current status model
Groeneboom, P.; Hendrickx, K.
2017-01-01
It has been proved that direct bootstrapping of the nonparametric maximum likelihood estimator (MLE) of the distribution function in the current status model leads to inconsistent confidence intervals. We show that bootstrapping of functionals of the MLE can however be used to produce valid
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 correctly sized and...
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 correctly sized and...
Bootstrap Determination of the Co-Integration Rank in Heteroskedastic VAR Models
DEFF Research Database (Denmark)
Cavaliere, G.; Rahbek, Anders; Taylor, A.M.R.
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...
Phu, Jack; Bui, Bang V; Kalloniatis, Michael; Khuu, Sieu K
2018-03-01
The number of subjects needed to establish the normative limits for visual field (VF) testing is not known. Using bootstrap resampling, we determined whether the ground truth mean, distribution limits, and standard deviation (SD) could be approximated using different set size ( x ) levels, in order to provide guidance for the number of healthy subjects required to obtain robust VF normative data. We analyzed the 500 Humphrey Field Analyzer (HFA) SITA-Standard results of 116 healthy subjects and 100 HFA full threshold results of 100 psychophysically experienced healthy subjects. These VFs were resampled (bootstrapped) to determine mean sensitivity, distribution limits (5th and 95th percentiles), and SD for different ' x ' and numbers of resamples. We also used the VF results of 122 glaucoma patients to determine the performance of ground truth and bootstrapped results in identifying and quantifying VF defects. An x of 150 (for SITA-Standard) and 60 (for full threshold) produced bootstrapped descriptive statistics that were no longer different to the original distribution limits and SD. Removing outliers produced similar results. Differences between original and bootstrapped limits in detecting glaucomatous defects were minimized at x = 250. Ground truth statistics of VF sensitivities could be approximated using set sizes that are significantly smaller than the original cohort. Outlier removal facilitates the use of Gaussian statistics and does not significantly affect the distribution limits. We provide guidance for choosing the cohort size for different levels of error when performing normative comparisons with glaucoma patients.
The Local Fractional Bootstrap
DEFF Research Database (Denmark)
Bennedsen, Mikkel; Hounyo, Ulrich; Lunde, Asger
We introduce a bootstrap procedure for high-frequency statistics of Brownian semistationary processes. More specifically, we focus on a hypothesis test on the roughness of sample paths of Brownian semistationary processes, which uses an estimator based on a ratio of realized power variations. Our...... 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...... and in simulations we observe that the bootstrap-based hypothesis test provides considerable finite-sample improvements over an existing test that is based on a central limit theorem. This is important when studying the roughness properties of time series data; we illustrate this by applying the bootstrap method...
Bootstrapping language acquisition.
Abend, Omri; Kwiatkowski, Tom; Smith, Nathaniel J; Goldwater, Sharon; Steedman, Mark
2017-07-01
The semantic bootstrapping hypothesis proposes that children acquire their native language through exposure to sentences of the language paired with structured representations of their meaning, whose component substructures can be associated with words and syntactic structures used to express these concepts. The child's task is then to learn a language-specific grammar and lexicon based on (probably contextually ambiguous, possibly somewhat noisy) pairs of sentences and their meaning representations (logical forms). Starting from these assumptions, we develop a Bayesian probabilistic account of semantically bootstrapped first-language acquisition in the child, based on techniques from computational parsing and interpretation of unrestricted text. Our learner jointly models (a) word learning: the mapping between components of the given sentential meaning and lexical words (or phrases) of the language, and (b) syntax learning: the projection of lexical elements onto sentences by universal construction-free syntactic rules. Using an incremental learning algorithm, we apply the model to a dataset of real syntactically complex child-directed utterances and (pseudo) logical forms, the latter including contextually plausible but irrelevant distractors. Taking the Eve section of the CHILDES corpus as input, the model simulates several well-documented phenomena from the developmental literature. In particular, the model exhibits syntactic bootstrapping effects (in which previously learned constructions facilitate the learning of novel words), sudden jumps in learning without explicit parameter setting, acceleration of word-learning (the "vocabulary spurt"), an initial bias favoring the learning of nouns over verbs, and one-shot learning of words and their meanings. The learner thus demonstrates how statistical learning over structured representations can provide a unified account for these seemingly disparate phenomena. Copyright © 2017 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Castedo Echeverri, Alejandro; Harling, Benedict von; Serone, Marco
2016-06-01
We study the numerical bounds obtained using a conformal-bootstrap method where different points in the plane of conformal cross ratios z and anti z are sampled. In contrast to the most used method based on derivatives evaluated at the symmetric point z= anti 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.
Energy Technology Data Exchange (ETDEWEB)
Castedo Echeverri, Alejandro [SISSA, Trieste (Italy); INFN, Trieste (Italy); Harling, Benedict von [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Serone, Marco [SISSA, Trieste (Italy); INFN, Trieste (Italy); ICTP, Trieste (Italy)
2016-06-15
We study the numerical bounds obtained using a conformal-bootstrap method where different points in the plane of conformal cross ratios z and anti z are sampled. In contrast to the most used method based on derivatives evaluated at the symmetric point z= anti 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.
Monte Carlo based statistical power analysis for mediation models: methods and software.
Zhang, Zhiyong
2014-12-01
The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.
Energy Technology Data Exchange (ETDEWEB)
Cornagliotto, Martina; Lemos, Madalena; Schomerus, Volker [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Theory Group
2017-02-15
Applications of the bootstrap program to superconformal field theories promise unique new insights into their landscape and could even lead to the discovery of new models. Most existing results of the superconformal bootstrap were obtained form correlation functions of very special fields in short (BPS) representations of the superconformal algebra. Our main goal is to initiate a superconformal bootstrap for long multiplets, one that exploits all constraints from superprimaries and their descendants. To this end, we work out the Casimir equations for four-point correlators of long multiplets of the two-dimensional global N=2 superconformal algebra. After constructing the full set of conformal blocks we discuss two different applications. The first one concerns two-dimensional (2,0) theories. The numerical bootstrap analysis we perform serves a twofold purpose, as a feasibility study of our long multiplet bootstrap and also as an exploration of (2,0) theories. A second line of applications is directed towards four-dimensional N=3 SCFTs. In this context, our results imply a new bound c ≥ (13)/(24) for the central charge of such models. A theory that saturates this bound is not known yet.
International Nuclear Information System (INIS)
Cornagliotto, Martina; Lemos, Madalena; Schomerus, Volker
2017-02-01
Applications of the bootstrap program to superconformal field theories promise unique new insights into their landscape and could even lead to the discovery of new models. Most existing results of the superconformal bootstrap were obtained form correlation functions of very special fields in short (BPS) representations of the superconformal algebra. Our main goal is to initiate a superconformal bootstrap for long multiplets, one that exploits all constraints from superprimaries and their descendants. To this end, we work out the Casimir equations for four-point correlators of long multiplets of the two-dimensional global N=2 superconformal algebra. After constructing the full set of conformal blocks we discuss two different applications. The first one concerns two-dimensional (2,0) theories. The numerical bootstrap analysis we perform serves a twofold purpose, as a feasibility study of our long multiplet bootstrap and also as an exploration of (2,0) theories. A second line of applications is directed towards four-dimensional N=3 SCFTs. In this context, our results imply a new bound c ≥ (13)/(24) for the central charge of such models. A theory that saturates this bound is not known yet.
Cornagliotto, Martina; Lemos, Madalena; Schomerus, Volker
2017-10-01
Applications of the bootstrap program to superconformal field theories promise unique new insights into their landscape and could even lead to the discovery of new models. Most existing results of the superconformal bootstrap were obtained form correlation functions of very special fields in short (BPS) representations of the superconformal algebra. Our main goal is to initiate a superconformal bootstrap for long multiplets, one that exploits all constraints from superprimaries and their descendants. To this end, we work out the Casimir equations for four-point correlators of long multiplets of the two-dimensional global N=2 superconformal algebra. After constructing the full set of conformal blocks we discuss two different applications. The first one concerns two-dimensional (2,0) theories. The numerical bootstrap analysis we perform serves a twofold purpose, as a feasibility study of our long multiplet bootstrap and also as an exploration of (2,0) theories. A second line of applications is directed towards four-dimensional N=3 SCFTs. In this context, our results imply a new bound c≥ 13/24 for the central charge of such models, which we argue cannot be saturated by an interacting SCFT.
Internal validation of risk models in clustered data: a comparison of bootstrap schemes
Bouwmeester, W.; Moons, K.G.M.; Kappen, T.H.; van Klei, W.A.; Twisk, J.W.R.; Eijkemans, M.J.C.; Vergouwe, Y.
2013-01-01
Internal validity of a risk model can be studied efficiently with bootstrapping to assess possible optimism in model performance. Assumptions of the regular bootstrap are violated when the development data are clustered. We compared alternative resampling schemes in clustered data for the estimation
Buonaccorsi, John P; Romeo, Giovanni; Thoresen, Magne
2018-03-01
When fitting regression models, measurement error in any of the predictors typically leads to biased coefficients and incorrect inferences. A plethora of methods have been proposed to correct for this. Obtaining standard errors and confidence intervals using the corrected estimators can be challenging and, in addition, there is concern about remaining bias in the corrected estimators. The bootstrap, which is one option to address these problems, has received limited attention in this context. It has usually been employed by simply resampling observations, which, while suitable in some situations, is not always formally justified. In addition, the simple bootstrap does not allow for estimating bias in non-linear models, including logistic regression. Model-based bootstrapping, which can potentially estimate bias in addition to being robust to the original sampling or whether the measurement error variance is constant or not, has received limited attention. However, it faces challenges that are not present in handling regression models with no measurement error. This article develops new methods for model-based bootstrapping when correcting for measurement error in logistic regression with replicate measures. The methodology is illustrated using two examples, and a series of simulations are carried out to assess and compare the simple and model-based bootstrap methods, as well as other standard methods. While not always perfect, the model-based approaches offer some distinct improvements over the other methods. © 2017, The International Biometric Society.
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...
Energy Technology Data Exchange (ETDEWEB)
Wedenberg, Minna, E-mail: minna.wedenberg@raysearchlabs.com
2013-11-15
Purpose: To apply a statistical bootstrap analysis to assess the uncertainty in the dose–response relation for the endpoints pneumonitis and myelopathy reported in the QUANTEC review. Methods and Materials: The bootstrap method assesses the uncertainty of the estimated population-based dose-response relation due to sample variability, which reflects the uncertainty due to limited numbers of patients in the studies. A large number of bootstrap replicates of the original incidence data were produced by random sampling with replacement. The analysis requires only the dose, the number of patients, and the number of occurrences of the studied endpoint, for each study. Two dose–response models, a Poisson-based model and the Lyman model, were fitted to each bootstrap replicate using maximum likelihood. Results: The bootstrap analysis generates a family of curves representing the range of plausible dose–response relations, and the 95% bootstrap confidence intervals give an estimated upper and lower toxicity risk. The curve families for the 2 dose–response models overlap for doses included in the studies at hand but diverge beyond that, with the Lyman model suggesting a steeper slope. The resulting distributions of the model parameters indicate correlation and non-Gaussian distribution. For both data sets, the likelihood of the observed data was higher for the Lyman model in >90% of the bootstrap replicates. Conclusions: The bootstrap method provides a statistical analysis of the uncertainty in the estimated dose–response relation for myelopathy and pneumonitis. It suggests likely values of model parameter values, their confidence intervals, and how they interrelate for each model. Finally, it can be used to evaluate to what extent data supports one model over another. For both data sets considered here, the Lyman model was preferred over the Poisson-based model.
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.
Directory of Open Access Journals (Sweden)
Enrico Zio
2008-01-01
Full Text Available In the present work, the uncertainties affecting the safety margins estimated from thermal-hydraulic code calculations are captured quantitatively by resorting to the order statistics and the bootstrap technique. The proposed framework of analysis is applied to the estimation of the safety margin, with its confidence interval, of the maximum fuel cladding temperature reached during a complete group distribution blockage scenario in a RBMK-1500 nuclear reactor.
Finite-Size Effects for Some Bootstrap Percolation Models
Enter, A.C.D. van; Adler, Joan; Duarte, J.A.M.S.
The consequences of Schonmann's new proof that the critical threshold is unity for certain bootstrap percolation models are explored. It is shown that this proof provides an upper bound for the finite-size scaling in these systems. Comparison with data for one case demonstrates that this scaling
Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations
Directory of Open Access Journals (Sweden)
Roberto S. Flowers-Cano
2018-02-01
Full Text Available Design of hydraulic works requires the estimation of design hydrological events by statistical inference from a probability distribution. Using Monte Carlo simulations, we compared coverage of confidence intervals constructed with four bootstrap techniques: percentile bootstrap (BP, bias-corrected bootstrap (BC, accelerated bias-corrected bootstrap (BCA and a modified version of the standard bootstrap (MSB. Different simulation scenarios were analyzed. In some cases, the mother distribution function was fit to the random samples that were generated. In other cases, a distribution function different to the mother distribution was fit to the samples. When the fitted distribution had three parameters, and was the same as the mother distribution, the intervals constructed with the four techniques had acceptable coverage. However, the bootstrap techniques failed in several of the cases in which the fitted distribution had two parameters.
The bootstrap and Bayesian bootstrap method in assessing bioequivalence
International Nuclear Information System (INIS)
Wan Jianping; Zhang Kongsheng; Chen Hui
2009-01-01
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.
Using the bootstrap in a multivariadte data problem: An example
International Nuclear Information System (INIS)
Glosup, J.G.; Axelrod, M.C.
1995-01-01
The use of the bootstrap in the multivariate version of the paired t-test is considered and demonstrated through an example. The problem of interest involves comparing two different techniques for measuring the chemical constituents of an sample item. The bootstrap is used to form an empirical significance level for Hotelling's one-sample T-squared statistic. The bootstrap was selected to determine empirical significance levels because the implicit assumption of multivariate normality in the classic Hotelling's one-sample test night not hold. The results of both the classic and bootstrap test are presented and contrasted
CSIR Research Space (South Africa)
Ntaka, L
2013-08-01
Full Text Available . In this work, statistical inference approach specifically the non-parametric bootstrapping and linear model were applied. Data used to develop the model were sourced from the literature. 104 data points with information on aggregation, natural organic matter...
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.
Online Statistical Modeling (Regression Analysis) for Independent Responses
Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus
2017-06-01
Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.
Liu, Chunbo; Pan, Feng; Li, Yun
2016-07-29
Glutamate is of great importance in food and pharmaceutical industries. There is still lack of effective statistical approaches for fault diagnosis in the fermentation process of glutamate. To date, the statistical approach based on generalized additive model (GAM) and bootstrap has not been used for fault diagnosis in fermentation processes, much less the fermentation process of glutamate with small samples sets. A combined approach of GAM and bootstrap was developed for the online fault diagnosis in the fermentation process of glutamate with small sample sets. GAM was first used to model the relationship between glutamate production and different fermentation parameters using online data from four normal fermentation experiments of glutamate. The fitted GAM with fermentation time, dissolved oxygen, oxygen uptake rate and carbon dioxide evolution rate captured 99.6 % variance of glutamate production during fermentation process. Bootstrap was then used to quantify the uncertainty of the estimated production of glutamate from the fitted GAM using 95 % confidence interval. The proposed approach was then used for the online fault diagnosis in the abnormal fermentation processes of glutamate, and a fault was defined as the estimated production of glutamate fell outside the 95 % confidence interval. The online fault diagnosis based on the proposed approach identified not only the start of the fault in the fermentation process, but also the end of the fault when the fermentation conditions were back to normal. The proposed approach only used a small sample sets from normal fermentations excitements to establish the approach, and then only required online recorded data on fermentation parameters for fault diagnosis in the fermentation process of glutamate. The proposed approach based on GAM and bootstrap provides a new and effective way for the fault diagnosis in the fermentation process of glutamate with small sample sets.
Bootstrapping in a language of thought: a formal model of numerical concept learning.
Piantadosi, Steven T; Tenenbaum, Joshua B; Goodman, Noah D
2012-05-01
In acquiring number words, children exhibit a qualitative leap in which they transition from understanding a few number words, to possessing a rich system of interrelated numerical concepts. We present a computational framework for understanding this inductive leap as the consequence of statistical inference over a sufficiently powerful representational system. We provide an implemented model that is powerful enough to learn number word meanings and other related conceptual systems from naturalistic data. The model shows that bootstrapping can be made computationally and philosophically well-founded as a theory of number learning. Our approach demonstrates how learners may combine core cognitive operations to build sophisticated representations during the course of development, and how this process explains observed developmental patterns in number word learning. Copyright Â© 2011 Elsevier B.V. All rights reserved.
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.
Workshop on Model Uncertainty and its Statistical Implications
1988-01-01
In this book problems related to the choice of models in such diverse fields as regression, covariance structure, time series analysis and multinomial experiments are discussed. The emphasis is on the statistical implications for model assessment when the assessment is done with the same data that generated the model. This is a problem of long standing, notorious for its difficulty. Some contributors discuss this problem in an illuminating way. Others, and this is a truly novel feature, investigate systematically whether sample re-use methods like the bootstrap can be used to assess the quality of estimators or predictors in a reliable way given the initial model uncertainty. The book should prove to be valuable for advanced practitioners and statistical methodologists alike.
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.
Models for probability and statistical inference theory and applications
Stapleton, James H
2007-01-01
This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses mo...
A Parsimonious Bootstrap Method to Model Natural Inflow Energy Series
Directory of Open Access Journals (Sweden)
Fernando Luiz Cyrino Oliveira
2014-01-01
Full Text Available The Brazilian energy generation and transmission system is quite peculiar in its dimension and characteristics. As such, it can be considered unique in the world. It is a high dimension hydrothermal system with huge participation of hydro plants. Such strong dependency on hydrological regimes implies uncertainties related to the energetic planning, requiring adequate modeling of the hydrological time series. This is carried out via stochastic simulations of monthly inflow series using the family of Periodic Autoregressive models, PAR(p, one for each period (month of the year. In this paper it is shown the problems in fitting these models by the current system, particularly the identification of the autoregressive order “p” and the corresponding parameter estimation. It is followed by a proposal of a new approach to set both the model order and the parameters estimation of the PAR(p models, using a nonparametric computational technique, known as Bootstrap. This technique allows the estimation of reliable confidence intervals for the model parameters. The obtained results using the Parsimonious Bootstrap Method of Moments (PBMOM produced not only more parsimonious model orders but also adherent stochastic scenarios and, in the long range, lead to a better use of water resources in the energy operation planning.
Bootstrap procedure in the quasinuclear quark model
International Nuclear Information System (INIS)
Anisovich, V.V.; Gerasyuta, S.M.; Keltuyala, I.V.
1983-01-01
The scattering amplitude for quarks (dressed quarks of a single flavour, and three colours) is obtained by means of a bootstrap procedure with introdUction of an initial paint-wise interaction due to a heavy gluon exchange. The obtained quasi-nuclear model (effective short-range interaction in the S-wave states) has reasonable properties: there exist colourless meson states Jsup(p)=0sup(-), 1 - ; there are no bound states in coloured channels, a virtual diquark level Jsup(p)=1sup(+) appears in the coloured state anti 3sub(c)
Roberts, Steven; Martin, Michael A
2010-01-01
Concerns have been raised about findings of associations between particulate matter (PM) air pollution and mortality that have been based on a single "best" model arising from a model selection procedure, because such a strategy may ignore model uncertainty inherently involved in searching through a set of candidate models to find the best model. Model averaging has been proposed as a method of allowing for model uncertainty in this context. To propose an extension (double BOOT) to a previously described bootstrap model-averaging procedure (BOOT) for use in time series studies of the association between PM and mortality. We compared double BOOT and BOOT with Bayesian model averaging (BMA) and a standard method of model selection [standard Akaike's information criterion (AIC)]. Actual time series data from the United States are used to conduct a simulation study to compare and contrast the performance of double BOOT, BOOT, BMA, and standard AIC. Double BOOT produced estimates of the effect of PM on mortality that have had smaller root mean squared error than did those produced by BOOT, BMA, and standard AIC. This performance boost resulted from estimates produced by double BOOT having smaller variance than those produced by BOOT and BMA. Double BOOT is a viable alternative to BOOT and BMA for producing estimates of the mortality effect of PM.
Interaction of bootstrap-current-driven magnetic islands
International Nuclear Information System (INIS)
Hegna, C.C.; Callen, J.D.
1991-10-01
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
The economics of bootstrapping space industries - Development of an analytic computer model
Goldberg, A. H.; Criswell, D. R.
1982-01-01
A simple economic model of 'bootstrapping' industrial growth in space and on the Moon is presented. An initial space manufacturing facility (SMF) is assumed to consume lunar materials to enlarge the productive capacity in space. After reaching a predetermined throughput, the enlarged SMF is devoted to products which generate revenue continuously in proportion to the accumulated output mass (such as space solar power stations). Present discounted value and physical estimates for the general factors of production (transport, capital efficiency, labor, etc.) are combined to explore optimum growth in terms of maximized discounted revenues. It is found that 'bootstrapping' reduces the fractional cost to a space industry of transport off-Earth, permits more efficient use of a given transport fleet. It is concluded that more attention should be given to structuring 'bootstrapping' scenarios in which 'learning while doing' can be more fully incorporated in program analysis.
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...
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.
DEFF Research Database (Denmark)
Cavaliere, Giuseppe; Nielsen, Morten Ørregaard; Taylor, A.M. Robert
Empirical evidence from time series methods which assume the usual I(0)/I(1) paradigm suggests that the efficient market hypothesis, stating that spot and futures prices of a commodity should cointegrate with a unit slope on futures prices, does not hold. However, these statistical methods...... fractionally integrated model we are able to find a body of evidence in support of the efficient market hypothesis for a number of commodities. Our new tests are wild bootstrap implementations of score-based tests for the order of integration of a fractionally integrated time series. These tests are designed...... principle do. A Monte Carlo simulation study demonstrates that very significant improvements infinite sample behaviour can be obtained by the bootstrap vis-à-vis the corresponding asymptotic tests in both heteroskedastic and homoskedastic environments....
Bootstrap Sequential Determination of the Co-integration Rank in VAR Models
DEFF Research Database (Denmark)
Guiseppe, Cavaliere; Rahbæk, Anders; Taylor, A.M. Robert
with 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...... 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....
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.
White, H; Racine, J
2001-01-01
We propose tests for individual and joint irrelevance of network inputs. Such tests can be used to determine whether an input or group of inputs "belong" in a particular model, thus permitting valid statistical inference based on estimated feedforward neural-network models. The approaches employ well-known statistical resampling techniques. We conduct a small Monte Carlo experiment showing that our tests have reasonable level and power behavior, and we apply our methods to examine whether there are predictable regularities in foreign exchange rates. We find that exchange rates do appear to contain information that is exploitable for enhanced point prediction, but the nature of the predictive relations evolves through time.
Accidental symmetries and the conformal bootstrap
Energy Technology Data Exchange (ETDEWEB)
Chester, Shai M.; Giombi, Simone; Iliesiu, Luca V.; Klebanov, Igor R.; Pufu, Silviu S.; Yacoby, Ran [Joseph Henry Laboratories, Princeton University,Princeton, NJ 08544 (United States)
2016-01-19
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{sub 1}X∑{sub i}Z{sub i}{sup 2}+g{sub 2}X{sup 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{sub 2} flowing to zero. This example is special in that the existence of an infrared fixed point with g{sub 1},g{sub 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{sub 1},g{sub 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{sub 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{sub 1},g{sub 2}≠0 models by studying them perturbatively in the 4−ϵ expansion.
Energy Technology Data Exchange (ETDEWEB)
Andrade, Maria Celia Ramos; Ludwig, Gerson Otto [Instituto Nacional de Pesquisas Espaciais (INPE), Sao Jose dos Campos, SP (Brazil). Lab. Associado de Plasma]. E-mail: mcr@plasma.inpe.br
2004-07-01
Different bootstrap current formulations are implemented in a self-consistent equilibrium calculation obtained from a direct variational technique in fixed boundary tokamak plasmas. The total plasma current profile is supposed to have contributions of the diamagnetic, Pfirsch-Schlueter, and the neoclassical Ohmic and bootstrap currents. The Ohmic component is calculated in terms of the neoclassical conductivity, compared here among different expressions, and the loop voltage determined consistently in order to give the prescribed value of the total plasma current. A comparison among several bootstrap current models for different viscosity coefficient calculations and distinct forms for the Coulomb collision operator is performed for a variety of plasma parameters of the small aspect ratio tokamak ETE (Experimento Tokamak Esferico) at the Associated Plasma Laboratory of INPE, in Brazil. We have performed this comparison for the ETE tokamak so that the differences among all the models reported here, mainly regarding plasma collisionality, can be better illustrated. The dependence of the bootstrap current ratio upon some plasma parameters in the frame of the self-consistent calculation is also analysed. We emphasize in this paper what we call the Hirshman-Sigmar/Shaing model, valid for all collisionality regimes and aspect ratios, and a fitted formulation proposed by Sauter, which has the same range of validity but is faster to compute than the previous one. The advantages or possible limitations of all these different formulations for the bootstrap current estimate are analysed throughout this work. (author)
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 series first, the applying the standard wild bootstrap for independent and heteroscedastic distrbuted observations to overlapping tapered blocks in an appropriate way. Its perserves the favorable bias and mean squared error properties of the tapered block bootstrap, which is the state-of-the-art block......-order asymptotic validity of the tapered block bootstrap as well as the wild tapered block bootstrap approximation to the actual distribution of the sample mean is also established when data are assumed to satisfy a near epoch dependent condition. The consistency of the bootstrap variance estimator for the sample...
EBW-Bootstrap Current Synergy in the National Spherical Torus Experiment (NSTX)
International Nuclear Information System (INIS)
Harvey, R.W.; Taylor, G.
2005-01-01
Current driven by electron Bernstein waves (EBW) and by the electron bootstrap effect are calculated separately and concurrently with a kinetic code, to determine the degree of synergy between them. A target β = 40% NSTX plasma is examined. A simple bootstrap model in the CQL3D Fokker-Planck code is used in these studies: the transiting electron distributions are connected in velocity-space at the trapped-passing boundary to trapped-electron distributions which are displaced radially by a half-banana width outwards/inwards for the co-/counter-passing regions. This model agrees well with standard bootstrap current calculations, over the outer 60% of the plasma radius. Relatively small synergy net bootstrap current is obtained for EBW power up to 4 MW. Locally, bootstrap current density increases in proportion to increased plasma pressure, and this effect can significantly affect the radial profile of driven current
Bootstrapped efficiency measures of oil blocks in Angola
International Nuclear Information System (INIS)
Barros, C.P.; Assaf, A.
2009-01-01
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.
A NONPARAMETRIC HYPOTHESIS TEST VIA THE BOOTSTRAP RESAMPLING
Temel, Tugrul T.
2001-01-01
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.
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
Bootstrapping phylogenies inferred from rearrangement data.
Lin, Yu; Rajan, Vaibhav; Moret, Bernard Me
2012-08-29
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. 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. Our method is the first to provide a standard of assessment to match that of the classic phylogenetic bootstrap for aligned sequences. Its support values follow a similar scale and its receiver
DEFF Research Database (Denmark)
Linnet, Kristian
2005-01-01
Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors......Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors...
Babamoradi, Hamid; van den Berg, Frans; Rinnan, Åsmund
2016-02-18
In Multivariate Statistical Process Control, when a fault is expected or detected in the process, contribution plots are essential for operators and optimization engineers in identifying those process variables that were affected by or might be the cause of the fault. The traditional way of interpreting a contribution plot is to examine the largest contributing process variables as the most probable faulty ones. This might result in false readings purely due to the differences in natural variation, measurement uncertainties, etc. It is more reasonable to compare variable contributions for new process runs with historical results achieved under Normal Operating Conditions, where confidence limits for contribution plots estimated from training data are used to judge new production runs. Asymptotic methods cannot provide confidence limits for contribution plots, leaving re-sampling methods as the only option. We suggest bootstrap re-sampling to build confidence limits for all contribution plots in online PCA-based MSPC. The new strategy to estimate CLs is compared to the previously reported CLs for contribution plots. An industrial batch process dataset was used to illustrate the concepts. Copyright © 2016 Elsevier B.V. All rights reserved.
Uncertainty Assessment of Hydrological Frequency Analysis Using Bootstrap Method
Directory of Open Access Journals (Sweden)
Yi-Ming Hu
2013-01-01
Full Text Available The hydrological frequency analysis (HFA is the foundation for the hydraulic engineering design and water resources management. Hydrological extreme observations or samples are the basis for HFA; the representativeness of a sample series to the population distribution is extremely important for the estimation reliability of the hydrological design value or quantile. However, for most of hydrological extreme data obtained in practical application, the size of the samples is usually small, for example, in China about 40~50 years. Generally, samples with small size cannot completely display the statistical properties of the population distribution, thus leading to uncertainties in the estimation of hydrological design values. In this paper, a new method based on bootstrap is put forward to analyze the impact of sampling uncertainty on the design value. By bootstrap resampling technique, a large number of bootstrap samples are constructed from the original flood extreme observations; the corresponding design value or quantile is estimated for each bootstrap sample, so that the sampling distribution of design value is constructed; based on the sampling distribution, the uncertainty of quantile estimation can be quantified. Compared with the conventional approach, this method provides not only the point estimation of a design value but also quantitative evaluation on uncertainties of the estimation.
Bootstrap currents in stellarators and tokamaks
International Nuclear Information System (INIS)
Okamoto, Masao; Nakajima, Noriyoshi.
1990-09-01
The remarkable feature of the bootstrap current in stellarators is it's strong dependence on the magnetic field configuration. Neoclassical bootstrap currents in a large helical device of torsatron/heliotron type (L = 2, M = 10, R = 4 m, B = 4 T) is evaluated in the banana (1/ν) and the plateau regime. Various vacuum magnetic field configurations are studied with a view to minimizing the bootstrap current. It is found that in the banana regime, shifting of the magnetic axis and shaping of magnetic surfaces have a remarkable influence on the bootstrap current; a small outward shift of the magnetic axis and vertically elongated magnetic surfaces are favourable for a reduction of the bootstrap current. It is noted, however, that the ripple diffusion in the 1/ν regime has opposite tendency to the bootstrap current; it increases with the outward shift and increases as the plasma cross section is vertically elongated. The comparison will be made between bootstrap currents in stellarators and tokamaks. (author)
Inference for Local Distributions at High Sampling Frequencies: A Bootstrap Approach
DEFF Research Database (Denmark)
Hounyo, Ulrich; Varneskov, Rasmus T.
of "large" jumps. Our locally dependent wild bootstrap (LDWB) accommodate issues related to the stochastic scale and jumps as well as account for a special block-wise dependence structure induced by sampling errors. We show that the LDWB replicates first and second-order limit theory from the usual...... empirical process and the stochastic scale estimate, respectively, as well as an asymptotic bias. Moreover, we design the LDWB sufficiently general to establish asymptotic equivalence between it and and a nonparametric local block bootstrap, also introduced here, up to second-order distribution theory....... Finally, we introduce LDWB-aided Kolmogorov-Smirnov tests for local Gaussianity as well as local von-Mises statistics, with and without bootstrap inference, and establish their asymptotic validity using the second-order distribution theory. The finite sample performance of CLT and LDWB-aided local...
DEFF Research Database (Denmark)
Hounyo, Ulrich
to a gneral class of estimators of integrated covolatility. We then show the first-order asymptotic validity of this method in the multivariate context with a potential presence of jumps, dependent microsturcture noise, irregularly spaced and non-synchronous data. Due to our focus on non...... covariance estimator. As an application of our results, we also consider the bootstrap for regression coefficients. We show that the wild blocks of bootstrap, appropriately centered, is able to mimic both the dependence and heterogeneity of the scores, thus justifying the construction of bootstrap percentile...... intervals as well as variance estimates in this context. This contrasts with the traditional pairs bootstrap which is not able to mimic the score heterogeneity even in the simple case where no microsturcture noise is present. Our Monte Carlo simulations show that the wild blocks of blocks bootstrap improves...
Abrupt change in mean using block bootstrap and avoiding variance estimation
Czech Academy of Sciences Publication Activity Database
Peštová, Barbora; Pešta, M.
2018-01-01
Roč. 33, č. 1 (2018), s. 413-441 ISSN 0943-4062 Grant - others:GA ČR(CZ) GJ15-04774Y Institutional support: RVO:67985807 Keywords : Block bootstrap * Change in mean * Change point * Hypothesis test ing * Ratio type statistics * Robustness Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.434, year: 2016
GSD: An SPSS extension command for sub-sampling and bootstrapping datasets
Directory of Open Access Journals (Sweden)
Harding, Bradley
2016-09-01
Full Text Available Statistical analyses have grown immensely since the inception of computational methods. However, many quantitative methods classes teach sampling and sub-sampling at a very abstract level despite the fact that, with the faster computers of today, these notions could be demonstrated live to the students. For this reason, we have created a simple extension module for SPSS that can sub-sample and Bootstrap data, GSD (Generator of Sub-sampled Data. In this paper, we describe and show how to use the GSD module as well as provide short descriptions of both the sub-sampling and Bootstrap methods. In addition, as this article aims to inspire instructors to introduce these concepts in their statistics classes of all levels, we provide three short exercises that are ready for curriculum implementation.
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
Quantifying uncertainty on sediment loads using bootstrap confidence intervals
Slaets, Johanna I. F.; Piepho, Hans-Peter; Schmitter, Petra; Hilger, Thomas; Cadisch, Georg
2017-01-01
Load estimates are more informative than constituent concentrations alone, as they allow quantification of on- and off-site impacts of environmental processes concerning pollutants, nutrients and sediment, such as soil fertility loss, reservoir sedimentation and irrigation channel siltation. While statistical models used to predict constituent concentrations have been developed considerably over the last few years, measures of uncertainty on constituent loads are rarely reported. Loads are the product of two predictions, constituent concentration and discharge, integrated over a time period, which does not make it straightforward to produce a standard error or a confidence interval. In this paper, a linear mixed model is used to estimate sediment concentrations. A bootstrap method is then developed that accounts for the uncertainty in the concentration and discharge predictions, allowing temporal correlation in the constituent data, and can be used when data transformations are required. The method was tested for a small watershed in Northwest Vietnam for the period 2010-2011. The results showed that confidence intervals were asymmetric, with the highest uncertainty in the upper limit, and that a load of 6262 Mg year-1 had a 95 % confidence interval of (4331, 12 267) in 2010 and a load of 5543 Mg an interval of (3593, 8975) in 2011. Additionally, the approach demonstrated that direct estimates from the data were biased downwards compared to bootstrap median estimates. These results imply that constituent loads predicted from regression-type water quality models could frequently be underestimating sediment yields and their environmental impact.
Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns
DEFF Research Database (Denmark)
Gonçalves, Sílvia; Hounyo, Ulrich; Meddahi, Nour
The main contribution of this paper is to propose bootstrap methods for realized volatility-like estimators defined on pre-averaged returns. In particular, we focus on the pre-averaged realized volatility estimator proposed by Podolskij and Vetter (2009). This statistic can be written (up to a bias......-overlapping nature of the pre-averaged returns implies that these are asymptotically independent, but possibly heteroskedastic. This motivates the application of the wild bootstrap in this context. We provide a proof of the first order asymptotic validity of this method for percentile and percentile-t intervals. Our...... Monte Carlo simulations show that the wild bootstrap can improve the finite sample properties of the existing first order asymptotic theory provided we choose the external random variable appropriately. We use empirical work to illustrate its use in practice....
Optical Flow of Small Objects Using Wavelets, Bootstrap Methods, and Synthetic Discriminant Filters
National Research Council Canada - National Science Library
Hewer, Gary
1997-01-01
...) targets in highly cluttered and noisy environments. In this paper; we present a novel wavelet detection algorithm which incorporates adaptive CFAR detection statistics using the bootstrap method...
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.
Energy confinement of tokamak plasma with consideration of bootstrap current effect
International Nuclear Information System (INIS)
Yuan Ying; Gao Qingdi
1992-01-01
Based on the η i -mode induced anomalous transport model of Lee et al., the energy confinement of tokamak plasmas with auxiliary heating is investigated with consideration of bootstrap current effect. The results indicate that energy confinement time increases with plasma current and tokamak major radius, and decreases with heating power, toroidal field and minor radius. This is in reasonable agreement with the Kaye-Goldston empirical scaling law. Bootstrap current always leads to an improvement of energy confinement and the contraction of inversion radius. When γ, the ratio between bootstrap current and total plasma current, is small, the part of energy confinement time contributed from bootstrap current will be about γ/2
Bias Correction with Jackknife, Bootstrap, and Taylor Series
Jiao, Jiantao; Han, Yanjun; Weissman, Tsachy
2017-01-01
We analyze the bias correction methods using jackknife, bootstrap, and Taylor series. We focus on the binomial model, and consider the problem of bias correction for estimating $f(p)$, where $f \\in C[0,1]$ is arbitrary. We characterize the supremum norm of the bias of general jackknife and bootstrap estimators for any continuous functions, and demonstrate the in delete-$d$ jackknife, different values of $d$ may lead to drastically different behavior in jackknife. We show that in the binomial ...
Point Set Denoising Using Bootstrap-Based Radial Basis Function.
Liew, Khang Jie; 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.
More on analytic bootstrap for O(N) models
Energy Technology Data Exchange (ETDEWEB)
Dey, Parijat; Kaviraj, Apratim; Sen, Kallol [Centre for High Energy Physics, Indian Institute of Science,C.V. Raman Avenue, Bangalore 560012 (India)
2016-06-22
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{sub μν}) and the ϕ{sub i}ϕ{sup i} scalar, we also have other minimal twist operators as the spin-1 current J{sub μ} and the symmetric-traceless scalar in the case of O(N). We determine the effect of these additional objects on the anomalous dimensions of the corresponding trace, symmetric-traceless and antisymmetric operators in the large spin sector of the O(N) model, in the limit when the spin is much larger than the twist. As an observation, we also verified that the leading order results for the large spin sector from the ϵ−expansion are an exact match with our n=0 case. A plausible holographic setup for the special case when N=2 is also mentioned which mimics the calculation in the CFT.
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
Time evolution of the bootstrap current profile in LHD plasmas
International Nuclear Information System (INIS)
Nakamura, Yuji; Kawaoto, K.; Watanabe, K.Y.
2008-10-01
The direction of the bootstrap current is inverted in the outward shifted plasmas of the Large Helical Device (LHD). In order to verify the reliability of the theoretical models of the bootstrap current in helical plasmas, the rotational transform profiles are observed by the Motional Stark Effect measurement in the bootstrap current carrying plasmas of the LHD, and they are compared with the numerical simulations of the toroidal current profile including the bootstrap current. Since the toroidal current profile is not in the steady state in these plasmas, taking care of the inversely induced component of the toroidal current and finite duration of the resistive diffusion of the toroidal current are important in the numerical simulations. Reasonable agreement can be obtained between the rotational transform profiles measured in the experiments and those calculated in the numerical simulations. (author)
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.
Point Set Denoising Using Bootstrap-Based Radial Basis Function.
Directory of Open Access Journals (Sweden)
Khang Jie Liew
Full Text Available 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.
Forecasting Model for IPTV Service in Korea Using Bootstrap Ridge Regression Analysis
Lee, Byoung Chul; Kee, Seho; Kim, Jae Bum; Kim, Yun Bae
The telecom firms in Korea are taking new step to prepare for the next generation of convergence services, IPTV. In this paper we described our analysis on the effective method for demand forecasting about IPTV broadcasting. We have tried according to 3 types of scenarios based on some aspects of IPTV potential market and made a comparison among the results. The forecasting method used in this paper is the multi generation substitution model with bootstrap ridge regression analysis.
Bootstrapping Relational Affordances of Object Pairs using Transfer
DEFF Research Database (Denmark)
Fichtl, Severin; Kraft, Dirk; Krüger, Norbert
2018-01-01
leverage past knowledge to accelerate current learning (which we call bootstrapping). We learn Random Forest based affordance predictors from visual inputs and demonstrate two approaches to knowledge transfer for bootstrapping. In the first approach (direct bootstrapping), the state-space for a new...... affordance predictor is augmented with the output of previously learnt affordances. In the second approach (category based bootstrapping), we form categories that capture underlying commonalities of a pair of existing affordances and augment the state-space with this category classifier’s output. In addition......, we introduce a novel heuristic, which suggests how a large set of potential affordance categories can be pruned to leave only those categories which are most promising for bootstrapping future affordances. Our results show that both bootstrapping approaches outperform learning without bootstrapping...
A bootstrapping method for development of Treebank
Zarei, F.; Basirat, A.; Faili, H.; Mirain, M.
2017-01-01
Using statistical approaches beside the traditional methods of natural language processing could significantly improve both the quality and performance of several natural language processing (NLP) tasks. The effective usage of these approaches is subject to the availability of the informative, accurate and detailed corpora on which the learners are trained. This article introduces a bootstrapping method for developing annotated corpora based on a complex and rich linguistically motivated elementary structure called supertag. To this end, a hybrid method for supertagging is proposed that combines both of the generative and discriminative methods of supertagging. The method was applied on a subset of Wall Street Journal (WSJ) in order to annotate its sentences with a set of linguistically motivated elementary structures of the English XTAG grammar that is using a lexicalised tree-adjoining grammar formalism. The empirical results confirm that the bootstrapping method provides a satisfactory way for annotating the English sentences with the mentioned structures. The experiments show that the method could automatically annotate about 20% of WSJ with the accuracy of F-measure about 80% of which is particularly 12% higher than the F-measure of the XTAG Treebank automatically generated from the approach proposed by Basirat and Faili [(2013). Bridge the gap between statistical and hand-crafted grammars. Computer Speech and Language, 27, 1085-1104].
Ultrafast Approximation for Phylogenetic Bootstrap
Bui Quang Minh, [No Value; Nguyen, Thi; von Haeseler, Arndt
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
Electron Bernstein wave-bootstrap current synergy in the National Spherical Torus Experiment
International Nuclear Information System (INIS)
Harvey, R.W.; Taylor, G.
2005-01-01
Current driven by electron Bernstein waves (EBW) and by the electron bootstrap effect are calculated separately and concurrently with a kinetic code to determine the degree of synergy between them. A target β=40% NSTX [M. Ono, S. Kaye, M. Peng et al., Proceedings of the 17th IAEA Fusion Energy Conference, edited by M. Spak (IAEA, Vienna, Austria, 1999), Vol. 3, p. 1135] plasma is examined. A simple bootstrap model in the collisional-quasilinear CQL3D Fokker-Planck code (National Technical Information Service document No. DE93002962) is used in these studies: the transiting electron distributions are connected in velocity space at the trapped-passing boundary to trapped-electron distributions that are displaced radially by a half-banana-width outwards/inwards for the co-passing/counter-passing regions. This model agrees well with standard bootstrap current calculations over the outer 60% of the plasma radius. Relatively small synergy net bootstrap current is obtained for EBW power up to 4 MW. Locally, bootstrap current density increases in proportion to increased plasma pressure, and this effect can significantly affect the radial profile of driven current
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.…
Stock Price Simulation Using Bootstrap and Monte Carlo
Directory of Open Access Journals (Sweden)
Pažický Martin
2017-06-01
Full Text Available In this paper, an attempt is made to assessment and comparison of bootstrap experiment and Monte Carlo experiment for stock price simulation. Since the stock price evolution in the future is extremely important for the investors, there is the attempt to find the best method how to determine the future stock price of BNP Paribas′ bank. The aim of the paper is define the value of the European and Asian option on BNP Paribas′ stock at the maturity date. There are employed four different methods for the simulation. First method is bootstrap experiment with homoscedastic error term, second method is blocked bootstrap experiment with heteroscedastic error term, third method is Monte Carlo simulation with heteroscedastic error term and the last method is Monte Carlo simulation with homoscedastic error term. In the last method there is necessary to model the volatility using econometric GARCH model. The main purpose of the paper is to compare the mentioned methods and select the most reliable. The difference between classical European option and exotic Asian option based on the experiment results is the next aim of tis paper.
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.
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.
Directory of Open Access Journals (Sweden)
Campbell Michael J
2004-12-01
Full Text Available Abstract Health-Related Quality of Life (HRQoL measures are becoming increasingly used in clinical trials as primary outcome measures. Investigators are now asking statisticians for advice on how to analyse studies that have used HRQoL outcomes. HRQoL outcomes, like the SF-36, are usually measured on an ordinal scale. However, most investigators assume that there exists an underlying continuous latent variable that measures HRQoL, and that the actual measured outcomes (the ordered categories, reflect contiguous intervals along this continuum. The ordinal scaling of HRQoL measures means they tend to generate data that have discrete, bounded and skewed distributions. Thus, standard methods of analysis such as the t-test and linear regression that assume Normality and constant variance may not be appropriate. For this reason, conventional statistical advice would suggest that non-parametric methods be used to analyse HRQoL data. The bootstrap is one such computer intensive non-parametric method for analysing data. We used the bootstrap for hypothesis testing and the estimation of standard errors and confidence intervals for parameters, in four datasets (which illustrate the different aspects of study design. We then compared and contrasted the bootstrap with standard methods of analysing HRQoL outcomes. The standard methods included t-tests, linear regression, summary measures and General Linear Models. Overall, in the datasets we studied, using the SF-36 outcome, bootstrap methods produce results similar to conventional statistical methods. This is likely because the t-test and linear regression are robust to the violations of assumptions that HRQoL data are likely to cause (i.e. non-Normality. While particular to our datasets, these findings are likely to generalise to other HRQoL outcomes, which have discrete, bounded and skewed distributions. Future research with other HRQoL outcome measures, interventions and populations, is required to
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.
Energy Technology Data Exchange (ETDEWEB)
Niehof, Jonathan T.; Morley, Steven K.
2012-01-01
We review and develop techniques to determine associations between series of discrete events. The bootstrap, a nonparametric statistical method, allows the determination of the significance of associations with minimal assumptions about the underlying processes. We find the key requirement for this method: one of the series must be widely spaced in time to guarantee the theoretical applicability of the bootstrap. If this condition is met, the calculated significance passes a reasonableness test. We conclude with some potential future extensions and caveats on the applicability of these methods. The techniques presented have been implemented in a Python-based software toolkit.
Darling, Stephen; Parker, Mary-Jane; Goodall, Karen E; Havelka, Jelena; Allen, Richard J
2014-03-01
When participants carry out visually presented digit serial recall, their performance is better if they are given the opportunity to encode extra visuospatial information at encoding-a phenomenon that has been termed visuospatial bootstrapping. This bootstrapping is the result of integration of information from different modality-specific short-term memory systems and visuospatial knowledge in long term memory, and it can be understood in the context of recent models of working memory that address multimodal binding (e.g., models incorporating an episodic buffer). Here we report a cross-sectional developmental study that demonstrated visuospatial bootstrapping in adults (n=18) and 9-year-old children (n=15) but not in 6-year-old children (n=18). This is the first developmental study addressing visuospatial bootstrapping, and results demonstrate that the developmental trajectory of bootstrapping is different from that of basic verbal and visuospatial working memory. This pattern suggests that bootstrapping (and hence integrative functions such as those associated with the episodic buffer) emerge independent of the development of basic working memory slave systems during childhood. Copyright © 2013 Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Rejon-Barrera, Fernando [Institute for Theoretical Physics, University of Amsterdam,Science Park 904, Postbus 94485, 1090 GL, Amsterdam (Netherlands); Robbins, Daniel [Department of Physics, Texas A& M University,TAMU 4242, College Station, TX 77843 (United States)
2016-01-22
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.
Directory of Open Access Journals (Sweden)
Engin YILDIZTEPE
2015-05-01
Full Text Available Bootstrap methodology is a modern statistical tool which enables us makin g statistical inference when the sampling distribution of the estimator is not known. Although the underlying idea is the same in all bootstrap methods, one might come across so many variations in tthe literature. In this study, the coverage accuracy of four most commonly used bootstrap confidence interval methods was assessed for various asymmetr c and heavy tailed distributions with an exh austive Monte Carlo simulation. In most of the cases, it has been found that the coverage accuracy of bootstrap percentile method is close to nominal for robust estimators of location.
Finite-size effects for anisotropic bootstrap percolation : Logarithmic corrections
van Enter, Aernout C. D.; Hulshof, Tim
In this note we analyse an anisotropic, two-dimensional bootstrap percolation model introduced by Gravner and Griffeath. We present upper and lower bounds on the finite-size effects. We discuss the similarities with the semi-oriented model introduced by Duarte.
Finite-size effects for anisotropic bootstrap percolation: logerithmic corrections
Enter, van A.C.D.; Hulshof, T.
2007-01-01
In this note we analyse an anisotropic, two-dimensional bootstrap percolation model introduced by Gravner and Griffeath. We present upper and lower bounds on the finite-size effects. We discuss the similarities with the semi-oriented model introduced by Duarte.
Uncertainty Estimation using Bootstrapped Kriging Predictions for Precipitation Isoscapes
Ma, C.; Bowen, G. J.; Vander Zanden, H.; Wunder, M.
2017-12-01
Isoscapes are spatial models representing the distribution of stable isotope values across landscapes. Isoscapes of hydrogen and oxygen in precipitation are now widely used in a diversity of fields, including geology, biology, hydrology, and atmospheric science. To generate isoscapes, geostatistical methods are typically applied to extend predictions from limited data measurements. Kriging is a popular method in isoscape modeling, but quantifying the uncertainty associated with the resulting isoscapes is challenging. Applications that use precipitation isoscapes to determine sample origin require estimation of uncertainty. Here we present a simple bootstrap method (SBM) to estimate the mean and uncertainty of the krigged isoscape and compare these results with a generalized bootstrap method (GBM) applied in previous studies. We used hydrogen isotopic data from IsoMAP to explore these two approaches for estimating uncertainty. We conducted 10 simulations for each bootstrap method and found that SBM results in more kriging predictions (9/10) compared to GBM (4/10). Prediction from SBM was closer to the original prediction generated without bootstrapping and had less variance than GBM. SBM was tested on different datasets from IsoMAP with different numbers of observation sites. We determined that predictions from the datasets with fewer than 40 observation sites using SBM were more variable than the original prediction. The approaches we used for estimating uncertainty will be compiled in an R package that is under development. We expect that these robust estimates of precipitation isoscape uncertainty can be applied in diagnosing the origin of samples ranging from various type of waters to migratory animals, food products, and humans.
The Bootstrap Current and Neutral Beam Current Drive in DIII-D
International Nuclear Information System (INIS)
Politzer, P.A.
2005-01-01
Noninductive current drive is an essential part of the implementation of the DIII-D Advanced Tokamak program. For an efficient steady-state tokamak reactor, the plasma must provide close to 100% bootstrap fraction (f bs ). For noninductive operation of DIII-D, current drive by injection of energetic neutral beams [neutral beam current drive (NBCD)] is also important. DIII-D experiments have reached ∼80% bootstrap current in stationary discharges without inductive current drive. The remaining current is ∼20% NBCD. This is achieved at β N [approximately equal to] β p > 3, but at relatively high q 95 (∼10). In lower q 95 Advanced Tokamak plasmas, f bs ∼ 0.6 has been reached in essentially noninductive plasmas. The phenomenology of high β p and β N plasmas without current control is being studied. These plasmas display a relaxation oscillation involving repetitive formation and collapse of an internal transport barrier. The frequency and severity of these events increase with increasing β, limiting the achievable average β and causing modulation of the total current as well as the pressure. Modeling of both bootstrap and NBCD currents is based on neoclassical theory. Measurements of the total bootstrap and NBCD current agree with calculations. A recent experiment based on the evolution of the transient voltage profile after an L-H transition shows that the more recent bootstrap current models accurately describe the plasma behavior. The profiles and the parametric dependences of the local neutral beam-driven current density have not yet been compared with theory
Nonparametric bootstrap procedures for predictive inference based on recursive estimation schemes
Corradi, Valentina; Swanson, Norman R.
2005-01-01
Our objectives in this paper are twofold. First, we introduce block bootstrap techniques that are (first order) valid in recursive estimation frameworks. Thereafter, we present two examples where predictive accuracy tests are made operational using our new bootstrap procedures. In one application, we outline a consistent test for out-of-sample nonlinear Granger causality, and in the other we outline a test for selecting amongst multiple alternative forecasting models, all of which are possibl...
Mirror bootstrap method for testing hypotheses of one mean
Varvak, Anna
2012-01-01
The general philosophy for bootstrap or permutation methods for testing hypotheses is to simulate the variation of the test statistic by generating the sampling distribution which assumes both that the null hypothesis is true, and that the data in the sample is somehow representative of the population. This philosophy is inapplicable for testing hypotheses for a single parameter like the population mean, since the two assumptions are contradictory (e.g., how can we assume both that the mean o...
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.
Integrable deformations of conformal theories and bootstrap trees
International Nuclear Information System (INIS)
Mussardo, G.
1991-01-01
I present recent results in the study of massive integrable quantum field theories in (1+1) dimensions considered as perturbed conformal minimal models. The on mass-shell properties of such theories, with a particular emphasis on the bootstrap principle, are investigated. (orig.)
Metastability Thresholds for Anisotropic Bootstrap Percolation in Three Dimensions
Enter, Aernout C.D. van; Fey, Anne
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
Selfconsistent RF driven and bootstrap currents
International Nuclear Information System (INIS)
Peysson, Y.
2002-01-01
This important problem selfconsistent calculations of the bootstrap current with RF, taking into account possible synergistic effects, is addressed for the case of lower hybrid (LH) and electron cyclotron (EC) current drive by numerically solving the electron drift kinetic equation. Calculations are performed using a new, fast, and fully implicit code which solves the 3-D relativistic Fokker-Planck equation with quasilinear diffusion. These calculations take into account the perturbations to the electron distribution due to radial drifts induced by magnetic field gradient and curvature. While the synergism between bootstrap and LH-driven current does not seem to exceed 15%, it can reach 30-40% with the EC-driven current for some plasma parameters. In addition, considerable current can be generated by judiciously using ECCD with the Okhawa effect. This is in contrast to the usual ECCD which tries to avoid it. A detailed analysis of the numerical results is presented using a simplified analytical model which incorporates the underlying physical processes. (author)
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...... (1989). In many cases validity of bootstrap-based inference procedures is found to depend crucially on whether the bandwidth sequence satisfies a particular (asymptotic linearity) condition. An exception to this rule occurs for inference procedures involving a studentized estimator employing a "robust...
Hunink, Maria; Bult, J.R.; De Vries, J; Weinstein, MC
1998-01-01
Purpose. To illustrate the use of a nonparametric bootstrap method in the evaluation of uncertainty in decision models analyzing cost-effectiveness. Methods. The authors reevaluated a previously published cost-effectiveness analysis that used a Markov model comparing initial percutaneous
Bootstrapping non-commutative gauge theories from L∞ algebras
Blumenhagen, Ralph; Brunner, Ilka; Kupriyanov, Vladislav; Lüst, Dieter
2018-05-01
Non-commutative gauge theories with a non-constant NC-parameter are investigated. As a novel approach, we propose that such theories should admit an underlying L∞ algebra, that governs not only the action of the symmetries but also the dynamics of the theory. Our approach is well motivated from string theory. We recall that such field theories arise in the context of branes in WZW models and briefly comment on its appearance for integrable deformations of AdS5 sigma models. For the SU(2) WZW model, we show that the earlier proposed matrix valued gauge theory on the fuzzy 2-sphere can be bootstrapped via an L∞ algebra. We then apply this approach to the construction of non-commutative Chern-Simons and Yang-Mills theories on flat and curved backgrounds with non-constant NC-structure. More concretely, up to the second order, we demonstrate how derivative and curvature corrections to the equations of motion can be bootstrapped in an algebraic way from the L∞ algebra. The appearance of a non-trivial A∞ algebra is discussed, as well.
Quadratic mass relations in topological bootstrap theory
International Nuclear Information System (INIS)
Jones, C.E.; Uschersohn, J.
1980-01-01
From the requirement of reality of discontinuities of scattering amplitudes at the spherical level of the topological bootstrap theory, a large number of mass relations for hadrons is derived. Quadratic mass formulas for the symmetry-breaking pattern of both mesons and baryon is obtained and their relation to conventional models of symmetry breaking is briefly discussed
Statistical mechanics of black holes
International Nuclear Information System (INIS)
Harms, B.; Leblanc, Y.
1992-01-01
We analyze the statistical mechanics of a gas of neutral and charged black holes. The microcanonical ensemble is the only possible approach to this system, and the equilibrium configuration is the one for which most of the energy is carried by a single black hole. Schwarzschild black holes are found to obey the statistical bootstrap condition. In all cases, the microcanonical temperature is identical to the Hawking temperature of the most massive black hole in the gas. U(1) charges in general break the bootstrap property. The problems of black-hole decay and of quantum coherence are also addressed
Larwin, Karen H.; Larwin, David A.
2011-01-01
Bootstrapping methods and random distribution methods are increasingly recommended as better approaches for teaching students about statistical inference in introductory-level statistics courses. The authors examined the effect of teaching undergraduate business statistics students using random distribution and bootstrapping simulations. It is the…
Bootstrap-Based Inference for Cube Root Consistent Estimators
DEFF Research Database (Denmark)
Cattaneo, Matias D.; Jansson, Michael; Nagasawa, Kenichi
This note proposes a consistent bootstrap-based distributional approximation for cube root consistent estimators such as the maximum score estimator of Manski (1975) and the isotonic density estimator of Grenander (1956). In both cases, the standard nonparametric bootstrap is known...... to be inconsistent. Our method restores consistency of the nonparametric bootstrap by altering the shape of the criterion function defining the estimator whose distribution we seek to approximate. This modification leads to a generic and easy-to-implement resampling method for inference that is conceptually distinct...... from other available distributional approximations based on some form of modified bootstrap. We offer simulation evidence showcasing the performance of our inference method in finite samples. An extension of our methodology to general M-estimation problems is also discussed....
Validation of neoclassical bootstrap current models in the edge of an H-mode plasma.
Wade, M R; Murakami, M; Politzer, P A
2004-06-11
Analysis of the parallel electric field E(parallel) evolution following an L-H transition in the DIII-D tokamak indicates the generation of a large negative pulse near the edge which propagates inward, indicative of the generation of a noninductive edge current. Modeling indicates that the observed E(parallel) evolution is consistent with a narrow current density peak generated in the plasma edge. Very good quantitative agreement is found between the measured E(parallel) evolution and that expected from neoclassical theory predictions of the bootstrap current.
Gray bootstrap method for estimating frequency-varying random vibration signals with small samples
Directory of Open Access Journals (Sweden)
Wang Yanqing
2014-04-01
Full Text Available During environment testing, the estimation of random vibration signals (RVS is an important technique for the airborne platform safety and reliability. However, the available methods including extreme value envelope method (EVEM, statistical tolerances method (STM and improved statistical tolerance method (ISTM require large samples and typical probability distribution. Moreover, the frequency-varying characteristic of RVS is usually not taken into account. Gray bootstrap method (GBM is proposed to solve the problem of estimating frequency-varying RVS with small samples. Firstly, the estimated indexes are obtained including the estimated interval, the estimated uncertainty, the estimated value, the estimated error and estimated reliability. In addition, GBM is applied to estimating the single flight testing of certain aircraft. At last, in order to evaluate the estimated performance, GBM is compared with bootstrap method (BM and gray method (GM in testing analysis. The result shows that GBM has superiority for estimating dynamic signals with small samples and estimated reliability is proved to be 100% at the given confidence level.
Directory of Open Access Journals (Sweden)
Hojin Moon
2006-08-01
Full Text Available A computational tool for testing for a dose-related trend and/or a pairwise difference in the incidence of an occult tumor via an age-adjusted bootstrap-based poly-k test and the original poly-k test is presented in this paper. The poly-k test (Bailer and Portier 1988 is a survival-adjusted Cochran-Armitage test, which achieves robustness to effects of differential mortality across dose groups. The original poly-k test is asymptotically standard normal under the null hypothesis. However, the asymptotic normality is not valid if there is a deviation from the tumor onset distribution that is assumed in this test. Our age-adjusted bootstrap-based poly-k test assesses the significance of assumed asymptotic normal tests and investigates an empirical distribution of the original poly-k test statistic using an age-adjusted bootstrap method. A tumor of interest is an occult tumor for which the time to onset is not directly observable. Since most of the animal carcinogenicity studies are designed with a single terminal sacrifice, the present tool is applicable to rodent tumorigenicity assays that have a single terminal sacrifice. The present tool takes input information simply from a user screen and reports testing results back to the screen through a user-interface. The computational tool is implemented in C/C++ and is applied to analyze a real data set as an example. Our tool enables the FDA and the pharmaceutical industry to implement a statistical analysis of tumorigenicity data from animal bioassays via our age-adjusted bootstrap-based poly-k test and the original poly-k test which has been adopted by the National Toxicology Program as its standard statistical test.
International Nuclear Information System (INIS)
Iwi, G.; Millard, R.K.; Palmer, A.M.; Preece, A.W.; Saunders, M.
1999-01-01
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 99m Tc-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 99m Tc-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 99m Tc-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)
Transport barriers in bootstrap-driven tokamaks
Staebler, G. M.; Garofalo, A. M.; Pan, C.; McClenaghan, J.; Van Zeeland, M. A.; Lao, L. L.
2018-05-01
Experiments have demonstrated improved energy confinement due to the spontaneous formation of an internal transport barrier in high bootstrap fraction discharges. Gyrokinetic analysis, and quasilinear predictive modeling, demonstrates that the observed transport barrier is caused by the suppression of turbulence primarily from the large Shafranov shift. It is shown that the Shafranov shift can produce a bifurcation to improved confinement in regions of positive magnetic shear or a continuous reduction in transport for weak or negative magnetic shear. Operation at high safety factor lowers the pressure gradient threshold for the Shafranov shift-driven barrier formation. Two self-organized states of the internal and edge transport barrier are observed. It is shown that these two states are controlled by the interaction of the bootstrap current with magnetic shear, and the kinetic ballooning mode instability boundary. Election scale energy transport is predicted to be dominant in the inner 60% of the profile. Evidence is presented that energetic particle-driven instabilities could be playing a role in the thermal energy transport in this region.
2009-01-01
Background The International Commission on Radiological Protection (ICRP) recommended annual occupational dose limit is 20 mSv. Cancer mortality in Japanese A-bomb survivors exposed to less than 20 mSv external radiation in 1945 was analysed previously, using a latency model with non-linear dose response. Questions were raised regarding statistical inference with this model. Methods Cancers with over 100 deaths in the 0 - 20 mSv subcohort of the 1950-1990 Life Span Study are analysed with Poisson regression models incorporating latency, allowing linear and non-linear dose response. Bootstrap percentile and Bias-corrected accelerated (BCa) methods and simulation of the Likelihood Ratio Test lead to Confidence Intervals for Excess Relative Risk (ERR) and tests against the linear model. Results The linear model shows significant large, positive values of ERR for liver and urinary cancers at latencies from 37 - 43 years. Dose response below 20 mSv is strongly non-linear at the optimal latencies for the stomach (11.89 years), liver (36.9), lung (13.6), leukaemia (23.66), and pancreas (11.86) and across broad latency ranges. Confidence Intervals for ERR are comparable using Bootstrap and Likelihood Ratio Test methods and BCa 95% Confidence Intervals are strictly positive across latency ranges for all 5 cancers. Similar risk estimates for 10 mSv (lagged dose) are obtained from the 0 - 20 mSv and 5 - 500 mSv data for the stomach, liver, lung and leukaemia. Dose response for the latter 3 cancers is significantly non-linear in the 5 - 500 mSv range. Conclusion Liver and urinary cancer mortality risk is significantly raised using a latency model with linear dose response. A non-linear model is strongly superior for the stomach, liver, lung, pancreas and leukaemia. Bootstrap and Likelihood-based confidence intervals are broadly comparable and ERR is strictly positive by bootstrap methods for all 5 cancers. Except for the pancreas, similar estimates of latency and risk from 10
Developments in statistical analysis in quantitative genetics
DEFF Research Database (Denmark)
Sorensen, Daniel
2009-01-01
of genetic means and variances, models for the analysis of categorical and count data, the statistical genetics of a model postulating that environmental variance is partly under genetic control, and a short discussion of models that incorporate massive genetic marker information. We provide an overview......A remarkable research impetus has taken place in statistical genetics since the last World Conference. This has been stimulated by breakthroughs in molecular genetics, automated data-recording devices and computer-intensive statistical methods. The latter were revolutionized by the bootstrap...... and by Markov chain Monte Carlo (McMC). In this overview a number of specific areas are chosen to illustrate the enormous flexibility that McMC has provided for fitting models and exploring features of data that were previously inaccessible. The selected areas are inferences of the trajectories over time...
The cluster bootstrap consistency in generalized estimating equations
Cheng, Guang; Yu, Zhuqing; Huang, Jianhua Z.
2013-01-01
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
Energy Technology Data Exchange (ETDEWEB)
Iliesiu, Luca [Joseph Henry Laboratories, Princeton University, Princeton, NJ 08544 (United States); Kos, Filip; Poland, David [Department of Physics, Yale University, New Haven, CT 06520 (United States); Pufu, Silviu S. [Joseph Henry Laboratories, Princeton University, Princeton, NJ 08544 (United States); Simmons-Duffin, David [School of Natural Sciences, Institute for Advanced Study, Princeton, NJ 08540 (United States); Yacoby, Ran [Joseph Henry Laboratories, Princeton University, Princeton, NJ 08544 (United States)
2016-03-17
We study the conformal bootstrap for a 4-point function of fermions 〈ψψψψ〉 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{sub T}. We observe features in our bounds that coincide with scaling dimensions in the Gross-Neveu models at large N. We also speculate that other features could coincide with a fermionic CFT containing no relevant scalar operators.
Transport Barriers in Bootstrap Driven Tokamaks
Staebler, Gary
2017-10-01
Maximizing the bootstrap current in a tokamak, so that it drives a high fraction of the total current, reduces the external power required to drive current by other means. Improved energy confinement, relative to empirical scaling laws, enables a reactor to more fully take advantage of the bootstrap driven tokamak. Experiments have demonstrated improved energy confinement due to the spontaneous formation of an internal transport barrier in high bootstrap fraction discharges. Gyrokinetic analysis, and quasilinear predictive modeling, demonstrates that the observed transport barrier is due to the suppression of turbulence primarily due to the large Shafranov shift. ExB velocity shear does not play a significant role in the transport barrier due to the high safety factor. It will be shown, that the Shafranov shift can produce a bifurcation to improved confinement in regions of positive magnetic shear or a continuous reduction in transport for weak or negative magnetic shear. Operation at high safety factor lowers the pressure gradient threshold for the Shafranov shift driven barrier formation. The ion energy transport is reduced to neoclassical and electron energy and particle transport is reduced, but still turbulent, within the barrier. Deeper into the plasma, very large levels of electron transport are observed. The observed electron temperature profile is shown to be close to the threshold for the electron temperature gradient (ETG) mode. A large ETG driven energy transport is qualitatively consistent with recent multi-scale gyrokinetic simulations showing that reducing the ion scale turbulence can lead to large increase in the electron scale transport. A new saturation model for the quasilinear TGLF transport code, that fits these multi-scale gyrokinetic simulations, can match the data if the impact of zonal flow mixing on the ETG modes is reduced at high safety factor. This work was supported by the U.S. Department of Energy under DE-FG02-95ER54309 and DE-FC02
Sediment Curve Uncertainty Estimation Using GLUE and Bootstrap Methods
Directory of Open Access Journals (Sweden)
aboalhasan fathabadi
2017-02-01
Full Text Available Introduction: In order to implement watershed practices to decrease soil erosion effects it needs to estimate output sediment of watershed. Sediment rating curve is used as the most conventional tool to estimate sediment. Regarding to sampling errors and short data, there are some uncertainties in estimating sediment using sediment curve. In this research, bootstrap and the Generalized Likelihood Uncertainty Estimation (GLUE resampling techniques were used to calculate suspended sediment loads by using sediment rating curves. Materials and Methods: The total drainage area of the Sefidrood watershed is about 560000 km2. In this study uncertainty in suspended sediment rating curves was estimated in four stations including Motorkhane, Miyane Tonel Shomare 7, Stor and Glinak constructed on Ayghdamosh, Ghrangho, GHezelOzan and Shahrod rivers, respectively. Data were randomly divided into a training data set (80 percent and a test set (20 percent by Latin hypercube random sampling.Different suspended sediment rating curves equations were fitted to log-transformed values of sediment concentration and discharge and the best fit models were selected based on the lowest root mean square error (RMSE and the highest correlation of coefficient (R2. In the GLUE methodology, different parameter sets were sampled randomly from priori probability distribution. For each station using sampled parameter sets and selected suspended sediment rating curves equation suspended sediment concentration values were estimated several times (100000 to 400000 times. With respect to likelihood function and certain subjective threshold, parameter sets were divided into behavioral and non-behavioral parameter sets. Finally using behavioral parameter sets the 95% confidence intervals for suspended sediment concentration due to parameter uncertainty were estimated. In bootstrap methodology observed suspended sediment and discharge vectors were resampled with replacement B (set to
International Nuclear Information System (INIS)
Zhang, Jinzhao; Segurado, Jacobo; Schneidesch, Christophe
2013-01-01
Since 1980's, Tractebel Engineering (TE) has being developed and applied a multi-physical modelling and safety analyses capability, based on a code package consisting of the best estimate 3D neutronic (PANTHER), system thermal hydraulic (RELAP5), core sub-channel thermal hydraulic (COBRA-3C), and fuel thermal mechanic (FRAPCON/FRAPTRAN) codes. A series of methodologies have been developed to perform and to license the reactor safety analysis and core reload design, based on the deterministic bounding approach. Following the recent trends in research and development as well as in industrial applications, TE has been working since 2010 towards the application of the statistical sensitivity and uncertainty analysis methods to the multi-physical modelling and licensing safety analyses. In this paper, the TE multi-physical modelling and safety analyses capability is first described, followed by the proposed TE best estimate plus statistical uncertainty analysis method (BESUAM). The chosen statistical sensitivity and uncertainty analysis methods (non-parametric order statistic method or bootstrap) and tool (DAKOTA) are then presented, followed by some preliminary results of their applications to FRAPCON/FRAPTRAN simulation of OECD RIA fuel rod codes benchmark and RELAP5/MOD3.3 simulation of THTF tests. (authors)
Wu, M. Q.; Pan, C. K.; Chan, V. S.; Li, G. Q.; Garofalo, A. M.; Jian, X.; Liu, L.; Ren, Q. L.; Chen, J. L.; Gao, X.; Gong, X. Z.; Ding, S. Y.; Qian, J. P.; Cfetr Physics Team
2018-04-01
Time-dependent integrated modeling of DIII-D ITER-like and high bootstrap current plasma ramp-up discharges has been performed with the equilibrium code EFIT, and the transport codes TGYRO and ONETWO. Electron and ion temperature profiles are simulated by TGYRO with the TGLF (SAT0 or VX model) turbulent and NEO neoclassical transport models. The VX model is a new empirical extension of the TGLF turbulent model [Jian et al., Nucl. Fusion 58, 016011 (2018)], which captures the physics of multi-scale interaction between low-k and high-k turbulence from nonlinear gyro-kinetic simulation. This model is demonstrated to accurately model low Ip discharges from the EAST tokamak. Time evolution of the plasma current density profile is simulated by ONETWO with the experimental current ramp-up rate. The general trend of the predicted evolution of the current density profile is consistent with that obtained from the equilibrium reconstruction with Motional Stark effect constraints. The predicted evolution of βN , li , and βP also agrees well with the experiments. For the ITER-like cases, the predicted electron and ion temperature profiles using TGLF_Sat0 agree closely with the experimental measured profiles, and are demonstrably better than other proposed transport models. For the high bootstrap current case, the predicted electron and ion temperature profiles perform better in the VX model. It is found that the SAT0 model works well at high IP (>0.76 MA) while the VX model covers a wider range of plasma current ( IP > 0.6 MA). The results reported in this paper suggest that the developed integrated modeling could be a candidate for ITER and CFETR ramp-up engineering design modeling.
Closure of the operator product expansion in the non-unitary bootstrap
Energy Technology Data Exchange (ETDEWEB)
Esterlis, Ilya [Stanford Institute for Theoretical Physics, Stanford University,Via Pueblo, Stanford, CA 94305 (United States); Fitzpatrick, A. Liam [Department of Physics, Boston University,Commonwealth Ave, Boston, MA, 02215 (United States); Ramirez, David M. [Stanford Institute for Theoretical Physics, Stanford University,Via Pueblo, Stanford, CA 94305 (United States)
2016-11-07
We use the numerical conformal bootstrap in two dimensions to search for finite, closed sub-algebras of the operator product expansion (OPE), without assuming unitarity. We find the minimal models as special cases, as well as additional lines of solutions that can be understood in the Coulomb gas formalism. All the solutions we find that contain the vacuum in the operator algebra are cases where the external operators of the bootstrap equation are degenerate operators, and we argue that this follows analytically from the expressions in http://arxiv.org/abs/1202.4698 for the crossing matrices of Virasoro conformal blocks. Our numerical analysis is a special case of the “Gliozzi” bootstrap method, and provides a simpler setting in which to study technical challenges with the method. In the supplementary material, we provide a Mathematica notebook that automates the calculation of the crossing matrices and OPE coefficients for degenerate operators using the formulae of Dotsenko and Fateev.
A Bootstrapping Model of Frequency and Context Effects in Word Learning.
Kachergis, George; Yu, Chen; Shiffrin, Richard M
2017-04-01
Prior research has shown that people can learn many nouns (i.e., word-object mappings) from a short series of ambiguous situations containing multiple words and objects. For successful cross-situational learning, people must approximately track which words and referents co-occur most frequently. This study investigates the effects of allowing some word-referent pairs to appear more frequently than others, as is true in real-world learning environments. Surprisingly, high-frequency pairs are not always learned better, but can also boost learning of other pairs. Using a recent associative model (Kachergis, Yu, & Shiffrin, 2012), we explain how mixing pairs of different frequencies can bootstrap late learning of the low-frequency pairs based on early learning of higher frequency pairs. We also manipulate contextual diversity, the number of pairs a given pair appears with across training, since it is naturalistically confounded with frequency. The associative model has competing familiarity and uncertainty biases, and their interaction is able to capture the individual and combined effects of frequency and contextual diversity on human learning. Two other recent word-learning models do not account for the behavioral findings. Copyright © 2016 Cognitive Science Society, Inc.
MPBoot: fast phylogenetic maximum parsimony tree inference and bootstrap approximation.
Hoang, Diep Thi; Vinh, Le Sy; Flouri, Tomáš; Stamatakis, Alexandros; von Haeseler, Arndt; Minh, Bui Quang
2018-02-02
The nonparametric bootstrap is widely used to measure the branch support of phylogenetic trees. However, bootstrapping is computationally expensive and remains a bottleneck in phylogenetic analyses. Recently, an ultrafast bootstrap approximation (UFBoot) approach was proposed for maximum likelihood analyses. However, such an approach is still missing for maximum parsimony. To close this gap we present MPBoot, an adaptation and extension of UFBoot to compute branch supports under the maximum parsimony principle. MPBoot works for both uniform and non-uniform cost matrices. Our analyses on biological DNA and protein showed that under uniform cost matrices, MPBoot runs on average 4.7 (DNA) to 7 times (protein data) (range: 1.2-20.7) faster than the standard parsimony bootstrap implemented in PAUP*; but 1.6 (DNA) to 4.1 times (protein data) slower than the standard bootstrap with a fast search routine in TNT (fast-TNT). However, for non-uniform cost matrices MPBoot is 5 (DNA) to 13 times (protein data) (range:0.3-63.9) faster than fast-TNT. We note that MPBoot achieves better scores more frequently than PAUP* and fast-TNT. However, this effect is less pronounced if an intensive but slower search in TNT is invoked. Moreover, experiments on large-scale simulated data show that while both PAUP* and TNT bootstrap estimates are too conservative, MPBoot bootstrap estimates appear more unbiased. MPBoot provides an efficient alternative to the standard maximum parsimony bootstrap procedure. It shows favorable performance in terms of run time, the capability of finding a maximum parsimony tree, and high bootstrap accuracy on simulated as well as empirical data sets. MPBoot is easy-to-use, open-source and available at http://www.cibiv.at/software/mpboot .
A Simple Counterexample to the Bootstrap
Donald W.K. Andrews
1997-01-01
The bootstrap of the maximum likelihood estimator of the mean of a sample of iid normal random variables with mean mu and variance one is not asymptotically correct to first order when the mean is restricted to be nonnegative. The problem occurs when the true value of the mean mu equals zero. This counterexample to the bootstrap generalizes to a wide variety of estimation problems in which the true parameter may be on the boundary of the parameter space. We provide some alternatives to the bo...
International Nuclear Information System (INIS)
Chiu, C.B.; Hossain, M.; Tow, D.M.
1977-07-01
To investigate the t-dependent solutions of simple dual bootstrap models, two general formulations are discussed, one without and one with cut cancellation at the planar level. The possible corresponding production mechanisms are discussed. In contrast to Bishari's formulation, both models recover the Lee-Veneziano relation, i.e., in the peak approximation the Pomeron intercept is unity. The solutions based on an exponential form for the reduced triple-Reggeon vertex for both models are discussed in detail. Also calculated are the cut discontinuities for both models and for Bishari's and it is shown that at both the planar and cylinder levels they are small compared with the corresponding pole residues. Precocious asymptotic planarity is also found in the solutions
Truncatable bootstrap equations in algebraic form and critical surface exponents
Energy Technology Data Exchange (ETDEWEB)
Gliozzi, Ferdinando [Dipartimento di Fisica, Università di Torino andIstituto Nazionale di Fisica Nucleare - sezione di Torino,Via P. Giuria 1, Torino, I-10125 (Italy)
2016-10-10
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 two different solutions of the same polynomial equation. Their interplay yields an estimate of the surface renormalization group exponents, y{sub h}=0.72558(18) for the ordinary universality class and y{sub h}=1.646(2) for the special universality class, which compare well with the most recent Monte Carlo calculations. Estimates of other surface exponents as well as OPE coefficients are also obtained.
Bootstrap percolation: a renormalisation group approach
International Nuclear Information System (INIS)
Branco, N.S.; Santos, Raimundo R. dos; Queiroz, S.L.A. de.
1984-02-01
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) [pt
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.
Bootstrapping N=2 chiral correlators
Energy Technology Data Exchange (ETDEWEB)
Lemos, Madalena [DESY Hamburg, Theory Group,Notkestrasse 85, D-22607 Hamburg (Germany); Liendo, Pedro [IMIP, Humboldt-Universität zu Berlin, IRIS Adlershof,Zum Großen Windkanal 6, 12489 Berlin (Germany)
2016-01-07
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.
Y-90 PET imaging for radiation theragnosis using bootstrap event re sampling
International Nuclear Information System (INIS)
Nam, Taewon; Woo, Sangkeun; Min, Gyungju; Kim, Jimin; Kang, Joohyun; Lim, Sangmoo; Kim, Kyeongmin
2013-01-01
Surgical resection is the most effective method to recover the liver function. However, Yttrium-90 (Y-90) has been used as a new treatment due to the fact that it can be delivered to the tumors and results in greater radiation exposure to the tumors than using external radiation nowadays since most treatment is palliative in case of unresectable stage of hepatocellular carcinoma (HCC). Recently, Y-90 has been received much interest and studied by many researchers. Imaging of Y-90 has been conducted using most commonly gamma camera but PET imaging is required due to low sensitivity and resolution. The purpose of this study was to assess statistical characteristics and to improve count rate of image for enhancing image quality by using nonparametric bootstrap method. PET data was able to be improved using non-parametric bootstrap method and it was verified with showing improved uniformity and SNR. Uniformity showed more improvement under the condition of low count rate, i.e. Y-90, in case of phantom and also uniformity and SNR showed improvement of 15.6% and 33.8% in case of mouse, respectively. Bootstrap method performed in this study for PET data increased count rate of PET image and consequentially time for acquisition time can be reduced. It will be expected to improve performance for diagnosis
Directory of Open Access Journals (Sweden)
Dropkin Greg
2009-12-01
Full Text Available Abstract Background The International Commission on Radiological Protection (ICRP recommended annual occupational dose limit is 20 mSv. Cancer mortality in Japanese A-bomb survivors exposed to less than 20 mSv external radiation in 1945 was analysed previously, using a latency model with non-linear dose response. Questions were raised regarding statistical inference with this model. Methods Cancers with over 100 deaths in the 0 - 20 mSv subcohort of the 1950-1990 Life Span Study are analysed with Poisson regression models incorporating latency, allowing linear and non-linear dose response. Bootstrap percentile and Bias-corrected accelerated (BCa methods and simulation of the Likelihood Ratio Test lead to Confidence Intervals for Excess Relative Risk (ERR and tests against the linear model. Results The linear model shows significant large, positive values of ERR for liver and urinary cancers at latencies from 37 - 43 years. Dose response below 20 mSv is strongly non-linear at the optimal latencies for the stomach (11.89 years, liver (36.9, lung (13.6, leukaemia (23.66, and pancreas (11.86 and across broad latency ranges. Confidence Intervals for ERR are comparable using Bootstrap and Likelihood Ratio Test methods and BCa 95% Confidence Intervals are strictly positive across latency ranges for all 5 cancers. Similar risk estimates for 10 mSv (lagged dose are obtained from the 0 - 20 mSv and 5 - 500 mSv data for the stomach, liver, lung and leukaemia. Dose response for the latter 3 cancers is significantly non-linear in the 5 - 500 mSv range. Conclusion Liver and urinary cancer mortality risk is significantly raised using a latency model with linear dose response. A non-linear model is strongly superior for the stomach, liver, lung, pancreas and leukaemia. Bootstrap and Likelihood-based confidence intervals are broadly comparable and ERR is strictly positive by bootstrap methods for all 5 cancers. Except for the pancreas, similar estimates of
Obraztsov, S. M.; Konobeev, Yu. V.; Birzhevoy, G. A.; Rachkov, V. I.
2006-12-01
The dependence of mechanical properties of ferritic/martensitic (F/M) steels on irradiation temperature is of interest because these steels are used as structural materials for fast, fusion reactors and accelerator driven systems. Experimental data demonstrating temperature peaks in physical and mechanical properties of neutron irradiated pure iron, nickel, vanadium, and austenitic stainless steels are available in the literature. A lack of such an information for F/M steels forces one to apply a computational mathematical-statistical modeling methods. The bootstrap procedure is one of such methods that allows us to obtain the necessary statistical characteristics using only a sample of limited size. In the present work this procedure is used for modeling the frequency distribution histograms of ultimate strength temperature peaks in pure iron and Russian F/M steels EP-450 and EP-823. Results of fitting the sums of Lorentz or Gauss functions to the calculated distributions are presented. It is concluded that there are two temperature (at 360 and 390 °C) peaks of the ultimate strength in EP-450 steel and single peak at 390 °C in EP-823.
Locality, bulk equations of motion and the conformal bootstrap
Energy Technology Data Exchange (ETDEWEB)
Kabat, Daniel [Department of Physics and Astronomy, Lehman College, City University of New York,250 Bedford Park Blvd. W, Bronx NY 10468 (United States); Lifschytz, Gilad [Department of Mathematics, Faculty of Natural Science, University of Haifa,199 Aba Khoushy Ave., Haifa 31905 (Israel)
2016-10-18
We develop an approach to construct local bulk operators in a CFT to order 1/N{sup 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 determine the bulk equations of motion to order 1/N{sup 2}.
Nonparametric bootstrap analysis with applications to demographic effects in demand functions.
Gozalo, P L
1997-12-01
"A new bootstrap proposal, labeled smooth conditional moment (SCM) bootstrap, is introduced for independent but not necessarily identically distributed data, where the classical bootstrap procedure fails.... A good example of the benefits of using nonparametric and bootstrap methods is the area of empirical demand analysis. In particular, we will be concerned with their application to the study of two important topics: what are the most relevant effects of household demographic variables on demand behavior, and to what extent present parametric specifications capture these effects." excerpt
Bootstrap inference when using multiple imputation.
Schomaker, Michael; Heumann, Christian
2018-04-16
Many modern estimators require bootstrapping to calculate confidence intervals because either no analytic standard error is available or the distribution of the parameter of interest is nonsymmetric. It remains however unclear how to obtain valid bootstrap inference when dealing with multiple imputation to address missing data. We present 4 methods that are intuitively appealing, easy to implement, and combine bootstrap estimation with multiple imputation. We show that 3 of the 4 approaches yield valid inference, but that the performance of the methods varies with respect to the number of imputed data sets and the extent of missingness. Simulation studies reveal the behavior of our approaches in finite samples. A topical analysis from HIV treatment research, which determines the optimal timing of antiretroviral treatment initiation in young children, demonstrates the practical implications of the 4 methods in a sophisticated and realistic setting. This analysis suffers from missing data and uses the g-formula for inference, a method for which no standard errors are available. Copyright © 2018 John Wiley & Sons, Ltd.
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.
Bootstrap and fast wave current drive for tokamak reactors
International Nuclear Information System (INIS)
Ehst, D.A.
1991-09-01
Using the multi-species neoclassical treatment of Hirshman and Sigmar we study steady state bootstrap equilibria with seed currents provided by low frequency (ICRF) fast waves and with additional surface current density driven by lower hybrid waves. This study applies to reactor plasmas of arbitrary aspect ratio. IN one limit the bootstrap component can supply nearly the total equilibrium current with minimal driving power ( o = 18 MA needs P FW = 15 MW, P LH = 75 MW). A computational survey of bootstrap fraction and current drive efficiency is presented. 11 refs., 8 figs
Current drive and sustain experiments with the bootstrap current in JT-60
International Nuclear Information System (INIS)
Kikuchi, Mitsuru; Azumi, Masafumi; Tani, Keiji; Tsuji, Shunji; Kubo, Hirotaka
1989-11-01
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 β p regime (β p = 3.2) and the current drive product I p (bootstrap) n-bar e R p up to 4.4 x 10 19 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 (I p = 0.5 -2 MA) and the poloidal beta (β p = 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 I p 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 T e 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 β p plasma are analyzed using the current profiles including the bootstrap current. The plasma pressure is close to the ballooning limit in high β p discharges. (author)
Bootstrapping the O(N) Archipelago
Kos, Filip; Simmons-Duffin, David; Vichi, Alessandro
2015-01-01
We study 3d CFTs with an $O(N)$ global symmetry using the conformal bootstrap for a system of mixed correlators. Specifically, we consider all nonvanishing scalar four-point functions containing the lowest dimension $O(N)$ vector $\\phi_i$ and the lowest dimension $O(N)$ singlet $s$, assumed to be the only relevant operators in their symmetry representations. The constraints of crossing symmetry and unitarity for these four-point functions force the scaling dimensions $(\\Delta_\\phi, \\Delta_s)$ to lie inside small islands. We also make rigorous determinations of current two-point functions in the $O(2)$ and $O(3)$ models, with applications to transport in condensed matter systems.
On a generalized bootstrap principle
International Nuclear Information System (INIS)
Corrigan, E.; Sasaki, R.; Dorey, P.E.
1993-01-01
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 (F 4 (1) , e 6 (2) ), is also considered and provides many interesting examples of pole generation. (author)
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...
International Nuclear Information System (INIS)
Wang, Guodong; He, Zhen; Xue, Li; Cui, Qingan; Lv, Shanshan; Zhou, Panpan
2017-01-01
Factors which significantly affect product reliability are of great interest to reliability practitioners. This paper proposes a bootstrap-based methodology for identifying significant factors when both location and scale parameters of the smallest extreme value distribution vary over experimental factors. An industrial thermostat experiment is presented, analyzed, and discussed as an illustrative example. The analysis results show that 1) the misspecification of a constant scale parameter may lead to misidentify spurious effects; 2) the important factors identified by different bootstrap methods (i.e., percentile bootstrapping, bias-corrected percentile bootstrapping, and bias-corrected and accelerated percentile bootstrapping) are different; 3) the number of factors affecting 10th percentile lifetime significantly is less than the number of important factors identified at 63.21th percentile. - Highlights: • Product reliability is improved by design of experiments under both scale and location parameters of smallest extreme value distribution vary with experimental factors. • A bootstrap-based methodology is proposed to identify important factors which affect 100pth lifetime percentile significantly. • Bootstrapping confidence intervals associating experimental factors are obtained by using three bootstrap methods (i.e., percentile bootstrapping, bias-corrected percentile bootstrapping, and bias-corrected and accelerated percentile bootstrapping). • The important factors identified by different bootstrap methods are different. • The number of factors affecting 10th percentile significantly is less than the number of important factors identified at 63.21th percentile.
Statistics and finance an introduction
Ruppert, David
2004-01-01
This textbook emphasizes the applications of statistics and probability to finance. Students are assumed to have had a prior course in statistics, but no background in finance or economics. The basics of probability and statistics are reviewed and more advanced topics in statistics, such as regression, ARMA and GARCH models, the bootstrap, and nonparametric regression using splines, are introduced as needed. The book covers the classical methods of finance such as portfolio theory, CAPM, and the Black-Scholes formula, and it introduces the somewhat newer area of behavioral finance. Applications and use of MATLAB and SAS software are stressed. The book will serve as a text in courses aimed at advanced undergraduates and masters students in statistics, engineering, and applied mathematics as well as quantitatively oriented MBA students. Those in the finance industry wishing to know more statistics could also use it for self-study. David Ruppert is the Andrew Schultz, Jr. Professor of Engineering, School of Oper...
Directory of Open Access Journals (Sweden)
Müller Kai F
2005-10-01
constrained node, at least not for datasets that fall within the size range found in the current literature. Conclusion In view of these results, calculating bootstrap or jackknife proportions with narrow confidence intervals even for very large datasets can be achieved with less expense than often thought. In particular, iterated bootstrap methods that aim at reducing statistical bias inherent to these proportions are more feasible when the individual bootstrap searches require less time.
Low mass diffractive dissociation in a simple t-dependent dual bootstrap model
International Nuclear Information System (INIS)
Bishari, M.
1978-08-01
The smallness of inelastic diffractive dissociation is explicitly demonstrated, in the framework of the '1/N dual unitarization' scheme, by incorporating a Deck type mechanism with the crucial planar bootstrap equation. Although both inelastic and elastic pomeron couplings are of the same order in 1/N, the origin for their smallness, however, is not identical. (author)
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.
Self-consistent ECCD calculations with bootstrap current
International Nuclear Information System (INIS)
Decker, J.; Bers, A.; Ram, A. K; Peysson, Y.
2003-01-01
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 f e . 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
Efficient generation of pronunciation dictionaries: human factors factors during bootstrapping
CSIR Research Space (South Africa)
Davel, MH
2004-10-01
Full Text Available Bootstrapping techniques have significant potential for the efficient generation of linguistic resources such as electronic pronunciation dictionaries. The authors describe a system and an approach to bootstrapping for the development...
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...
Bootstrapping pronunciation dictionaries: practical issues
CSIR Research Space (South Africa)
Davel, MH
2005-09-01
Full Text Available Bootstrapping techniques are an efficient way to develop electronic pronunciation dictionaries, but require fast system response to be practical for medium-to-large lexicons. In addition, user errors are inevitable during this process...
Bootstrapping the O(N) archipelago
Energy Technology Data Exchange (ETDEWEB)
Kos, Filip; Poland, David [Department of Physics, Yale University, New Haven, CT 06520 (United States); Simmons-Duffin, David [School of Natural Sciences, Institute for Advanced Study, Princeton, New Jersey 08540 (United States); Vichi, Alessandro [Theory Division, CERN, Geneva (Switzerland)
2015-11-17
We study 3d CFTs with an O(N) global symmetry using the conformal bootstrap for a system of mixed correlators. Specifically, we consider all nonvanishing scalar four-point functions containing the lowest dimension O(N) vector ϕ{sub i} and the lowest dimension O(N) singlet s, assumed to be the only relevant operators in their symmetry representations. The constraints of crossing symmetry and unitarity for these four-point functions force the scaling dimensions (Δ{sub ϕ},Δ{sub s}) to lie inside small islands. We also make rigorous determinations of current two-point functions in the O(2) and O(3) models, with applications to transport in condensed matter systems.
Bootstrapping as a Resource Dependence Management Strategy and its Association with Startup Growth
T. VANACKER; S. MANIGART; M. MEULEMAN; L. SELS
2011-01-01
This paper studies the association between bootstrapping and startup growth. Bootstrapping reduces a startup’s dependence on financial investors, but may create new dependencies. Drawing upon resource dependence theory, we hypothesize that when bootstrapping does not create new strong dependencies it will benefit startup growth, especially when dependence from financial investors is high. However, when bootstrapping creates new strong dependencies it will constrain growth, especially when dep...
Bootstrap embedding: An internally consistent fragment-based method
Energy Technology Data Exchange (ETDEWEB)
Welborn, Matthew; Tsuchimochi, Takashi; Van Voorhis, Troy [Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States)
2016-08-21
Strong correlation poses a difficult problem for electronic structure theory, with computational cost scaling quickly with system size. Fragment embedding is an attractive approach to this problem. By dividing a large complicated system into smaller manageable fragments “embedded” in an approximate description of the rest of the system, we can hope to ameliorate the steep cost of correlated calculations. While appealing, these methods often converge slowly with fragment size because of small errors at the boundary between fragment and bath. We describe a new electronic embedding method, dubbed “Bootstrap Embedding,” a self-consistent wavefunction-in-wavefunction embedding theory that uses overlapping fragments to improve the description of fragment edges. We apply this method to the one dimensional Hubbard model and a translationally asymmetric variant, and find that it performs very well for energies and populations. We find Bootstrap Embedding converges rapidly with embedded fragment size, overcoming the surface-area-to-volume-ratio error typical of many embedding methods. We anticipate that this method may lead to a low-scaling, high accuracy treatment of electron correlation in large molecular systems.
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...
Some statistical properties of gene expression clustering for array data
DEFF Research Database (Denmark)
Abreu, G C G; Pinheiro, A; Drummond, R D
2010-01-01
DNA array data without a corresponding statistical error measure. We propose an easy-to-implement and simple-to-use technique that uses bootstrap re-sampling to evaluate the statistical error of the nodes provided by SOM-based clustering. Comparisons between SOM and parametric clustering are presented...... for simulated as well as for two real data sets. We also implement a bootstrap-based pre-processing procedure for SOM, that improves the false discovery ratio of differentially expressed genes. Code in Matlab is freely available, as well as some supplementary material, at the following address: https...
Directory of Open Access Journals (Sweden)
Jong Seok Lee
2018-03-01
Full Text Available The purpose of this paper is to compare the degree of uncertainty of the water scarcity footprint using the Monte Carlo statistical method and block bootstrap method. Using the hydrological data of a water drainage basin in Korea, characterization factors based on the available water remaining (AWARE model were obtained. The uncertainties of the water scarcity footprint considering temporal variations in paddy rice production in Korea were estimated. The block bootstrap method gave five-times smaller percentage uncertainty values of the model output compared to that of the two different Monte Carlo statistical method scenarios. Incorrect estimation of the probability distribution of the AWARE characterization factor model is what causes the higher uncertainty in the water scarcity footprint value calculated by the Monte Carlo statistical method in this study. This is because AWARE characterization factor values partly follows discrete distribution with extreme value on one side. Therefore, this study suggests that the block bootstrap method is a better choice in analyzing uncertainty compared to the Monte Carlo statistical method when using the AWARE model to quantify the water scarcity footprint.
Bootstrapping the (A1, A2) Argyres-Douglas theory
Cornagliotto, Martina; Lemos, Madalena; Liendo, Pedro
2018-03-01
We apply bootstrap techniques in order to constrain the CFT data of the ( A 1 , A 2) Argyres-Douglas theory, which is arguably the simplest of the Argyres-Douglas models. We study the four-point function of its single Coulomb branch chiral ring generator and put numerical bounds on the low-lying spectrum of the theory. Of particular interest is an infinite family of semi-short multiplets labeled by the spin ℓ. Although the conformal dimensions of these multiplets are protected, their three-point functions are not. Using the numerical bootstrap we impose rigorous upper and lower bounds on their values for spins up to ℓ = 20. Through a recently obtained inversion formula, we also estimate them for sufficiently large ℓ, and the comparison of both approaches shows consistent results. We also give a rigorous numerical range for the OPE coefficient of the next operator in the chiral ring, and estimates for the dimension of the first R-symmetry neutral non-protected multiplet for small spin.
Thermal energy and bootstrap current in fusion reactor plasmas
International Nuclear Information System (INIS)
Becker, G.
1993-01-01
For DT fusion reactors with prescribed alpha particle heating power P α , 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 P α and V makes these relations independent of the magnitudes of the density and temperature, i.e. they only depend on P α , V and shape factors or profile parameters. For model density and temperature profiles analytic expressions for these shape factors and for the factor C bs in the bootstrap current formula I bs ∼ C bs (a/R) 1/2 β p I p 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
Directory of Open Access Journals (Sweden)
Mohammad Reza Marami Milani
2015-09-01
Full Text Available This study analyzes the linear relationship between climate variables and milk components in Iran by applying bootstrapping to include and assess the uncertainty. The climate parameters, Temperature Humidity Index (THI and Equivalent Temperature Index (ETI are computed from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA reanalysis (2002–2010. Milk data for fat, protein (measured on fresh matter bases, and milk yield are taken from 936,227 milk records for the same period, using cows fed by natural pasture from April to September. Confidence intervals for the regression model are calculated using the bootstrap technique. This method is applied to the original times series, generating statistically equivalent surrogate samples. As a result, despite the short time data and the related uncertainties, an interesting behavior of the relationships between milk compound and the climate parameters is visible. During spring only, a weak dependency of milk yield and climate variations is obvious, while fat and protein concentrations show reasonable correlations. In summer, milk yield shows a similar level of relationship with ETI, but not with temperature and THI. We suggest this methodology for studies in the field of the impacts of climate change and agriculture, also environment and food with short-term data.
Bootstrapping in language resource generation
CSIR Research Space (South Africa)
Davel, MH
2003-11-01
Full Text Available by Schultz [1]. Bootstrapping approaches are applicable to various lan- guage resource development tasks, specifically where an au- tomated mechanism can be defined to convert between vari- ous representations of the data considered. In the above ex...
Energy Technology Data Exchange (ETDEWEB)
Schmitt, J. C.; Talmadge, J. N.; Anderson, D. T. [Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706 (United States); Hanson, J. D. [Department of Physics, Auburn University, Auburn, Alabama 36849 (United States)
2014-09-15
The bootstrap current for three electron cyclotron resonance heated plasma scenarios in a quasihelically symmetric stellarator (the Helically Symmetric Experiment) are analyzed and compared to a neoclassical transport code PENTA. The three conditions correspond to 50 kW input power with a resonance that is off-axis, 50 kW on-axis heating and 100 kW on-axis heating. When the heating location was moved from off-axis to on-axis with 50 kW heating power, the stored energy and the extrapolated steady-state current were both observed to increase. When the on-axis heating power was increased from 50 kW to 100 kW, the stored energy continued to increase while the bootstrap current slightly decreased. This trend is qualitatively in agreement with the calculations which indicate that a large positive electric field for the 100 kW case was driving the current negative in a small region close to the magnetic axis and accounting for the decrease in the total integrated current. This trend in the calculations is only observed to occur when momentum conservation between particle species is included. Without momentum conservation, the calculated bootstrap current increases monotonically. We show that the magnitude of the bootstrap current as calculated by PENTA agrees better with the experiment when momentum conservation between plasma species is included in the calculation. The total current was observed in all cases to flow in a direction to unwind the transform, unlike in a tokamak in which the bootstrap current adds to the transform. The 3-D inductive response of the plasma is simulated to predict the evolution of the current profile during the discharge. The 3-D equilibrium reconstruction code V3FIT is used to reconstruct profiles of the plasma pressure and current constrained by measurements with a set of magnetic diagnostics. The reconstructed profiles are consistent with the measured plasma pressure profile and the simulated current profile when the
On transport and the bootstrap current in toroidal plasmas
International Nuclear Information System (INIS)
Connor, J.W.; Taylor, J.B.
1987-01-01
The recently reported observation of the bootstrap current in a tokamak plasma highlights the problem of reconciling this neoclassical effect with the anomalous (i.e., non-neoclassical) electron thermal transport. This Comment reviews the bootstrap current and considers the implications of a self-consistent modification of neoclassical theory based on an enhanced electron-electron interaction. (author)
Bootstrap current of fast ions in neutral beam injection heating
International Nuclear Information System (INIS)
Huang Qianhong; Gong Xueyu; Li Xinxia; Yu Jun
2012-01-01
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)
BootGraph: probabilistic fiber tractography using bootstrap algorithms and graph theory.
Vorburger, Robert S; Reischauer, Carolin; Boesiger, Peter
2013-02-01
Bootstrap methods have recently been introduced to diffusion-weighted magnetic resonance imaging to estimate the measurement uncertainty of ensuing diffusion parameters directly from the acquired data without the necessity to assume a noise model. These methods have been previously combined with deterministic streamline tractography algorithms to allow for the assessment of connection probabilities in the human brain. Thereby, the local noise induced disturbance in the diffusion data is accumulated additively due to the incremental progression of streamline tractography algorithms. Graph based approaches have been proposed to overcome this drawback of streamline techniques. For this reason, the bootstrap method is in the present work incorporated into a graph setup to derive a new probabilistic fiber tractography method, called BootGraph. The acquired data set is thereby converted into a weighted, undirected graph by defining a vertex in each voxel and edges between adjacent vertices. By means of the cone of uncertainty, which is derived using the wild bootstrap, a weight is thereafter assigned to each edge. Two path finding algorithms are subsequently applied to derive connection probabilities. While the first algorithm is based on the shortest path approach, the second algorithm takes all existing paths between two vertices into consideration. Tracking results are compared to an established algorithm based on the bootstrap method in combination with streamline fiber tractography and to another graph based algorithm. The BootGraph shows a very good performance in crossing situations with respect to false negatives and permits incorporating additional constraints, such as a curvature threshold. By inheriting the advantages of the bootstrap method and graph theory, the BootGraph method provides a computationally efficient and flexible probabilistic tractography setup to compute connection probability maps and virtual fiber pathways without the drawbacks of
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...
International Nuclear Information System (INIS)
Debón, A.; Carlos Garcia-Díaz, J.
2012-01-01
Advanced statistical models can help industry to design more economical and rational investment plans. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing. Increasingly stringent quality requirements in the automotive industry also require ongoing efforts in process control to make processes more robust. Robust methods for estimating the quality of galvanized steel coils are an important tool for the comprehensive monitoring of the performance of the manufacturing process. This study applies different statistical regression models: generalized linear models, generalized additive models and classification trees to estimate the quality of galvanized steel coils on the basis of short time histories. The data, consisting of 48 galvanized steel coils, was divided into sets of conforming and nonconforming coils. Five variables were selected for monitoring the process: steel strip velocity and four bath temperatures. The present paper reports a comparative evaluation of statistical models for binary data using Receiver Operating Characteristic (ROC) curves. A ROC curve is a graph or a technique for visualizing, organizing and selecting classifiers based on their performance. The purpose of this paper is to examine their use in research to obtain the best model to predict defective steel coil probability. In relation to the work of other authors who only propose goodness of fit statistics, we should highlight one distinctive feature of the methodology presented here, which is the possibility of comparing the different models with ROC graphs which are based on model classification performance. Finally, the results are validated by bootstrap procedures.
Design and implementation of new design of numerical experiments for non linear models
International Nuclear Information System (INIS)
Gazut, St.
2007-03-01
This thesis addresses the problem of the construction of surrogate models in numerical simulation. Whenever numerical experiments are costly, the simulation model is complex and difficult to use. It is important then to select the numerical experiments as efficiently as possible in order to minimize their number. In statistics, the selection of experiments is known as optimal experimental design. In the context of numerical simulation where no measurement uncertainty is present, we describe an alternative approach based on statistical learning theory and re-sampling techniques. The surrogate models are constructed using neural networks and the generalization error is estimated by leave-one-out, cross-validation and bootstrap. It is shown that the bootstrap can control the over-fitting and extend the concept of leverage for non linear in their parameters surrogate models. The thesis describes an iterative method called LDR for Learner Disagreement from experiment Re-sampling, based on active learning using several surrogate models constructed on bootstrap samples. The method consists in adding new experiments where the predictors constructed from bootstrap samples disagree most. We compare the LDR method with other methods of experimental design such as D-optimal selection. (author)
Bootstrap current of fast ions in neutral beam injection heating
International Nuclear Information System (INIS)
Huang Qianhong; Gong Xueyu; Yang Lei; Li Xinxia; Lu Xingqiang; Yu Jun
2012-01-01
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)
Molinos-Senante, María; Donoso, Guillermo; Sala-Garrido, Ramon; Villegas, Andrés
2018-03-01
Benchmarking the efficiency of water companies is essential to set water tariffs and to promote their sustainability. In doing so, most of the previous studies have applied conventional data envelopment analysis (DEA) models. However, it is a deterministic method that does not allow to identify environmental factors influencing efficiency scores. To overcome this limitation, this paper evaluates the efficiency of a sample of Chilean water and sewerage companies applying a double-bootstrap DEA model. Results evidenced that the ranking of water and sewerage companies changes notably whether efficiency scores are computed applying conventional or double-bootstrap DEA models. Moreover, it was found that the percentage of non-revenue water and customer density are factors influencing the efficiency of Chilean water and sewerage companies. This paper illustrates the importance of using a robust and reliable method to increase the relevance of benchmarking tools.
Bootstrapping N=3 superconformal theories
Energy Technology Data Exchange (ETDEWEB)
Lemos, Madalena; Liendo, Pedro [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Theory Group; Meneghelli, Carlo [Stony Brook Univ., Stony Brook, NY (United States). Simons Center for Geometry and Physics; Mitev, Vladimir [Mainz Univ. (Germany). PRISMA Cluster of Excellence
2016-12-15
We initiate the bootstrap program for N=3 superconformal field theories (SCFTs) in four dimensions. The problem is considered from two fronts: the protected subsector described by a 2d chiral algebra, and crossing symmetry for half-BPS operators whose superconformal primaries parametrize the Coulomb branch of N=3 theories. With the goal of describing a protected subsector of a family of =3 SCFTs, we propose a new 2d chiral algebra with super Virasoro symmetry that depends on an arbitrary parameter, identified with the central charge of the theory. Turning to the crossing equations, we work out the superconformal block expansion and apply standard numerical bootstrap techniques in order to constrain the CFT data. We obtain bounds valid for any theory but also, thanks to input from the chiral algebra results, we are able to exclude solutions with N=4 supersymmetry, allowing us to zoom in on a specific N=3 SCFT.
Bootstrapping N=3 superconformal theories
Energy Technology Data Exchange (ETDEWEB)
Lemos, Madalena; Liendo, Pedro [DESY Hamburg, Theory Group,Notkestrasse 85, D-22607 Hamburg (Germany); Meneghelli, Carlo [Simons Center for Geometry and Physics,Stony Brook University, Stony Brook, NY 11794-3636 (United States); Mitev, Vladimir [PRISMA Cluster of Excellence, Institut für Physik,JGU Mainz, Staudingerweg 7, 55128 Mainz (Germany)
2017-04-06
We initiate the bootstrap program for N=3 superconformal field theories (SCFTs) in four dimensions. The problem is considered from two fronts: the protected subsector described by a 2d chiral algebra, and crossing symmetry for half-BPS operators whose superconformal primaries parametrize the Coulomb branch of N=3 theories. With the goal of describing a protected subsector of a family of N=3 SCFTs, we propose a new 2d chiral algebra with super Virasoro symmetry that depends on an arbitrary parameter, identified with the central charge of the theory. Turning to the crossing equations, we work out the superconformal block expansion and apply standard numerical bootstrap techniques in order to constrain the CFT data. We obtain bounds valid for any theory but also, thanks to input from the chiral algebra results, we are able to exclude solutions with N=4 supersymmetry, allowing us to zoom in on a specific N=3 SCFT.
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...
Li, Hao; Dong, Siping
2015-01-01
China has long been stuck in applying traditional data envelopment analysis (DEA) models to measure technical efficiency of public hospitals without bias correction of efficiency scores. In this article, we have introduced the Bootstrap-DEA approach from the international literature to analyze the technical efficiency of public hospitals in Tianjin (China) and tried to improve the application of this method for benchmarking and inter-organizational learning. It is found that the bias corrected efficiency scores of Bootstrap-DEA differ significantly from those of the traditional Banker, Charnes, and Cooper (BCC) model, which means that Chinese researchers need to update their DEA models for more scientific calculation of hospital efficiency scores. Our research has helped shorten the gap between China and the international world in relative efficiency measurement and improvement of hospitals. It is suggested that Bootstrap-DEA be widely applied into afterward research to measure relative efficiency and productivity of Chinese hospitals so as to better serve for efficiency improvement and related decision making. © The Author(s) 2015.
Heptagons from the Steinmann cluster bootstrap
International Nuclear Information System (INIS)
Dixon, Lance J.; Drummond, James; Papathanasiou, Georgios
2017-01-01
We reformulate the heptagon cluster bootstrap to take advantage of the Steinmann relations, which require certain double discontinuities of any amplitude to vanish. These constraints vastly reduce the number of functions needed to bootstrap seven-point amplitudes in planar N = 4 supersymmetric Yang-Mills theory, making higher-loop contributions to these amplitudes more computationally accessible. In particular, dual superconformal symmetry and well-defined collinear limits suffice to determine uniquely the symbols of the three-loop NMHV and four-loop MHV seven-point amplitudes. We also show that at three loops, relaxing the dual superconformal Q̄ relations and imposing dihedral symmetry (and for NMHV the absence of spurious poles) leaves only a single ambiguity in the heptagon amplitudes. These results point to a strong tension between the collinear properties of the amplitudes and the Steinmann relations.
On a linear method in bootstrap confidence intervals
Directory of Open Access Journals (Sweden)
Andrea Pallini
2007-10-01
Full Text Available A linear method for the construction of asymptotic bootstrap confidence intervals is proposed. We approximate asymptotically pivotal and non-pivotal quantities, which are smooth functions of means of n independent and identically distributed random variables, by using a sum of n independent smooth functions of the same analytical form. Errors are of order Op(n-3/2 and Op(n-2, respectively. The linear method allows a straightforward approximation of bootstrap cumulants, by considering the set of n independent smooth functions as an original random sample to be resampled with replacement.
TRANSFORMERLESS OPERATION OF DIII-D WITH HIGH BOOTSTRAP FRACTION
International Nuclear Information System (INIS)
POLITZER, PA; HYATT, AW; LUCE, TC; MAHDAVI, MA; MURAKAMI, M; PERKINS, FW; PRATER, R; TURNBULL, AD; CASPER, TA; FERRON, JR; JAYAKUMAR, RJ; LAHAYE, RJ; LAZARUS, EA; PETTY, CC; WADE, MR
2003-01-01
OAK-B135 The authors have initiated an experimental program to address some of the questions associated with operation of a tokamak with high bootstrap current fraction under high performance conditions, without assistance from a transformer. In these discharges they have maintained stationary (or slowly improving) conditions for > 2.2 s at β N ∼ β p ∼ 2.8. Significant current overdrive, with dI/dt > 50 kA/s and zero or negative voltage, is sustained for over 0.7 s. The overdrive condition is usually ended with the appearance of MHD activity, which alters the profiles and reduces the bootstrap current. Characteristically these plasmas have 65%-80% bootstrap current, 25%-30% NBCD, and 5%-10% ECCD. Fully noninductive operation is essential for steady-state tokamaks. For efficient operation, the bootstrap current fraction must be close to 100%, allowing for a small additional (∼ 10%) external current drive capability to be used for control. In such plasmas the current and pressure profiles are rightly coupled because J(r) is entirely determined by p(r) (or more accurately by the kinetic profiles). The pressure gradient in turn is determined by transport coefficients which depend on the poloidal field profile
Neoclassical bootstrap current and transport in optimized stellarator configurations
International Nuclear Information System (INIS)
Maassberg, H.; Lotz, W.; Nuehrenberg, J.
1993-01-01
The neoclassical bootstrap current properties of optimized stellarators are analyzed in the relevant mean-free-path regimes and compared with the neoclassical transport properties. Two methods---global Monte Carlo simulation [Phys. Fluids 31, 2984 (1988)], and local analysis with the drift kinetic equation solver code [Phys. Fluids B 1, 563 (1989)]---are employed and good agreement is obtained. Full consistency with the elimination of the bootstrap current and favorable neoclassical transport are found
Bootstrapping Kernel-Based Semiparametric Estimators
DEFF Research Database (Denmark)
Cattaneo, Matias D.; Jansson, Michael
by accommodating a non-negligible bias. A noteworthy feature of the assumptions under which the result is obtained is that reliance on a commonly employed stochastic equicontinuity condition is avoided. The second main result shows that the bootstrap provides an automatic method of correcting for the bias even...... when it is non-negligible....
Introduccción al Bootstrap: Desarrollo de un ejemplo acompañado de software de aplicación
Directory of Open Access Journals (Sweden)
Rubén Ledesma
2008-09-01
Full Text Available El bootstrap es un tipo de técnica de remuestreo de datos que permite resolver problemas relacionados con la estimación de intervalos de confianza o la prueba de significación estadística. Este enfoque puede resultar de interés para los investigadores en Psicología, no solo porque es menos restrictivo que el enfoque estadístico clásico, sino también porque es más general en su formulación y más simple de comprender en lo referente al procedimiento básico que subyace al método. En lugar de fórmulas o modelos matemáticos abstractos, el bootstrap simplemente requiere un ordenador capaz de simular un proceso de muestreo aleatorio de los datos. Sin embargo, y debido quizás a la escasa difusión de la técnica, los investigadores aún no han incorporado el bootstrap al repertorio habitual de herramientas de análisis de datos. En este trabajo realizamos una presentación conceptual del bootstrap, ilustramos la técnica mediante un ejemplo y revisamos algunas opciones disponibles en materia de software estadístico. El trabajo incluye además un programa para correr el ejemplo dentro de ViSta The Visual Statistics System, un sistema estadístico gratuito y abierto.
Heptagons from the Steinmann cluster bootstrap
International Nuclear Information System (INIS)
Dixon, Lance J.; McLeod, Andrew J.; Drummond, James; Harrington, Thomas; Spradlin, Marcus; Papathanasiou, Georgios; Stanford Univ., CA
2016-12-01
We reformulate the heptagon cluster bootstrap to take advantage of the Steinmann relations, which require certain double discontinuities of any amplitude to vanish. These constraints vastly reduce the number of functions needed to bootstrap seven-point amplitudes in planar N=4 supersymmetric Yang-Mills theory, making higher-loop contributions to these amplitudes more computationally accessible. In particular, dual superconformal symmetry and well-defined collinear limits suffice to determine uniquely the symbols of the three-loop NMHV and four-loop MHV seven-point amplitudes. We also show that at three loops, relaxing the dual superconformal (anti Q) relations and imposing dihedral symmetry (and for NMHV the absence of spurious poles) leaves only a single ambiguity in the heptagon amplitudes. These results point to a strong tension between the collinear properties of the amplitudes and the Steinmann relations.
Heptagons from the Steinmann cluster bootstrap
Energy Technology Data Exchange (ETDEWEB)
Dixon, Lance J.; McLeod, Andrew J. [Stanford Univ., CA (United States). SLAC National Accelerator Lab.; Drummond, James [Southampton Univ. (United Kingdom). School of Physics and Astronomy; Harrington, Thomas; Spradlin, Marcus [Brown Univ., Providence, RI (United States). Dept. of Physics; Papathanasiou, Georgios [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Theory Group; Stanford Univ., CA (United States). SLAC National Accelerator Lab.
2016-12-15
We reformulate the heptagon cluster bootstrap to take advantage of the Steinmann relations, which require certain double discontinuities of any amplitude to vanish. These constraints vastly reduce the number of functions needed to bootstrap seven-point amplitudes in planar N=4 supersymmetric Yang-Mills theory, making higher-loop contributions to these amplitudes more computationally accessible. In particular, dual superconformal symmetry and well-defined collinear limits suffice to determine uniquely the symbols of the three-loop NMHV and four-loop MHV seven-point amplitudes. We also show that at three loops, relaxing the dual superconformal (anti Q) relations and imposing dihedral symmetry (and for NMHV the absence of spurious poles) leaves only a single ambiguity in the heptagon amplitudes. These results point to a strong tension between the collinear properties of the amplitudes and the Steinmann relations.
Energy Technology Data Exchange (ETDEWEB)
Gazut, St
2007-03-15
This thesis addresses the problem of the construction of surrogate models in numerical simulation. Whenever numerical experiments are costly, the simulation model is complex and difficult to use. It is important then to select the numerical experiments as efficiently as possible in order to minimize their number. In statistics, the selection of experiments is known as optimal experimental design. In the context of numerical simulation where no measurement uncertainty is present, we describe an alternative approach based on statistical learning theory and re-sampling techniques. The surrogate models are constructed using neural networks and the generalization error is estimated by leave-one-out, cross-validation and bootstrap. It is shown that the bootstrap can control the over-fitting and extend the concept of leverage for non linear in their parameters surrogate models. The thesis describes an iterative method called LDR for Learner Disagreement from experiment Re-sampling, based on active learning using several surrogate models constructed on bootstrap samples. The method consists in adding new experiments where the predictors constructed from bootstrap samples disagree most. We compare the LDR method with other methods of experimental design such as D-optimal selection. (author)
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($N$)....
A framework for bootstrapping morphological decomposition
CSIR Research Space (South Africa)
Joubert, LJ
2004-11-01
Full Text Available The need for a bootstrapping approach to the morphological decomposition of words in agglutinative languages such as isiZulu is motivated, and the complexities of such an approach are described. The authors then introduce a generic framework which...
Directory of Open Access Journals (Sweden)
José Antonio Castorina
2005-12-01
Full Text Available El presente artículo expone la teoría explicativa propuesta por Carey para el cambio conceptual. Primeramente, se plantea la cuestión de la reorganización conceptual en la psicología cognitiva y la posición de Carey. En segundo lugar, se ponen de relieve las condiciones epistémica que deben cumplir las "teorías" infantiles para que la reestructuración conceptual sea posible, así como los modos que adopta esta última. En tercer lugar, se muestran los resultados de investigaciones que verifican el cambio conceptual entre teorías infantiles de biología intuitiva. En cuarto lugar, se plantean las dificultades de otras teorías del cambio conceptual, para luego formular los rasgos del mecanismo alternativo de bootstrapping y su pertinencia para interpretrar los datos de las indagaciones mencionadas. Finalmente, se evalúan la originalidad de la teoría del bootstrpping en el escenario de los debates contemporáneos. Muy especialmente, se esboza una posible aproximación con las tesis dialécticas de Piaget.This paper examines the Carey's theory of conceptual change. First, it describes the conceptual reorganization in cognitive psychology and the author position. Second, the epistemic conditions that children "theories" should fulfil to make conceptual restructuring possible, as well as the ways adopted by the latter, are analyzed. In third place, findings of researches testing the conceptual change among biology intuitive children theories are explained. Subsequently, it discusses the difficulties other theories of conceptual change present, in order to state features of bootstrapping as an alternative mechanism and its relevance for the interpretation of abovementioned researches results. Finally, it evaluates the originality of "bootstrapping" theory in the scene of contemporary debates. It particularly outlines a possible approach to Piaget's dialectic theses.
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
2016-03-11
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.
Efficient statistical tests to compare Youden index: accounting for contingency correlation.
Chen, Fangyao; Xue, Yuqiang; Tan, Ming T; Chen, Pingyan
2015-04-30
Youden index is widely utilized in studies evaluating accuracy of diagnostic tests and performance of predictive, prognostic, or risk models. However, both one and two independent sample tests on Youden index have been derived ignoring the dependence (association) between sensitivity and specificity, resulting in potentially misleading findings. Besides, paired sample test on Youden index is currently unavailable. This article develops efficient statistical inference procedures for one sample, independent, and paired sample tests on Youden index by accounting for contingency correlation, namely associations between sensitivity and specificity and paired samples typically represented in contingency tables. For one and two independent sample tests, the variances are estimated by Delta method, and the statistical inference is based on the central limit theory, which are then verified by bootstrap estimates. For paired samples test, we show that the estimated covariance of the two sensitivities and specificities can be represented as a function of kappa statistic so the test can be readily carried out. We then show the remarkable accuracy of the estimated variance using a constrained optimization approach. Simulation is performed to evaluate the statistical properties of the derived tests. The proposed approaches yield more stable type I errors at the nominal level and substantially higher power (efficiency) than does the original Youden's approach. Therefore, the simple explicit large sample solution performs very well. Because we can readily implement the asymptotic and exact bootstrap computation with common software like R, the method is broadly applicable to the evaluation of diagnostic tests and model performance. Copyright © 2015 John Wiley & Sons, Ltd.
International Nuclear Information System (INIS)
Zio, E.; Apostolakis, G.E.; Pedroni, N.
2010-01-01
The estimation of the functional failure probability of a thermal-hydraulic (T-H) passive system can be done by Monte Carlo (MC) sampling of the epistemic uncertainties affecting the system model and the numerical values of its parameters, followed by the computation of the system response by a mechanistic T-H code, for each sample. The computational effort associated to this approach can be prohibitive because a large number of lengthy T-H code simulations must be performed (one for each sample) for accurate quantification of the functional failure probability and the related statistics. In this paper, the computational burden is reduced by replacing the long-running, original T-H code by a fast-running, empirical regression model: in particular, an Artificial Neural Network (ANN) model is considered. It is constructed on the basis of a limited-size set of data representing examples of the input/output nonlinear relationships underlying the original T-H code; once the model is built, it is used for performing, in an acceptable computational time, the numerous system response calculations needed for an accurate failure probability estimation, uncertainty propagation and sensitivity analysis. The empirical approximation of the system response provided by the ANN model introduces an additional source of (model) uncertainty, which needs to be evaluated and accounted for. A bootstrapped ensemble of ANN regression models is here built for quantifying, in terms of confidence intervals, the (model) uncertainties associated with the estimates provided by the ANNs. For demonstration purposes, an application to the functional failure analysis of an emergency passive decay heat removal system in a simple steady-state model of a Gas-cooled Fast Reactor (GFR) is presented. The functional failure probability of the system is estimated together with global Sobol sensitivity indices. The bootstrapped ANN regression model built with low computational time on few (e.g., 100) data
Energy Technology Data Exchange (ETDEWEB)
Zio, E., E-mail: enrico.zio@polimi.i [Energy Department, Politecnico di Milano, Via Ponzio 34/3, 20133 Milan (Italy); Apostolakis, G.E., E-mail: apostola@mit.ed [Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139-4307 (United States); Pedroni, N. [Energy Department, Politecnico di Milano, Via Ponzio 34/3, 20133 Milan (Italy)
2010-05-15
The estimation of the functional failure probability of a thermal-hydraulic (T-H) passive system can be done by Monte Carlo (MC) sampling of the epistemic uncertainties affecting the system model and the numerical values of its parameters, followed by the computation of the system response by a mechanistic T-H code, for each sample. The computational effort associated to this approach can be prohibitive because a large number of lengthy T-H code simulations must be performed (one for each sample) for accurate quantification of the functional failure probability and the related statistics. In this paper, the computational burden is reduced by replacing the long-running, original T-H code by a fast-running, empirical regression model: in particular, an Artificial Neural Network (ANN) model is considered. It is constructed on the basis of a limited-size set of data representing examples of the input/output nonlinear relationships underlying the original T-H code; once the model is built, it is used for performing, in an acceptable computational time, the numerous system response calculations needed for an accurate failure probability estimation, uncertainty propagation and sensitivity analysis. The empirical approximation of the system response provided by the ANN model introduces an additional source of (model) uncertainty, which needs to be evaluated and accounted for. A bootstrapped ensemble of ANN regression models is here built for quantifying, in terms of confidence intervals, the (model) uncertainties associated with the estimates provided by the ANNs. For demonstration purposes, an application to the functional failure analysis of an emergency passive decay heat removal system in a simple steady-state model of a Gas-cooled Fast Reactor (GFR) is presented. The functional failure probability of the system is estimated together with global Sobol sensitivity indices. The bootstrapped ANN regression model built with low computational time on few (e.g., 100) data
Bootstrapping the economy -- a non-parametric method of generating consistent future scenarios
Müller, Ulrich A; Bürgi, Roland; Dacorogna, Michel M
2004-01-01
The fortune and the risk of a business venture depends on the future course of the economy. There is a strong demand for economic forecasts and scenarios that can be applied to planning and modeling. While there is an ongoing debate on modeling economic scenarios, the bootstrapping (or resampling) approach presented here has several advantages. As a non-parametric method, it directly relies on past market behaviors rather than debatable assumptions on models and parameters. Simultaneous dep...
Bootstrapping mixed correlators in the five dimensional critical O(N) models
Energy Technology Data Exchange (ETDEWEB)
Li, Zhijin; Su, Ning [George P. and Cynthia W. Mitchell Institute for Fundamental Physics and Astronomy,Texas A& M University, College Station, TX 77843 (United States)
2017-04-18
We use the conformal bootstrap approach to explore 5D CFTs with O(N) global symmetry, which contain N scalars ϕ{sub i} transforming as O(N) vector. Specifically, we study multiple four-point correlators of the leading O(N) vector ϕ{sub i} and the O(N) singlet σ. The crossing symmetry of the four-point functions and the unitarity condition provide nontrivial constraints on the scaling dimensions (Δ{sub ϕ}, Δ{sub σ}) of ϕ{sub i} and σ. With reasonable assumptions on the gaps between scaling dimensions of ϕ{sub i} (σ) and the next O(N) vector ϕ{sub i}{sup ′} (singlet σ{sup ′}) scalar, we are able to isolate the scaling dimensions (Δ{sub ϕ}, Δ{sub σ}) in small islands. In particular, for large N=500, the isolated region is highly consistent with the result obtained from large N expansion. We also study the interacting O(N) CFTs for 1≤N≤100. Isolated regions on (Δ{sub ϕ},Δ{sub σ}) plane are obtained using conformal bootstrap program with lower order of derivatives Λ; however, they disappear after increasing Λ. For N=100, no solution can be found with Λ=25 under the assumptions on the scaling dimensions of next O(N) vector Δ{sub ϕ{sub i{sup ′}}}≥5.0 (singlet Δ{sub σ{sup ′}}≥3.3). These islands are expected to be corresponding to interacting but nonunitary O(N) CFTs. Our results suggest a lower bound on the critical value N{sub c}>100, below which the interacting O(N) CFTs turn into nonunitary.
All of statistics a concise course in statistical inference
Wasserman, Larry
2004-01-01
This book is for people who want to learn probability and statistics quickly It brings together many of the main ideas in modern statistics in one place The book is suitable for students and researchers in statistics, computer science, data mining and machine learning This book covers a much wider range of topics than a typical introductory text on mathematical statistics It includes modern topics like nonparametric curve estimation, bootstrapping and classification, topics that are usually relegated to follow-up courses The reader is assumed to know calculus and a little linear algebra No previous knowledge of probability and statistics is required The text can be used at the advanced undergraduate and graduate level Larry Wasserman is Professor of Statistics at Carnegie Mellon University He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bi...
Progress Toward Steady State Tokamak Operation Exploiting the high bootstrap current fraction regime
Ren, Q.
2015-11-01
Recent DIII-D experiments have advanced the normalized fusion performance of the high bootstrap current fraction tokamak regime toward reactor-relevant steady state operation. The experiments, conducted by a joint team of researchers from the DIII-D and EAST tokamaks, developed a fully noninductive scenario that could be extended on EAST to a demonstration of long pulse steady-state tokamak operation. Fully noninductive plasmas with extremely high values of the poloidal beta, βp >= 4 , have been sustained at βT >= 2 % for long durations with excellent energy confinement quality (H98y,2 >= 1 . 5) and internal transport barriers (ITBs) generated at large minor radius (>= 0 . 6) in all channels (Te, Ti, ne, VTf). Large bootstrap fraction (fBS ~ 80 %) has been obtained with high βp. ITBs have been shown to be compatible with steady state operation. Because of the unusually large ITB radius, normalized pressure is not limited to low βN values by internal ITB-driven modes. βN up to ~4.3 has been obtained by optimizing the plasma-wall distance. The scenario is robust against several variations, including replacing some on-axis with off-axis neutral beam injection (NBI), adding electron cyclotron (EC) heating, and reducing the NBI torque by a factor of 2. This latter observation is particularly promising for extension of the scenario to EAST, where maximum power is obtained with balanced NBI injection, and to a reactor, expected to have low rotation. However, modeling of this regime has provided new challenges to state-of-the-art modeling capabilities: quasilinear models can dramatically underpredict the electron transport, and the Sauter bootstrap current can be insufficient. The analysis shows first-principle NEO is in good agreement with experiments for the bootstrap current calculation and ETG modes with a larger saturated amplitude or EM modes may provide the missing electron transport. Work supported in part by the US DOE under DE-FC02-04ER54698, DE-AC52-07NA
Pasta, D J; Taylor, J L; Henning, J M
1999-01-01
Decision-analytic models are frequently used to evaluate the relative costs and benefits of alternative therapeutic strategies for health care. Various types of sensitivity analysis are used to evaluate the uncertainty inherent in the models. Although probabilistic sensitivity analysis is more difficult theoretically and computationally, the results can be much more powerful and useful than deterministic sensitivity analysis. The authors show how a Monte Carlo simulation can be implemented using standard software to perform a probabilistic sensitivity analysis incorporating the bootstrap. The method is applied to a decision-analytic model evaluating the cost-effectiveness of Helicobacter pylori eradication. The necessary steps are straightforward and are described in detail. The use of the bootstrap avoids certain difficulties encountered with theoretical distributions. The probabilistic sensitivity analysis provided insights into the decision-analytic model beyond the traditional base-case and deterministic sensitivity analyses and should become the standard method for assessing sensitivity.
Robust block bootstrap panel predictability tests
Westerlund, J.; Smeekes, S.
2013-01-01
Most panel data studies of the predictability of returns presume that the cross-sectional units are independent, an assumption that is not realistic. As a response to this, the current paper develops block bootstrap-based panel predictability tests that are valid under very general conditions. Some
Financial bootstrapping use in new family ventures and the impact on venture growth
Helleboogh, David; LAVEREN, Eddy; LYBAERT, Nadine
2010-01-01
This paper contributes to the general knowledge of bootstrap financing among new family ventures in two ways. Firstly, this research reveals which human capital characteristics of the owner-manager has an impact on financial bootstrapping use. The empirical results indicate that the use of bootstrapping techniques does not depend upon the family's business founder's education, but that it is a skill which is absorbed from self-employed parents or during the founder's prior work and management...
Financial bootstrapping use in family ventures and the impact on start-up growth
Helleboogh, D.; Laveren, E.; LYBAERT, Nadine
2010-01-01
This paper contributes to the general knowledge of bootstrap financing among new family ventures in two ways. Firstly, this research reveals which human capital characteristics of the owner-manager has an impact on financial bootstrapping use. The empirical results indicate that the use of bootstrapping techniques does not depend upon the family business founder's education, but that it is a skill which is absorbed from self-employed parents or during the founder‟s prior work and management e...
Lomnitz, Cinna
Tichelaar and Ruff [1989] propose to “estimate model variance in complicated geophysical problems,” including the determination of focal depth in earthquakes, by means of unconventional statistical methods such as bootstrapping. They are successful insofar as they are able to duplicate the results from more conventional procedures.
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.
Smoothed Bootstrap und seine Anwendung in parametrischen Testverfahren
Directory of Open Access Journals (Sweden)
Handschuh, Dmitri
2015-03-01
Full Text Available In empirical research, the distribution of observations is usually unknown. This creates a problem if parametric methods are to be employed. The functionality of parametric methods relies on strong parametric assumptions. If these are violated the result of using classical parametric methods is questionable. Therefore, modifications of the parametric methods are required, if the appropriateness of their assumptions is in doubt. In this article, a modification of the smoothed bootstrap is presented (using the linear interpolation to approximate the distribution law suggested by the data. The application of this modification to statistical parametric methods allows taking into account deviations of the observed data distributions from the classical distribution assumptions without changing to other hypotheses, which often is implicit in using nonparametric methods. The approach is based on Monte Carlo method and is presented using one-way ANOVA as an example. The original and the modified statistical methods lead to identical outcomes when the assumptions of the original method are satisfied. For strong violations of the distributional assumptions, the modified version of the method is generally preferable. All procedures have been implemented in SAS. Test characteristics (type 1 error, the operating characteristic curve of the modified ANOVA are calculated.
Effect of non-normality on test statistics for one-way independent groups designs.
Cribbie, Robert A; Fiksenbaum, Lisa; Keselman, H J; Wilcox, Rand R
2012-02-01
The data obtained from one-way independent groups designs is typically non-normal in form and rarely equally variable across treatment populations (i.e., population variances are heterogeneous). Consequently, the classical test statistic that is used to assess statistical significance (i.e., the analysis of variance F test) typically provides invalid results (e.g., too many Type I errors, reduced power). For this reason, there has been considerable interest in finding a test statistic that is appropriate under conditions of non-normality and variance heterogeneity. Previously recommended procedures for analysing such data include the James test, the Welch test applied either to the usual least squares estimators of central tendency and variability, or the Welch test with robust estimators (i.e., trimmed means and Winsorized variances). A new statistic proposed by Krishnamoorthy, Lu, and Mathew, intended to deal with heterogeneous variances, though not non-normality, uses a parametric bootstrap procedure. In their investigation of the parametric bootstrap test, the authors examined its operating characteristics under limited conditions and did not compare it to the Welch test based on robust estimators. Thus, we investigated how the parametric bootstrap procedure and a modified parametric bootstrap procedure based on trimmed means perform relative to previously recommended procedures when data are non-normal and heterogeneous. The results indicated that the tests based on trimmed means offer the best Type I error control and power when variances are unequal and at least some of the distribution shapes are non-normal. © 2011 The British Psychological Society.
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: βbootstrap 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...
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.
Definition of total bootstrap current in tokamaks
International Nuclear Information System (INIS)
Ross, D.W.
1995-01-01
Alternative definitions of the total bootstrap current are compared. An analogous comparison is given for the ohmic and auxiliary currents. It is argued that different definitions than those usually employed lead to simpler analyses of tokamak operating scenarios
A note on the kappa statistic for clustered dichotomous data.
Zhou, Ming; Yang, Zhao
2014-06-30
The kappa statistic is widely used to assess the agreement between two raters. Motivated by a simulation-based cluster bootstrap method to calculate the variance of the kappa statistic for clustered physician-patients dichotomous data, we investigate its special correlation structure and develop a new simple and efficient data generation algorithm. For the clustered physician-patients dichotomous data, based on the delta method and its special covariance structure, we propose a semi-parametric variance estimator for the kappa statistic. An extensive Monte Carlo simulation study is performed to evaluate the performance of the new proposal and five existing methods with respect to the empirical coverage probability, root-mean-square error, and average width of the 95% confidence interval for the kappa statistic. The variance estimator ignoring the dependence within a cluster is generally inappropriate, and the variance estimators from the new proposal, bootstrap-based methods, and the sampling-based delta method perform reasonably well for at least a moderately large number of clusters (e.g., the number of clusters K ⩾50). The new proposal and sampling-based delta method provide convenient tools for efficient computations and non-simulation-based alternatives to the existing bootstrap-based methods. Moreover, the new proposal has acceptable performance even when the number of clusters is as small as K = 25. To illustrate the practical application of all the methods, one psychiatric research data and two simulated clustered physician-patients dichotomous data are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.
Collisionality dependence of Mercier stability in LHD equilibria with bootstrap currents
International Nuclear Information System (INIS)
Ichiguchi, Katsuji.
1997-02-01
The Mercier stability of the plasmas carrying bootstrap currents with different plasma collisionality is studied in the Large Helical Device (LHD). In the LHD configuration, the direction of the bootstrap current depends on the collisionality of the plasma through the change in the sign of the geometrical factor. When the beta value is raised by increasing the density of the plasma with a fixed low temperature, the plasma becomes more collisional and the collisionality approaches the plateau regime. In this case, the bootstrap current can flow in the direction so as to decrease the rotational transform. Then, the large Shafranov shift enhances the magnetic well and the magnetic shear, and therefore, the Mercier stability is improved. On the other hand, when the beta value is raised by increasing the temperature of the plasma with a fixed low density, the plasma collisionality becomes reduced to enter the 1/ν collisionality regime and the bootstrap current flows so that the rotational transform should be increased, which is unfavorable for the Mercier stability. Hence, the beta value should be raised by increasing the density rather than the temperature in order to obtain a high beta plasma. (author)
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 r...... in different studies performed on the same set of products. In addition, the graphical display of confidence ellipses eases interpretation and communication of results....
Inverse bootstrapping conformal field theories
Li, Wenliang
2018-01-01
We propose a novel approach to study conformal field theories (CFTs) in general dimensions. In the conformal bootstrap program, one usually searches for consistent CFT data that satisfy crossing symmetry. In the new method, we reverse the logic and interpret manifestly crossing-symmetric functions as generating functions of conformal data. Physical CFTs can be obtained by scanning the space of crossing-symmetric functions. By truncating the fusion rules, we are able to concentrate on the low-lying operators and derive some approximate relations for their conformal data. It turns out that the free scalar theory, the 2d minimal model CFTs, the ϕ 4 Wilson-Fisher CFT, the Lee-Yang CFTs and the Ising CFTs are consistent with the universal relations from the minimal fusion rule ϕ 1 × ϕ 1 = I + ϕ 2 + T , where ϕ 1 , ϕ 2 are scalar operators, I is the identity operator and T is the stress tensor.
Effect of bootstrap current on MHD equilibrium beta limit in heliotron plasmas
International Nuclear Information System (INIS)
Watanabe, K.Y.
2001-01-01
The effect of bootstrap current on the beta limit of MHD equilibria is studied systematically by an iterative calculation of MHD equilibrium and the consistent bootstrap current in high beta heliotron plasmas. The LHD machine is treated as a standard configuration heliotron with an L=2 planar axis. The effects of vacuum magnetic configurations, pressure profiles and the vertical field control method are studied. The equilibrium beta limit with consistent bootstrap current is quite sensitive to the magnetic axis location for finite beta, compared with the currentless cases. For a vacuum configuration with the magnetic axis shifted inwards in the torus, even in the high beta regimes, the bootstrap current flows to increase the rotational transform, leading to an increase in the equilibrium beta limit. On the contrary, for a vacuum configuration with the magnetic axis shifted outwards in the torus, even in the low beta regimes, the bootstrap current flows so as to reduce the rotational transform; therefore, there is an acceleration of the Shafranov shift increase as beta increases, leading to a decrease in the equilibrium beta limit. The pressure profiles and vertical field control methods influence the equilibrium beta limit through the location of the magnetic axis for finite beta. These characteristics are independent of both device parameters, such as magnetic field strength, and device size in the low collisional regime. (author)
Bootstrap confidence intervals for three-way methods
Kiers, Henk A.L.
Results from exploratory three-way analysis techniques such as CANDECOMP/PARAFAC and Tucker3 analysis are usually presented without giving insight into uncertainties due to sampling. Here a bootstrap procedure is proposed that produces percentile intervals for all output parameters. Special
The Bootstrap, the Jackknife, and the Randomization Test: A Sampling Taxonomy.
Rodgers, J L
1999-10-01
A simple sampling taxonomy is defined that shows the differences between and relationships among the bootstrap, the jackknife, and the randomization test. Each method has as its goal the creation of an empirical sampling distribution that can be used to test statistical hypotheses, estimate standard errors, and/or create confidence intervals. Distinctions between the methods can be made based on the sampling approach (with replacement versus without replacement) and the sample size (replacing the whole original sample versus replacing a subset of the original sample). The taxonomy is useful for teaching the goals and purposes of resampling schemes. An extension of the taxonomy implies other possible resampling approaches that have not previously been considered. Univariate and multivariate examples are presented.
Modality specificity and integration in working memory: Insights from visuospatial bootstrapping.
Allen, Richard J; Havelka, Jelena; Falcon, Thomas; Evans, Sally; Darling, Stephen
2015-05-01
The question of how meaningful associations between verbal and spatial information might be utilized to facilitate working memory performance is potentially highly instructive for models of memory function. The present study explored how separable processing capacities within specialized domains might each contribute to this, by examining the disruptive impacts of simple verbal and spatial concurrent tasks on young adults' recall of visually presented digit sequences encountered either in a single location or within a meaningful spatial "keypad" configuration. The previously observed advantage for recall in the latter condition (the "visuospatial bootstrapping effect") consistently emerged across 3 experiments, indicating use of familiar spatial information in boosting verbal memory. The magnitude of this effect interacted with concurrent activity; articulatory suppression during encoding disrupted recall to a greater extent when digits were presented in single locations (Experiment 1), while spatial tapping during encoding had a larger impact on the keypad condition and abolished the visuospatial bootstrapping advantage (Experiment 2). When spatial tapping was performed during recall (Experiment 3), no task by display interaction was observed. Outcomes are discussed within the context of the multicomponent model of working memory, with a particular emphasis on cross-domain storage in the episodic buffer (Baddeley, 2000). (c) 2015 APA, all rights reserved).
Carnegie, Nicole Bohme
2011-04-15
The incidence of new infections is a key measure of the status of the HIV epidemic, but accurate measurement of incidence is often constrained by limited data. Karon et al. (Statist. Med. 2008; 27:4617–4633) developed a model to estimate the incidence of HIV infection from surveillance data with biologic testing for recent infection for newly diagnosed cases. This method has been implemented by public health departments across the United States and is behind the new national incidence estimates, which are about 40 per cent higher than previous estimates. We show that the delta method approximation given for the variance of the estimator is incomplete, leading to an inflated variance estimate. This contributes to the generation of overly conservative confidence intervals, potentially obscuring important differences between populations. We demonstrate via simulation that an innovative model-based bootstrap method using the specified model for the infection and surveillance process improves confidence interval coverage and adjusts for the bias in the point estimate. Confidence interval coverage is about 94–97 per cent after correction, compared with 96–99 per cent before. The simulated bias in the estimate of incidence ranges from −6.3 to +14.6 per cent under the original model but is consistently under 1 per cent after correction by the model-based bootstrap. In an application to data from King County, Washington in 2007 we observe correction of 7.2 per cent relative bias in the incidence estimate and a 66 per cent reduction in the width of the 95 per cent confidence interval using this method. We provide open-source software to implement the method that can also be extended for alternate models.
Directory of Open Access Journals (Sweden)
Mabaso Musawenkosi LH
2007-09-01
Full Text Available Abstract Background Several malaria risk maps have been developed in recent years, many from the prevalence of infection data collated by the MARA (Mapping Malaria Risk in Africa project, and using various environmental data sets as predictors. Variable selection is a major obstacle due to analytical problems caused by over-fitting, confounding and non-independence in the data. Testing and comparing every combination of explanatory variables in a Bayesian spatial framework remains unfeasible for most researchers. The aim of this study was to develop a malaria risk map using a systematic and practicable variable selection process for spatial analysis and mapping of historical malaria risk in Botswana. Results Of 50 potential explanatory variables from eight environmental data themes, 42 were significantly associated with malaria prevalence in univariate logistic regression and were ranked by the Akaike Information Criterion. Those correlated with higher-ranking relatives of the same environmental theme, were temporarily excluded. The remaining 14 candidates were ranked by selection frequency after running automated step-wise selection procedures on 1000 bootstrap samples drawn from the data. A non-spatial multiple-variable model was developed through step-wise inclusion in order of selection frequency. Previously excluded variables were then re-evaluated for inclusion, using further step-wise bootstrap procedures, resulting in the exclusion of another variable. Finally a Bayesian geo-statistical model using Markov Chain Monte Carlo simulation was fitted to the data, resulting in a final model of three predictor variables, namely summer rainfall, mean annual temperature and altitude. Each was independently and significantly associated with malaria prevalence after allowing for spatial correlation. This model was used to predict malaria prevalence at unobserved locations, producing a smooth risk map for the whole country. Conclusion We have
International Nuclear Information System (INIS)
Lins, Isis Didier; Droguett, Enrique López; Moura, Márcio das Chagas; Zio, Enrico; Jacinto, Carlos Magno
2015-01-01
Data-driven learning methods for predicting the evolution of the degradation processes affecting equipment are becoming increasingly attractive in reliability and prognostics applications. Among these, we consider here Support Vector Regression (SVR), which has provided promising results in various applications. Nevertheless, the predictions provided by SVR are point estimates whereas in order to take better informed decisions, an uncertainty assessment should be also carried out. For this, we apply bootstrap to SVR so as to obtain confidence and prediction intervals, without having to make any assumption about probability distributions and with good performance even when only a small data set is available. The bootstrapped SVR is first verified on Monte Carlo experiments and then is applied to a real case study concerning the prediction of degradation of a component from the offshore oil industry. The results obtained indicate that the bootstrapped SVR is a promising tool for providing reliable point and interval estimates, which can inform maintenance-related decisions on degrading components. - Highlights: • Bootstrap (pairs/residuals) and SVR are used as an uncertainty analysis framework. • Numerical experiments are performed to assess accuracy and coverage properties. • More bootstrap replications does not significantly improve performance. • Degradation of equipment of offshore oil wells is estimated by bootstrapped SVR. • Estimates about the scale growth rate can support maintenance-related decisions
Dwivedi, Alok Kumar; Mallawaarachchi, Indika; Alvarado, Luis A
2017-06-30
Experimental studies in biomedical research frequently pose analytical problems related to small sample size. In such studies, there are conflicting findings regarding the choice of parametric and nonparametric analysis, especially with non-normal data. In such instances, some methodologists questioned the validity of parametric tests and suggested nonparametric tests. In contrast, other methodologists found nonparametric tests to be too conservative and less powerful and thus preferred using parametric tests. Some researchers have recommended using a bootstrap test; however, this method also has small sample size limitation. We used a pooled method in nonparametric bootstrap test that may overcome the problem related with small samples in hypothesis testing. The present study compared nonparametric bootstrap test with pooled resampling method corresponding to parametric, nonparametric, and permutation tests through extensive simulations under various conditions and using real data examples. The nonparametric pooled bootstrap t-test provided equal or greater power for comparing two means as compared with unpaired t-test, Welch t-test, Wilcoxon rank sum test, and permutation test while maintaining type I error probability for any conditions except for Cauchy and extreme variable lognormal distributions. In such cases, we suggest using an exact Wilcoxon rank sum test. Nonparametric bootstrap paired t-test also provided better performance than other alternatives. Nonparametric bootstrap test provided benefit over exact Kruskal-Wallis test. We suggest using nonparametric bootstrap test with pooled resampling method for comparing paired or unpaired means and for validating the one way analysis of variance test results for non-normal data in small sample size studies. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Genetic divergence among cupuaçu accessions by multiscale bootstrap resampling
Directory of Open Access Journals (Sweden)
Vinicius Silva dos Santos
2015-06-01
Full Text Available This study aimed at investigating the genetic divergence of eighteen accessions of cupuaçu trees based on fruit morphometric traits and comparing usual methods of cluster analysis with the proposed multiscale bootstrap resampling methodology. The data were obtained from an experiment conducted in Tomé-Açu city (PA, Brazil, arranged in a completely randomized design with eighteen cupuaçu accessions and 10 repetitions, from 2004 to 2011. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction (REML/BLUP methodology. The predicted breeding values were used in the study on genetic divergence through Unweighted Pair Cluster Method with Arithmetic Mean (UPGMA hierarchical clustering and Tocher’s optimization method based on standardized Euclidean distance. Clustering consistency and optimal number of clusters in the UPGMA method were verified by the cophenetic correlation coefficient (CCC and Mojena’s criterion, respectively, besides the multiscale bootstrap resampling technique. The use of the clustering UPGMA method in situations with and without multiscale bootstrap resulted in four and five clusters, respectively, while the Tocher’s method resulted in seven clusters. The multiscale bootstrap resampling technique proves to be efficient to assess the consistency of clustering in hierarchical methods and, consequently, the optimal number of clusters.
arXiv The S-matrix Bootstrap I: QFT in AdS
Paulos, Miguel F.; Toledo, Jonathan; van Rees, Balt C.; Vieira, Pedro
2017-11-21
We propose a strategy to study massive Quantum Field Theory (QFT) using conformal bootstrap methods. The idea is to consider QFT in hyperbolic space and study correlation functions of its boundary operators. We show that these are solutions of the crossing equations in one lower dimension. By sending the curvature radius of the background hyperbolic space to infinity we expect to recover flat-space physics. We explain that this regime corresponds to large scaling dimensions of the boundary operators, and discuss how to obtain the flat-space scattering amplitudes from the corresponding limit of the boundary correlators. We implement this strategy to obtain universal bounds on the strength of cubic couplings in 2D flat-space QFTs using 1D conformal bootstrap techniques. Our numerical results match precisely the analytic bounds obtained in our companion paper using S-matrix bootstrap techniques.
Analytic description of tokamak equilibrium sustained by high fraction bootstrap current
International Nuclear Information System (INIS)
Shi Bingren
2002-01-01
Recently, to save the current drive power and to obtain more favorable confinement merit for tokamak reactor, large faction bootstrap current sustained equilibrium has attracted great interests both theoretically and experimentally. An powerful expanding technique and the tokamak ordering are used to expand the Grad-Shafranov equation to obtain a series of ordinary differential equations which allow for different sets of input parameters. The fully bootstrap current sustained tokamak equilibria are then solved analytically
Marill, Keith A; Chang, Yuchiao; Wong, Kim F; Friedman, Ari B
2017-08-01
Objectives Assessing high-sensitivity tests for mortal illness is crucial in emergency and critical care medicine. Estimating the 95% confidence interval (CI) of the likelihood ratio (LR) can be challenging when sample sensitivity is 100%. We aimed to develop, compare, and automate a bootstrapping method to estimate the negative LR CI when sample sensitivity is 100%. Methods The lowest population sensitivity that is most likely to yield sample sensitivity 100% is located using the binomial distribution. Random binomial samples generated using this population sensitivity are then used in the LR bootstrap. A free R program, "bootLR," automates the process. Extensive simulations were performed to determine how often the LR bootstrap and comparator method 95% CIs cover the true population negative LR value. Finally, the 95% CI was compared for theoretical sample sizes and sensitivities approaching and including 100% using: (1) a technique of individual extremes, (2) SAS software based on the technique of Gart and Nam, (3) the Score CI (as implemented in the StatXact, SAS, and R PropCI package), and (4) the bootstrapping technique. Results The bootstrapping approach demonstrates appropriate coverage of the nominal 95% CI over a spectrum of populations and sample sizes. Considering a study of sample size 200 with 100 patients with disease, and specificity 60%, the lowest population sensitivity with median sample sensitivity 100% is 99.31%. When all 100 patients with disease test positive, the negative LR 95% CIs are: individual extremes technique (0,0.073), StatXact (0,0.064), SAS Score method (0,0.057), R PropCI (0,0.062), and bootstrap (0,0.048). Similar trends were observed for other sample sizes. Conclusions When study samples demonstrate 100% sensitivity, available methods may yield inappropriately wide negative LR CIs. An alternative bootstrapping approach and accompanying free open-source R package were developed to yield realistic estimates easily. This
A Mellin space approach to the conformal bootstrap
Energy Technology Data Exchange (ETDEWEB)
Gopakumar, Rajesh [International Centre for Theoretical Sciences (ICTS-TIFR),Survey No. 151, Shivakote, Hesaraghatta Hobli, Bangalore North 560 089 (India); Kaviraj, Apratim [Centre for High Energy Physics, Indian Institute of Science,C.V. Raman Avenue, Bangalore 560012 (India); Sen, Kallol [Centre for High Energy Physics, Indian Institute of Science,C.V. Raman Avenue, Bangalore 560012 (India); Kavli Institute for the Physics and Mathematics of the Universe (WPI),The University of Tokyo Institutes for Advanced Study, Kashiwa, Chiba 277-8583 (Japan); Sinha, Aninda [Centre for High Energy Physics, Indian Institute of Science,C.V. Raman Avenue, Bangalore 560012 (India)
2017-05-05
We describe in more detail our approach to the conformal bootstrap which uses the Mellin representation of CFT{sub d} four point functions and expands them in terms of crossing symmetric combinations of AdS{sub d+1} Witten exchange functions. We consider arbitrary external scalar operators and set up the conditions for consistency with the operator product expansion. Namely, we demand cancellation of spurious powers (of the cross ratios, in position space) which translate into spurious poles in Mellin space. We discuss two contexts in which we can immediately apply this method by imposing the simplest set of constraint equations. The first is the epsilon expansion. We mostly focus on the Wilson-Fisher fixed point as studied in an epsilon expansion about d=4. We reproduce Feynman diagram results for operator dimensions to O(ϵ{sup 3}) rather straightforwardly. This approach also yields new analytic predictions for OPE coefficients to the same order which fit nicely with recent numerical estimates for the Ising model (at ϵ=1). We will also mention some leading order results for scalar theories near three and six dimensions. The second context is a large spin expansion, in any dimension, where we are able to reproduce and go a bit beyond some of the results recently obtained using the (double) light cone expansion. We also have a preliminary discussion about numerical implementation of the above bootstrap scheme in the absence of a small parameter.
Energy Technology Data Exchange (ETDEWEB)
Gonzalez-Manteiga, W.; Prada-Sanchez, J.M.; Fiestras-Janeiro, M.G.; Garcia-Jurado, I. (Universidad de Santiago de Compostela, Santiago de Compostela (Spain). Dept. de Estadistica e Investigacion Operativa)
1990-11-01
A statistical study of the dependence between various critical fusion temperatures of a certain kind of coal and its chemical components is carried out. As well as using classical dependence techniques (multiple, stepwise and PLS regression, principal components, canonical correlation, etc.) together with the corresponding inference on the parameters of interest, non-parametric regression and bootstrap inference are also performed. 11 refs., 3 figs., 8 tabs.
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 items to a partner using repeated non-linguistic vocalization, repeated gesture, or repeated non-linguistic vocalization plus gesture (but without using their existing language system). Gesture proved more effective (measured by communication success) and more efficient (measured by the time taken to communicate) than non-linguistic vocalization across a range of item categories (emotion, object, and action). Combining gesture and vocalization did not improve performance beyond gesture alone. We experimentally demonstrate that gesture is a more effective means of bootstrapping a human communication system. We argue that gesture outperforms non-linguistic vocalization because it lends itself more naturally to the production of motivated signs. © 2013 Cognitive Science Society, Inc.
Czech Academy of Sciences Publication Activity Database
Kyselý, Jan
2010-01-01
Roč. 101, 3-4 (2010), s. 345-361 ISSN 0177-798X R&D Projects: GA AV ČR KJB300420801 Institutional research plan: CEZ:AV0Z30420517 Keywords : bootstrap * extreme value analysis * confidence intervals * heavy-tailed distributions * precipitation amounts Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.684, year: 2010
Explorations in statistics: the log transformation.
Curran-Everett, Douglas
2018-06-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This thirteenth installment of Explorations in Statistics explores the log transformation, an established technique that rescales the actual observations from an experiment so that the assumptions of some statistical analysis are better met. A general assumption in statistics is that the variability of some response Y is homogeneous across groups or across some predictor variable X. If the variability-the standard deviation-varies in rough proportion to the mean value of Y, a log transformation can equalize the standard deviations. Moreover, if the actual observations from an experiment conform to a skewed distribution, then a log transformation can make the theoretical distribution of the sample mean more consistent with a normal distribution. This is important: the results of a one-sample t test are meaningful only if the theoretical distribution of the sample mean is roughly normal. If we log-transform our observations, then we want to confirm the transformation was useful. We can do this if we use the Box-Cox method, if we bootstrap the sample mean and the statistic t itself, and if we assess the residual plots from the statistical model of the actual and transformed sample observations.
Im, Subin; Min, Soonhong
2013-04-01
Exploratory factor analyses of the Kirton Adaption-Innovation Inventory (KAI), which serves to measure individual cognitive styles, generally indicate three factors: sufficiency of originality, efficiency, and rule/group conformity. In contrast, a 2005 study by Im and Hu using confirmatory factor analysis supported a four-factor structure, dividing the sufficiency of originality dimension into two subdimensions, idea generation and preference for change. This study extends Im and Hu's (2005) study of a derived version of the KAI by providing additional evidence of the four-factor structure. Specifically, the authors test the robustness of the parameter estimates to the violation of normality assumptions in the sample using bootstrap methods. A bias-corrected confidence interval bootstrapping procedure conducted among a sample of 356 participants--members of the Arkansas Household Research Panel, with middle SES and average age of 55.6 yr. (SD = 13.9)--showed that the four-factor model with two subdimensions of sufficiency of originality fits the data significantly better than the three-factor model in non-normality conditions.
Combined RF current drive and bootstrap current in tokamaks
International Nuclear Information System (INIS)
Schultz, S. D.; Bers, A.; Ram, A. K.
1999-01-01
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
A proof of fulfillment of the strong bootstrap condition
International Nuclear Information System (INIS)
Fadin, V.S.; Papa, A.
2002-01-01
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. (author)
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.
Mobile first design : using Bootstrap
Bhusal, Bipin
2017-01-01
The aim of this project was to design and build a website for a company based in Australia. The business offers remedial massage therapy to its clients. It is a small business which works on the basis of calls and message reservation. The business currently has a temporary website designed with Wix, a cloud-based web development platform. The new website was built with responsive design using Bootstrap. This website was intended for the customers using mobile internet browsers. This design is...
How to Bootstrap Anonymous Communication
DEFF Research Database (Denmark)
Jakobsen, Sune K.; Orlandi, Claudio
2015-01-01
formal study in this direction. To solve this problem, we introduce the concept of anonymous steganography: think of a leaker Lea who wants to leak a large document to Joe the journalist. Using anonymous steganography Lea can embed this document in innocent looking communication on some popular website...... anonymous steganography, { A construction showing that anonymous steganography is possible (which uses recent results in circuits obfuscation), { A lower bound on the number of bits which are needed to bootstrap anonymous communication....
How to Bootstrap Anonymous Communication
DEFF Research Database (Denmark)
Jakobsen, Sune K.; Orlandi, Claudio
2015-01-01
formal study in this direction. To solve this problem, we introduce the concept of anonymous steganography: think of a leaker Lea who wants to leak a large document to Joe the journalist. Using anonymous steganography Lea can embed this document in innocent looking communication on some popular website...... defining anonymous steganography, - A construction showing that anonymous steganography is possible (which uses recent results in circuits obfuscation), - A lower bound on the number of bits which are needed to bootstrap anonymous communication....
Sampling, Probability Models and Statistical Reasoning Statistical
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 5. Sampling, Probability Models and Statistical Reasoning Statistical Inference. Mohan Delampady V R Padmawar. General Article Volume 1 Issue 5 May 1996 pp 49-58 ...
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.
Introduction of Bootstrap Current Reduction in the Stellarator Optimization Using the Algorithm DAB
International Nuclear Information System (INIS)
Castejón, F.; Gómez-Iglesias, A.; Velasco, J. L.
2015-01-01
This work is devoted to introduce new optimization criterion in the DAB (Distributed Asynchronous Bees) code. With this new criterion, we have now in DAB the equilibrium and Mercier stability criteria, the minimization of Bxgrad(B) criterion, which ensures the reduction of neoclassical transport and the improvement of the confinement of fast particles, and the reduction of bootstrap current. We have started from a neoclassically optimised configuration of the helias type and imposed the reduction of bootstrap current. The obtained configuration only presents a modest reduction of total bootstrap current, but the local current density is reduced along the minor radii. Further investigations are developed to understand the reason of this modest improvement.
Study of the separate exposure method for bootstrap sensitometry on X-ray cine film
International Nuclear Information System (INIS)
Matsuda, Eiji; Sanada, Taizo; Hitomi, Go; Kakuba, Koki; Kangai, Yoshiharu; Ishii, Koushi
1997-01-01
We developed a new method for bootstrap sensitometry that obtained the characteristic curve from a wide range, with a smaller number of aluminum steps than the conventional bootstrap method. In this method, the density-density curve was obtained from standard and multiplied exposures to the aluminum step wedge and used for bootstrap manipulation. The curve was acquired from two regions separated and added together, e.g., lower and higher photographic density regions. In this study, we evaluated the usefulness of a new cinefluorography method in comparison with N.D. filter sensitometry. The shape of the characteristic curve and the gradient curve obtained with the new method were highly similar to that obtained with N.D. filter sensitometry. Also, the average gradient obtained with the new bootstrap sensitometry method was not significantly different from that obtained by the N.D. filter method. The study revealed that the reliability of the characteristic curve was improved by increasing the measured value used to calculate the density-density curve. This new method was useful for obtaining a characteristic curve with a sufficient density range, and the results suggested that this new method could be applied to specific systems to which the conventional bootstrap method is not applicable. (author)
Boundary and interface CFTs from the conformal bootstrap
Energy Technology Data Exchange (ETDEWEB)
Gliozzi, Ferdinando [Dipartimento di Fisica, Università di Torino,Via P. Giuria 1 I-10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare - sezione di Torino,Via P. Giuria 1 I-10125 Torino (Italy); Liendo, Pedro [IMIP, Humboldt-Universität zu Berlin, IRIS Adelershof,Zum Großen Windkanal 6, 12489 Berlin (Germany); Meineri, Marco [Scuola Normale Superiore,Piazza dei Cavalieri 7 I-56126 Pisa (Italy); Istituto Nazionale di Fisica Nucleare - sezione di Pisa,Largo B. Pontecorvo, 3, 56127 Pisa (Italy); Rago, Antonio [Centre for Mathematical Sciences, Plymouth University,Drake Circus, Plymouth, PL4 8AA (United Kingdom)
2015-05-07
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-ϵ dimensions the renormalization group interface between the O(N) model and the free theory and check numerically the results in 3d.
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…
Stable equilibria for bootstrap-current-driven low aspect ratio tokamaks
International Nuclear Information System (INIS)
Miller, R.L.; Lin-Liu, Y.R.; Turnbull, A.D.; Chan, V.S.; Pearlstein, L.D.; Sauter, O.; Villard, L.
1997-01-01
Low aspect ratio tokamaks (LATs) can potentially provide a high ratio of plasma pressure to magnetic pressure β and high plasma current I at a modest size. This opens up the possibility of a high-power density compact fusion power plant. For the concept to be economically feasible, bootstrap current must be a major component of the plasma current, which requires operating at high β p . A high value of the Troyon factor β N and strong shaping is required to allow simultaneous operation at a high-β and high bootstrap fraction. Ideal magnetohydrodynamic stability of a range of equilibria at aspect ratio 1.4 is systematically explored by varying the pressure profile and shape. The pressure and current profiles are constrained in such a way as to assure complete bootstrap current alignment. Both β N and β are defined in terms of the vacuum toroidal field. Equilibria with β N ≥8 and β∼35%endash 55% exist that are stable to n=∞ ballooning modes. The highest β case is shown to be stable to n=0,1,2,3 kink modes with a conducting wall. copyright 1997 American Institute of Physics
International Nuclear Information System (INIS)
Li, Ke; Lin, Boqiang
2017-01-01
This paper proposes a total-factor energy consumption performance index (TEPI) for measuring China's energy efficiency across 30 provinces during the period 1997 to 2012. The TEPI is derived by solving an improved non-radial data envelopment analysis (DEA) model, which is based on an energy distance function. The production possibility set is constructed by combining the super-efficiency and sequential DEA models to avoid “discriminating power problem” and “technical regress”. In order to explore the impacts of technological progress on TEPI and perform statistical inferences on the results, a two-stage double bootstrap approach is adopted. The important findings are that China's energy technology innovation produces a negative effect on TEPI, while technology import and imitative innovation produce positive effects on TEPI. Thus, the main contribution of TEPI improvement is technology import. These conclusions imply that technology import especially foreign direct investment (FDI) is important for imitative innovation and can improve China's energy efficiency. In the long run, as the technical level of China approaches to the frontier, energy technology innovation and its wide adoption become a sustained way to improve energy efficiency. Therefore, it is urgent for China to introduce measures such as technology translation and spillover policies as well as energy pricing reforms to support energy technology innovation. - Highlights: • A total-factor energy consumption performance index (TEPI) is introduced. • Three types of technological progress have various effects on TEPI. • FDI is the main contributor of TEPI improvement. • An improved DEA calculation method is introduced. • A two-stage double-bootstrap non-radial DEA model is used.
More N =4 superconformal bootstrap
Beem, Christopher; Rastelli, Leonardo; van Rees, Balt C.
2017-08-01
In this long overdue second installment, we continue to develop the conformal bootstrap program for N =4 superconformal field theories (SCFTs) in four dimensions via an analysis of the correlation function of four stress-tensor supermultiplets. We review analytic results for this correlator and make contact with the SCFT/chiral algebra correspondence of Beem et al. [Commun. Math. Phys. 336, 1359 (2015), 10.1007/s00220-014-2272-x]. We demonstrate that the constraints of unitarity and crossing symmetry require the central charge c to be greater than or equal to 3 /4 in any interacting N =4 SCFT. We apply numerical bootstrap methods to derive upper bounds on scaling dimensions and operator product expansion coefficients for several low-lying, unprotected operators as a function of the central charge. We interpret our bounds in the context of N =4 super Yang-Mills theories, formulating a series of conjectures regarding the embedding of the conformal manifold—parametrized by the complexified gauge coupling—into the space of scaling dimensions and operator product expansion coefficients. Our conjectures assign a distinguished role to points on the conformal manifold that are self-dual under a subgroup of the S -duality group. This paper contains a more detailed exposition of a number of results previously reported in Beem et al. [Phys. Rev. Lett. 111, 071601 (2013), 10.1103/PhysRevLett.111.071601] in addition to new results.
Statistical Model of Extreme Shear
DEFF Research Database (Denmark)
Larsen, Gunner Chr.; Hansen, Kurt Schaldemose
2004-01-01
In order to continue cost-optimisation of modern large wind turbines, it is important to continously increase the knowledge on wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... by a model that, on a statistically consistent basis, describe the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of high-sampled full-scale time series measurements...... are consistent, given the inevitabel uncertainties associated with model as well as with the extreme value data analysis. Keywords: Statistical model, extreme wind conditions, statistical analysis, turbulence, wind loading, statistical analysis, turbulence, wind loading, wind shear, wind turbines....
Divergence-based tests for model diagnostic
Czech Academy of Sciences Publication Activity Database
Hobza, Tomáš; Esteban, M. D.; Morales, D.; Marhuenda, Y.
2008-01-01
Roč. 78, č. 13 (2008), s. 1702-1710 ISSN 0167-7152 R&D Projects: GA MŠk 1M0572 Grant - others:Instituto Nacional de Estadistica (ES) MTM2006-05693 Institutional research plan: CEZ:AV0Z10750506 Keywords : goodness of fit * devergence statistics * GLM * model checking * bootstrap Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.445, year: 2008 http://library.utia.cas.cz/separaty/2008/SI/hobza-divergence-based%20tests%20for%20model%20diagnostic.pdf
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…
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.
Bootstrap bound for conformal multi-flavor QCD on lattice
Energy Technology Data Exchange (ETDEWEB)
Nakayama, Yu [Department of Physics, Rikkyo University,Toshima, Tokyo 171-8501 (Japan); Kavli Institute for the Physics and Mathematics of the Universe (WPI), University of Tokyo,5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8583 (Japan)
2016-07-08
The recent work by Iha et al. shows an upper bound on mass anomalous dimension γ{sub m} of multi-flavor massless QCD at the renormalization group fixed point from the conformal bootstrap in SU(N{sub F}){sub 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{sub f}){sub L}×SU(N{sub f}){sub R} symmetric conformal field theories. For N{sub f}=8, our bound implies γ{sub m}<1.31 to avoid dangerously irrelevant operators that are not compatible with the lattice symmetry.
Al-Mudhafar, W. J.
2013-12-01
Precisely prediction of rock facies leads to adequate reservoir characterization by improving the porosity-permeability relationships to estimate the properties in non-cored intervals. It also helps to accurately identify the spatial facies distribution to perform an accurate reservoir model for optimal future reservoir performance. In this paper, the facies estimation has been done through Multinomial logistic regression (MLR) with respect to the well logs and core data in a well in upper sandstone formation of South Rumaila oil field. The entire independent variables are gamma rays, formation density, water saturation, shale volume, log porosity, core porosity, and core permeability. Firstly, Robust Sequential Imputation Algorithm has been considered to impute the missing data. This algorithm starts from a complete subset of the dataset and estimates sequentially the missing values in an incomplete observation by minimizing the determinant of the covariance of the augmented data matrix. Then, the observation is added to the complete data matrix and the algorithm continues with the next observation with missing values. The MLR has been chosen to estimate the maximum likelihood and minimize the standard error for the nonlinear relationships between facies & core and log data. The MLR is used to predict the probabilities of the different possible facies given each independent variable by constructing a linear predictor function having a set of weights that are linearly combined with the independent variables by using a dot product. Beta distribution of facies has been considered as prior knowledge and the resulted predicted probability (posterior) has been estimated from MLR based on Baye's theorem that represents the relationship between predicted probability (posterior) with the conditional probability and the prior knowledge. To assess the statistical accuracy of the model, the bootstrap should be carried out to estimate extra-sample prediction error by randomly
El-Showk, Sheer; Poland, David; Rychkov, Slava; Simmons-Duffin, David; Vichi, Alessandro
2014-01-01
We use the conformal bootstrap to perform a precision study of the operator spectrum of the critical 3d Ising model. We conjecture that the 3d Ising spectrum minimizes the central charge c in the space of unitary solutions to crossing symmetry. Because extremal solutions to crossing symmetry are uniquely determined, we are able to precisely reconstruct the first several Z2-even operator dimensions and their OPE coefficients. We observe that a sharp transition in the operator spectrum occurs at the 3d Ising dimension Delta_sigma=0.518154(15), and find strong numerical evidence that operators decouple from the spectrum as one approaches the 3d Ising point. We compare this behavior to the analogous situation in 2d, where the disappearance of operators can be understood in terms of degenerate Virasoro representations.
Directory of Open Access Journals (Sweden)
Kleber Rogério Moreira Prado
2013-06-01
Full Text Available Current essay forwards a biodegradation model of a dye, used in the textile industry, based on a neural network propped by bootstrap remodeling. Bootstrapped neural network is set to generate estimates that are close to results obtained in an intrinsic experience in which a chemical process is applied. Pseudomonas oleovorans was used in the biodegradation of reactive Black 5. Results show a brief comparison between the information estimated by the proposed approach and the experimental data, with a coefficient of correlation between real and predicted values for a more than 0.99 biodegradation rate. Dye concentration and the solution’s pH failed to interfere in biodegradation index rates. A value above 90% of dye biodegradation was achieved between 1.000 and 1.841 mL 10 mL-1 of microorganism concentration and between 1.000 and 2.000 g 100 mL-1 of glucose concentration within the experimental conditions under analysis.
Phonetic diversity, statistical learning, and acquisition of phonology.
Pierrehumbert, Janet B
2003-01-01
In learning to perceive and produce speech, children master complex language-specific patterns. Daunting language-specific variation is found both in the segmental domain and in the domain of prosody and intonation. This article reviews the challenges posed by results in phonetic typology and sociolinguistics for the theory of language acquisition. It argues that categories are initiated bottom-up from statistical modes in use of the phonetic space, and sketches how exemplar theory can be used to model the updating of categories once they are initiated. It also argues that bottom-up initiation of categories is successful thanks to the perception-production loop operating in the speech community. The behavior of this loop means that the superficial statistical properties of speech available to the infant indirectly reflect the contrastiveness and discriminability of categories in the adult grammar. The article also argues that the developing system is refined using internal feedback from type statistics over the lexicon, once the lexicon is well-developed. The application of type statistics to a system initiated with surface statistics does not cause a fundamental reorganization of the system. Instead, it exploits confluences across levels of representation which characterize human language and make bootstrapping possible.
On the Consistency of Bootstrap Testing for a Parameter on the Boundary of the Parameter Space
DEFF Research Database (Denmark)
Cavaliere, Giuseppe; Nielsen, Heino Bohn; Rahbek, Anders
2017-01-01
It is well known that with a parameter on the boundary of the parameter space, such as in the classic cases of testing for a zero location parameter or no autoregressive conditional heteroskedasticity (ARCH) effects, the classic nonparametric bootstrap – based on unrestricted parameter estimates...... – leads to inconsistent testing. In contrast, we show here that for the two aforementioned cases, a nonparametric bootstrap test based on parameter estimates obtained under the null – referred to as ‘restricted bootstrap’ – is indeed consistent. While the restricted bootstrap is simple to implement...... in practice, novel theoretical arguments are required in order to establish consistency. In particular, since the bootstrap is analysed both under the null hypothesis and under the alternative, non-standard asymptotic expansions are required to deal with parameters on the boundary. Detailed proofs...
A statistical method to estimate low-energy hadronic cross sections
Balassa, Gábor; Kovács, Péter; Wolf, György
2018-02-01
In this article we propose a model based on the Statistical Bootstrap approach to estimate the cross sections of different hadronic reactions up to a few GeV in c.m.s. energy. The method is based on the idea, when two particles collide a so-called fireball is formed, which after a short time period decays statistically into a specific final state. To calculate the probabilities we use a phase space description extended with quark combinatorial factors and the possibility of more than one fireball formation. In a few simple cases the probability of a specific final state can be calculated analytically, where we show that the model is able to reproduce the ratios of the considered cross sections. We also show that the model is able to describe proton-antiproton annihilation at rest. In the latter case we used a numerical method to calculate the more complicated final state probabilities. Additionally, we examined the formation of strange and charmed mesons as well, where we used existing data to fit the relevant model parameters.
A simulation study on burning profile tailoring of steady state, high bootstrap current tokamaks
International Nuclear Information System (INIS)
Nakamura, Y.; Takei, N.; Tobita, K.; Sakamoto, Y.; Fujita, T.; Fukuyama, A.; Jardin, S.C.
2007-01-01
From the aspect of fusion burn control in steady state DEMO plant, the significant challenges are to maintain its high power burning state of ∝3-5 GW without burning instability, hitherto well-known as ''thermal stability'', and also to keep its desired burning profile relevant with internal transport barrier (ITB) that generates high bootstrap current. The paper presents a simulation modeling of the burning stability coupled with the self-ignited fusion burn and the structure-formation of the ITB. A self-consistent simulation, including a model for improved core energy confinement, has pointed out that in the high power fusion DEMO plant there is a close, nonlinear interplay between the fusion burnup and the current source of non-inductive, ITB-generated bootstrap current. Consequently, as much distinct from usual plasma controls under simulated burning conditions with lower power (<<1 GW), the selfignited fusion burn at a high power burning state of ∝3-5 GW becomes so strongly selforganized that any of external means except fuelling can not provide the effective control of the stable fusion burn.It is also demonstrated that externally applied, inductive current perturbations can be used to control both the location and strength of ITB in a fully noninductive tokamak discharge. We find that ITB structures formed with broad noninductive current sources such as LHCD are more readily controlled than those formed by localized sources such as ECCD. The physics of the inductive current is well known. Consequently, we believe that the controllability of the ITB is generic, and does not depend on the details of the transport model (as long as they can form an ITB for sufficiently reversed magnetic shear q-profile). Through this external control of the magnetic shear profile, we can maintain the ITB strength that is otherwise prone to deteriorate when the bootstrap current increases. These distinguishing capabilities of inductive current perturbation provide steady
Exclusion statistics and integrable models
International Nuclear Information System (INIS)
Mashkevich, S.
1998-01-01
The definition of exclusion statistics that was given by Haldane admits a 'statistical interaction' between distinguishable particles (multispecies statistics). For such statistics, thermodynamic quantities can be evaluated exactly; explicit expressions are presented here for cluster coefficients. Furthermore, single-species exclusion statistics is realized in one-dimensional integrable models of the Calogero-Sutherland type. The interesting questions of generalizing this correspondence to the higher-dimensional and the multispecies cases remain essentially open; however, our results provide some hints as to searches for the models in question
Bootstrapping O(N) vector models with four supercharges in 3≤d≤4
Energy Technology Data Exchange (ETDEWEB)
Chester, Shai M.; Iliesiu, Luca V.; Pufu, Silviu S.; Yacoby, Ran [Joseph Henry Laboratories, Princeton University,Washington Road, Princeton, NJ 08544 (United States)
2016-05-17
We analyze the conformal bootstrap constraints in theories with four supercharges and a global O(N)×U(1) flavor symmetry in 3≤d≤4 dimensions. In particular, we consider the 4-point function of O(N)-fundamental chiral operators Z{sub i} that have no chiral primary in the O(N)-singlet sector of their OPE. We find features in our numerical bounds that nearly coincide with the theory of N+1 chiral super-fields with superpotential W=X∑{sub i=1}{sup N}Z{sub i}{sup 2}, as well as general bounds on SCFTs where ∑{sub i=1}{sup N}Z{sub i}{sup 2} vanishes in the chiral ring.
On the definition of Pfirsch--Schlueter and bootstrap currents in toroidal systems
International Nuclear Information System (INIS)
Coronado, M.; Wobig, H.
1992-01-01
In the plasma physics literature there appear two different definitions of Pfirsch--Schlueter current. One of them is predominantly used in equilibrium calculations and satisfies the condition I T =0. The other definition appears commonly in transport calculations and requires that the surface average of the dot product of the Pfirsch--Schlueter current density with the magnetic field vanish, i.e., left-angle J PS ·B right-angle=0. The difference between the definitions is a surface function. Within the framework of the moment equation approach, the total parallel current is completely determined through a surface average of Ohm's law; thus different definitions of Pfirsch--Schlueter current imply different expressions for the bootstrap current. Understanding the different implications of these two definitions is of particular importance when designing toroidal devices with minimized Pfirsch--Schlueter current or studying tokamaks with optimized bootstrap current. In this paper the definitions of Pfirsch--Schlueter and bootstrap current, as well as the expressions for the corresponding Pfirsch--Schlueter diffusion flux, are analyzed and discussed for the case of axisymmetric and nonaxisymmetric plasmas. Although in cases like a current-free stellarator or a large-aspect-ratio tokamak both definitions are equivalent, they are in general different, and in order to avoid misunderstandings it is therefore important to use only one. The most appropriate definition is I T =0. In this paper the equations for determining the bootstrap current within the framework of the fluid equations are also analyzed
Komachi, Mamoru; Kudo, Taku; Shimbo, Masashi; Matsumoto, Yuji
Bootstrapping has a tendency, called semantic drift, to select instances unrelated to the seed instances as the iteration proceeds. We demonstrate the semantic drift of Espresso-style bootstrapping has the same root as the topic drift of Kleinberg's HITS, using a simplified graph-based reformulation of bootstrapping. We confirm that two graph-based algorithms, the von Neumann kernels and the regularized Laplacian, can reduce the effect of semantic drift in the task of word sense disambiguation (WSD) on Senseval-3 English Lexical Sample Task. Proposed algorithms achieve superior performance to Espresso and previous graph-based WSD methods, even though the proposed algorithms have less parameters and are easy to calibrate.
Improved inference in the evaluation of mutual fund performance using panel bootstrap methods
Blake, David; Caulfield, Tristan; Ioannidis, Christos; Tonks, I P
2014-01-01
Two new methodologies are introduced to improve inference in the evaluation of mutual fund performance against benchmarks. First, the benchmark models are estimated using panel methods with both fund and time effects. Second, the non-normality of individual mutual fund returns is accounted for by using panel bootstrap methods. We also augment the standard benchmark factors with fund-specific characteristics, such as fund size. Using a dataset of UK equity mutual fund returns, we find that fun...
Statistical modelling with quantile functions
Gilchrist, Warren
2000-01-01
Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.Statistical Modelling with Quantile Functions adds a new dimension to the practice of stati...
A Statistical Programme Assignment Model
DEFF Research Database (Denmark)
Rosholm, Michael; Staghøj, Jonas; Svarer, Michael
When treatment effects of active labour market programmes are heterogeneous in an observable way across the population, the allocation of the unemployed into different programmes becomes a particularly important issue. In this paper, we present a statistical model designed to improve the present...... duration of unemployment spells may result if a statistical programme assignment model is introduced. We discuss several issues regarding the plementation of such a system, especially the interplay between the statistical model and case workers....
Statistical properties of four effect-size measures for mediation models.
Miočević, Milica; O'Rourke, Holly P; MacKinnon, David P; Brown, Hendricks C
2018-02-01
This project examined the performance of classical and Bayesian estimators of four effect size measures for the indirect effect in a single-mediator model and a two-mediator model. Compared to the proportion and ratio mediation effect sizes, standardized mediation effect-size measures were relatively unbiased and efficient in the single-mediator model and the two-mediator model. Percentile and bias-corrected bootstrap interval estimates of ab/s Y , and ab(s X )/s Y in the single-mediator model outperformed interval estimates of the proportion and ratio effect sizes in terms of power, Type I error rate, coverage, imbalance, and interval width. For the two-mediator model, standardized effect-size measures were superior to the proportion and ratio effect-size measures. Furthermore, it was found that Bayesian point and interval summaries of posterior distributions of standardized effect-size measures reduced excessive relative bias for certain parameter combinations. The standardized effect-size measures are the best effect-size measures for quantifying mediated effects.
Testing statistical hypotheses
Lehmann, E L
2005-01-01
The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760. E.L. Lehmann is Professor of Statistics Emeritus at the University of California, Berkeley. He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences, and the recipient of honorary degrees from the University of Leiden, The Netherlands and the University of Chicago. He is the author of Elements of Large-Sample Theory and (with George Casella) he is also the author of Theory of Point Estimat...
Banks, H T; Holm, Kathleen; Robbins, Danielle
2010-11-01
We computationally investigate two approaches for uncertainty quantification in inverse problems for nonlinear parameter dependent dynamical systems. We compare the bootstrapping and asymptotic theory approaches for problems involving data with several noise forms and levels. We consider both constant variance absolute error data and relative error which produces non-constant variance data in our parameter estimation formulations. We compare and contrast parameter estimates, standard errors, confidence intervals, and computational times for both bootstrapping and asymptotic theory methods.
Mattfeldt, Torsten
2011-04-01
Computer-intensive methods may be defined as data analytical procedures involving a huge number of highly repetitive computations. We mention resampling methods with replacement (bootstrap methods), resampling methods without replacement (randomization tests) and simulation methods. The resampling methods are based on simple and robust principles and are largely free from distributional assumptions. Bootstrap methods may be used to compute confidence intervals for a scalar model parameter and for summary statistics from replicated planar point patterns, and for significance tests. For some simple models of planar point processes, point patterns can be simulated by elementary Monte Carlo methods. The simulation of models with more complex interaction properties usually requires more advanced computing methods. In this context, we mention simulation of Gibbs processes with Markov chain Monte Carlo methods using the Metropolis-Hastings algorithm. An alternative to simulations on the basis of a parametric model consists of stochastic reconstruction methods. The basic ideas behind the methods are briefly reviewed and illustrated by simple worked examples in order to encourage novices in the field to use computer-intensive methods. © 2010 The Authors Journal of Microscopy © 2010 Royal Microscopical Society.
Quantum bootstrapping via compressed quantum Hamiltonian learning
International Nuclear Information System (INIS)
Wiebe, Nathan; Granade, Christopher; Cory, D G
2015-01-01
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)
Rodríguez-Álvarez, María Xosé; Roca-Pardiñas, Javier; Cadarso-Suárez, Carmen; Tahoces, Pablo G
2018-03-01
Prior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed. In this paper, we focus on an estimator for the covariate-specific receiver-operating characteristic curve based on direct regression modelling and nonparametric smoothing techniques. This approach defines the class of generalised additive models for the receiver-operating characteristic curve. The main aim of the paper is to offer new inferential procedures for testing the effect of covariates on the conditional receiver-operating characteristic curve within the above-mentioned class. Specifically, two different bootstrap-based tests are suggested to check (a) the possible effect of continuous covariates on the receiver-operating characteristic curve and (b) the presence of factor-by-curve interaction terms. The validity of the proposed bootstrap-based procedures is supported by simulations. To facilitate the application of these new procedures in practice, an R-package, known as npROCRegression, is provided and briefly described. Finally, data derived from a computer-aided diagnostic system for the automatic detection of tumour masses in breast cancer is analysed.
Towards bootstrapping QED{sub 3}
Energy Technology Data Exchange (ETDEWEB)
Chester, Shai M.; Pufu, Silviu S. [Joseph Henry Laboratories, Princeton University,Princeton, NJ 08544 (United States)
2016-08-02
We initiate the conformal bootstrap study of Quantum Electrodynamics in 2+1 space-time dimensions (QED{sub 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.
Energy Technology Data Exchange (ETDEWEB)
Castejón, F.; Gómez-Iglesias, A.; Velasco, J. L.
2015-07-01
This work is devoted to introduce new optimization criterion in the DAB (Distributed Asynchronous Bees) code. With this new criterion, we have now in DAB the equilibrium and Mercier stability criteria, the minimization of Bxgrad(B) criterion, which ensures the reduction of neoclassical transport and the improvement of the confinement of fast particles, and the reduction of bootstrap current. We have started from a neoclassically optimised configuration of the helias type and imposed the reduction of bootstrap current. The obtained configuration only presents a modest reduction of total bootstrap current, but the local current density is reduced along the minor radii. Further investigations are developed to understand the reason of this modest improvement.
Considerations on ECFH current drive and bootstrap current for W VII-X
International Nuclear Information System (INIS)
Gasparino, U.; Maassberg, H.
1988-01-01
Low shear is the characteristic of all proposed Wendelstein VII-X configurations. To avoid low harmonic rational numbers within the rotational transform profile, the current contribution to the rotational transform, Δt a α I/B, should be typically less than 10%. This leads to an upper limit of 50 kA (at B = 2.5 T) for the tolerable net toroidal current. A considerable net toroidal current (bootstrap current) is expected by neoclassical theory in the plateau and the low-collisionality regimes. Both radial transport as well as the bootstrap current densities depend sensitively on the magnetic configuration (see A. Montvai, this workshop). In case of an axisymmetric configuration with dimension and plasma parameters as predicted for the high- regime of WVII-X ( ∼ 5%), this current (∼ 0.5/1 MA) would dominate the rotational transform profile. This requires a reduction of magnitude of the bootstrap current to some % of the value of an equivalent tokamak. This reduction must act on the current profile itself and should not be merely obtained by having two channels of currents of different sign at different radii. Due to the possibility of controlling absorbed power and driven current profiles, electron cyclotron waves are a natural candidate for current profile control. Linear calculations show the possibility to drive a counteracting current with a profile similar to the bootstrap one. For ∼ 5% conditions, however, the optimium current drive efficiency (η ∼ 10 kA per MW) is far too low to make ECF-current drive suitable
Statistical Inference and Patterns of Inequality in the Global North
Moran, Timothy Patrick
2006-01-01
Cross-national inequality trends have historically been a crucial field of inquiry across the social sciences, and new methodological techniques of statistical inference have recently improved the ability to analyze these trends over time. This paper applies Monte Carlo, bootstrap inference methods to the income surveys of the Luxembourg Income…
Syntactic bootstrapping in children with Down syndrome: the impact of bilingualism.
Cleave, Patricia L; Kay-Raining Bird, Elizabeth; Trudeau, Natacha; Sutton, Ann
2014-01-01
The purpose of the study was to add to our knowledge of bilingual learning in children with Down syndrome (DS) using a syntactic bootstrapping task. Four groups of children and youth matched on non-verbal mental age participated. There were 14 bilingual participants with DS (DS-B, mean age 12;5), 12 monolingual participants with DS (DS-M, mean age 10;10), 9 bilingual typically developing children (TD-B; mean age 4;1) and 11 monolingual typically developing children (TD-M; mean age 4;1). The participants completed a computerized syntactic bootstrapping task involving unfamiliar nouns and verbs. The syntactic cues employed were a for the nouns and ing for the verbs. Performance was better on nouns than verbs. There was also a main effect for group. Follow-up t-tests revealed that there were no significant differences between the TD-M and TD-B or between the DS-M and DS-B groups. However, the DS-M group performed more poorly than the TD-M group with a large effect size. Analyses at the individual level revealed a similar pattern of results. There was evidence that Down syndrome impacted performance; there was no evidence that bilingualism negatively affected the syntactic bootstrapping skills of individuals with DS. These results from a dynamic language task are consistent with those of previous studies that used static or product measures. Thus, the results are consistent with the position that parents should be supported in their decision to provide bilingual input to their children with DS. Readers of this article will identify (1) research evidence regarding bilingual development in children with Down syndrome and (2) syntactic bootstrapping skills in monolingual and bilingual children who are typically developing or who have Down syndrome. Copyright © 2014 Elsevier Inc. All rights reserved.
A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates
Christian de Peretti; Carole Siani; Mario Cerrato
2010-01-01
This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.
The sound symbolism bootstrapping hypothesis for language acquisition and language evolution.
Imai, Mutsumi; Kita, Sotaro
2014-09-19
Sound symbolism is a non-arbitrary relationship between speech sounds and meaning. We review evidence that, contrary to the traditional view in linguistics, sound symbolism is an important design feature of language, which affects online processing of language, and most importantly, language acquisition. We propose the sound symbolism bootstrapping hypothesis, claiming that (i) pre-verbal infants are sensitive to sound symbolism, due to a biologically endowed ability to map and integrate multi-modal input, (ii) sound symbolism helps infants gain referential insight for speech sounds, (iii) sound symbolism helps infants and toddlers associate speech sounds with their referents to establish a lexical representation and (iv) sound symbolism helps toddlers learn words by allowing them to focus on referents embedded in a complex scene, alleviating Quine's problem. We further explore the possibility that sound symbolism is deeply related to language evolution, drawing the parallel between historical development of language across generations and ontogenetic development within individuals. Finally, we suggest that sound symbolism bootstrapping is a part of a more general phenomenon of bootstrapping by means of iconic representations, drawing on similarities and close behavioural links between sound symbolism and speech-accompanying iconic gesture. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Impurities in a non-axisymmetric plasma: Transport and effect on bootstrap current
Energy Technology Data Exchange (ETDEWEB)
Mollén, A., E-mail: albertm@chalmers.se [Department of Applied Physics, Chalmers University of Technology, Göteborg (Sweden); Max-Planck-Institut für Plasmaphysik, 17491 Greifswald (Germany); Landreman, M. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Smith, H. M.; Helander, P. [Max-Planck-Institut für Plasmaphysik, 17491 Greifswald (Germany); Braun, S. [Max-Planck-Institut für Plasmaphysik, 17491 Greifswald (Germany); German Aerospace Center, Institute of Engineering Thermodynamics, Pfaffenwaldring 38-40, D-70569 Stuttgart (Germany)
2015-11-15
Impurities cause radiation losses and plasma dilution, and in stellarator plasmas the neoclassical ambipolar radial electric field is often unfavorable for avoiding strong impurity peaking. In this work we use a new continuum drift-kinetic solver, the SFINCS code (the Stellarator Fokker-Planck Iterative Neoclassical Conservative Solver) [M. Landreman et al., Phys. Plasmas 21, 042503 (2014)] which employs the full linearized Fokker-Planck-Landau operator, to calculate neoclassical impurity transport coefficients for a Wendelstein 7-X (W7-X) magnetic configuration. We compare SFINCS calculations with theoretical asymptotes in the high collisionality limit. We observe and explain a 1/ν-scaling of the inter-species radial transport coefficient at low collisionality, arising due to the field term in the inter-species collision operator, and which is not found with simplified collision models even when momentum correction is applied. However, this type of scaling disappears if a radial electric field is present. We also use SFINCS to analyze how the impurity content affects the neoclassical impurity dynamics and the bootstrap current. We show that a change in plasma effective charge Z{sub eff} of order unity can affect the bootstrap current enough to cause a deviation in the divertor strike point locations.
Lee, Soojeong; Rajan, Sreeraman; Jeon, Gwanggil; Chang, Joon-Hyuk; Dajani, Hilmi R; Groza, Voicu Z
2017-06-01
Blood pressure (BP) is one of the most important vital indicators and plays a key role in determining the cardiovascular activity of patients. This paper proposes a hybrid approach consisting of nonparametric bootstrap (NPB) and machine learning techniques to obtain the characteristic ratios (CR) used in the blood pressure estimation algorithm to improve the accuracy of systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates and obtain confidence intervals (CI). The NPB technique is used to circumvent the requirement for large sample set for obtaining the CI. A mixture of Gaussian densities is assumed for the CRs and Gaussian mixture model (GMM) is chosen to estimate the SBP and DBP ratios. The K-means clustering technique is used to obtain the mixture order of the Gaussian densities. The proposed approach achieves grade "A" under British Society of Hypertension testing protocol and is superior to the conventional approach based on maximum amplitude algorithm (MAA) that uses fixed CR ratios. The proposed approach also yields a lower mean error (ME) and the standard deviation of the error (SDE) in the estimates when compared to the conventional MAA method. In addition, CIs obtained through the proposed hybrid approach are also narrower with a lower SDE. The proposed approach combining the NPB technique with the GMM provides a methodology to derive individualized characteristic ratio. The results exhibit that the proposed approach enhances the accuracy of SBP and DBP estimation and provides narrower confidence intervals for the estimates. Copyright © 2015 Elsevier Ltd. All rights reserved.
Contributions to sampling statistics
Conti, Pier; Ranalli, Maria
2014-01-01
This book contains a selection of the papers presented at the ITACOSM 2013 Conference, held in Milan in June 2013. ITACOSM is the bi-annual meeting of the Survey Sampling Group S2G of the Italian Statistical Society, intended as an international forum of scientific discussion on the developments of theory and application of survey sampling methodologies and applications in human and natural sciences. The book gathers research papers carefully selected from both invited and contributed sessions of the conference. The whole book appears to be a relevant contribution to various key aspects of sampling methodology and techniques; it deals with some hot topics in sampling theory, such as calibration, quantile-regression and multiple frame surveys, and with innovative methodologies in important topics of both sampling theory and applications. Contributions cut across current sampling methodologies such as interval estimation for complex samples, randomized responses, bootstrap, weighting, modeling, imputati...
DEFF Research Database (Denmark)
Hiller, Jochen; Genta, Gianfranco; Barbato, Giulio
2014-01-01
measurement processes, e.g., with tactile systems, also due to factors related to systematic errors, mainly caused by specific CT image characteristics. In this paper we propose a simulation-based framework for measurement uncertainty evaluation in dimensional CT using the bootstrap method. In a case study...... the problem concerning measurement uncertainties was addressed with bootstrap and successfully applied to ball-bar CT measurements. Results obtained enabled extension to more complex shapes such as actual industrial components as we show by tests on a hollow cylinder workpiece....
International Nuclear Information System (INIS)
Saarelma, S.; Kurki-Suonio, T.; Guenter, S.; Zehrfeld, H.-P.
2000-01-01
An ELMy ASDEX Upgrade plasma equilibrium is reconstructed taking into account the bootstrap current. The peeling mode stability of the equilibrium is numerically analysed using the GATO [1] code, and it is found that the bootstrap current can drive the plasma peeling mode unstable. A high-n ballooning mode stability analysis of the equilibria revealed that, while destabilizing the peeling modes, the bootstrap current has a stabilizing effect on the ballooning modes. A combination of these two instabilities is a possible explanation for the type I ELM phenomenon. A triangularity scan showed that increasing triangularity stabilizes the peeling modes and can produce ELM-free periods observed in the experiments. (author)
Diffeomorphic Statistical Deformation Models
DEFF Research Database (Denmark)
Hansen, Michael Sass; Hansen, Mads/Fogtman; Larsen, Rasmus
2007-01-01
In this paper we present a new method for constructing diffeomorphic statistical deformation models in arbitrary dimensional images with a nonlinear generative model and a linear parameter space. Our deformation model is a modified version of the diffeomorphic model introduced by Cootes et al....... The modifications ensure that no boundary restriction has to be enforced on the parameter space to prevent folds or tears in the deformation field. For straightforward statistical analysis, principal component analysis and sparse methods, we assume that the parameters for a class of deformations lie on a linear...... with ground truth in form of manual expert annotations, and compared to Cootes's model. We anticipate applications in unconstrained diffeomorphic synthesis of images, e.g. for tracking, segmentation, registration or classification purposes....
Stationary high confinement plasmas with large bootstrap current fraction in JT-60U
International Nuclear Information System (INIS)
Sakamoto, Y.; Fujita, T.; Ide, S.; Isayama, A.; Takechi, M.; Suzuki, T.; Takenaga, H.; Oyama, N.; Kamada, Y.
2005-01-01
This paper reports the results of the progress in stationary discharges with a large bootstrap current fraction in JT-60U towards steady-state tokamak operation. In the weak shear plasma regime, high-β p ELMy H-mode discharges have been optimized under nearly full non-inductive current drive conditions by the large bootstrap current fraction (f BS ∼ 45%) and the beam driven current fraction (f BD ∼ 50%), which was sustained for 5.8 s in the stationary condition. This duration corresponds to ∼26τ E and ∼2.8τ R , which was limited by the pulse length of negative-ion-based neutral beams. The high confinement enhancement factor H 89 ∼ 2.2 (HH 98y2 ∼ 1.0) was obtained and the profiles of current and pressure reached the stationary condition. In the reversed shear plasma regime, a large bootstrap current fraction (f BS ∼ 75%) has been sustained for 7.4 s under nearly full non-inductive current drive conditions. This duration corresponds to ∼16τ E and ∼2.7τ R . The high confinement enhancement factor H 89 ∼ 3.0 (HH 98y2 ∼ 1.7) was also sustained, and the profiles of current and pressure reached the stationary condition. The large bootstrap current and the off-axis beam driven current sustained this reversed q profile. This duration was limited only by the duration of the neutral beam injection
Maximum non-extensive entropy block bootstrap for non-stationary processes
Czech Academy of Sciences Publication Activity Database
Bergamelli, M.; Novotný, Jan; Urga, G.
2015-01-01
Roč. 91, 1/2 (2015), s. 115-139 ISSN 0001-771X R&D Projects: GA ČR(CZ) GA14-27047S Institutional support: RVO:67985998 Keywords : maximum entropy * bootstrap * Monte Carlo simulations Subject RIV: AH - Economics
Statistical modeling for degradation data
Lio, Yuhlong; Ng, Hon; Tsai, Tzong-Ru
2017-01-01
This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliability can be obtained by analyzing degradation data. In addition, statistical modeling and inference techniques have been developed on the basis of different degradation measures. The book brings together experts engaged in statistical modeling and inference, presenting and discussing important recent advances in degradation data analysis and related applications. The topics covered are timely and have considerable potential to impact both statistics and reliability engineering.
Exclusion statistics and integrable models
International Nuclear Information System (INIS)
Mashkevich, S.
1998-01-01
The definition of exclusion statistics, as given by Haldane, allows for a statistical interaction between distinguishable particles (multi-species statistics). The thermodynamic quantities for such statistics ca be evaluated exactly. The explicit expressions for the cluster coefficients are presented. Furthermore, single-species exclusion statistics is realized in one-dimensional integrable models. The interesting questions of generalizing this correspondence onto the higher-dimensional and the multi-species cases remain essentially open
Electric conductivity and bootstrap current in tokamak
International Nuclear Information System (INIS)
Mao Jianshan; Wang Maoquan
1996-12-01
A modified Ohm's law for the electric conductivity calculation is presented, where the modified ohmic current can be compensated by the bootstrap current. A comparison of TEXT tokamak experiment with the theories shows that the modified Ohm's law is a more close approximation to the tokamak experiments than the classical and neoclassical theories and can not lead to the absurd result of Z eff <1, and the extended neoclassical theory would be not necessary. (3 figs.)
Bootstrap equations for N=4 SYM with defects
Energy Technology Data Exchange (ETDEWEB)
Liendo, Pedro [IMIP, Humboldt-Universität zu Berlin, IRIS Adlershof,Zum Großen Windkanal 6, 12489 Berlin (Germany); Meneghelli, Carlo [Simons Center for Geometry and Physics, Stony Brook University,Stony Brook, NY 11794-3636 (United States)
2017-01-27
This paper focuses on the analysis of 4dN=4 superconformal theories in the presence of a defect from the point of view of the conformal bootstrap. We will concentrate first on the case of codimension one, where the defect is a boundary that preserves half of the supersymmetry. After studying the constraints imposed by supersymmetry, we will obtain the Ward identities associated to two-point functions of (1/2)-BPS operators and write their solution as a superconformal block expansion. Due to a surprising connection between spacetime and R-symmetry conformal blocks, our results not only apply to 4dN=4 superconformal theories with a boundary, but also to three more systems that have the same symmetry algebra: 4dN=4 superconformal theories with a line defect, 3dN=4 superconformal theories with no defect, and OSP(4{sup ∗}|4) superconformal quantum mechanics. The superconformal algebra implies that all these systems possess a closed subsector of operators in which the bootstrap equations become polynomial constraints on the CFT data. We derive these truncated equations and initiate the study of their solutions.
Bootstrap equations for N=4 SYM with defects
International Nuclear Information System (INIS)
Liendo, Pedro; Meneghelli, Carlo
2017-01-01
This paper focuses on the analysis of 4dN=4 superconformal theories in the presence of a defect from the point of view of the conformal bootstrap. We will concentrate first on the case of codimension one, where the defect is a boundary that preserves half of the supersymmetry. After studying the constraints imposed by supersymmetry, we will obtain the Ward identities associated to two-point functions of (1/2)-BPS operators and write their solution as a superconformal block expansion. Due to a surprising connection between spacetime and R-symmetry conformal blocks, our results not only apply to 4dN=4 superconformal theories with a boundary, but also to three more systems that have the same symmetry algebra: 4dN=4 superconformal theories with a line defect, 3dN=4 superconformal theories with no defect, and OSP(4 ∗ |4) superconformal quantum mechanics. The superconformal algebra implies that all these systems possess a closed subsector of operators in which the bootstrap equations become polynomial constraints on the CFT data. We derive these truncated equations and initiate the study of their solutions.
Physics issues of high bootstrap current tokamaks
International Nuclear Information System (INIS)
Ozeki, T.; Azumi, M.; Ishii, Y.
1997-01-01
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 q min is close to the region of high ∇n e . 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)
Adaptive Kernel In The Bootstrap Boosting Algorithm In KDE ...
African Journals Online (AJOL)
This paper proposes the use of adaptive kernel in a bootstrap boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...
Bootstrapping the energy flow in the beginning of life
Hengeveld, R.; Fedonkin, M.A.
2007-01-01
This paper suggests that the energy flow on which all living structures depend only started up slowly, the low-energy, initial phase starting up a second, slightly more energetic phase, and so on. In this way, the build up of the energy flow follows a bootstrapping process similar to that found in
Bootstrapping the energy flow in the beginning of life.
Hengeveld, R.; Fedonkin, M.A.
2007-01-01
This paper suggests that the energy flow on which all living structures depend only started up slowly, the low-energy, initial phase starting up a second, slightly more energetic phase, and so on. In this way, the build up of the energy flow follows a bootstrapping process similar to that found in
Use of Monte Carlo Bootstrap Method in the Analysis of Sample Sufficiency for Radioecological Data
International Nuclear Information System (INIS)
Silva, A. N. C. da; Amaral, R. S.; Araujo Santos Jr, J.; Wilson Vieira, J.; Lima, F. R. de A.
2015-01-01
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 226 Ra 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)
Bootstrapping Cox’s Regression Model.
1985-11-01
crucial points a multivariate martingale central limit theorem. Involved in this is a p x p covariance matrix Z with elements T j2= f {2(s8 ) - s(l)( s ,8o...1980). The statistical analaysis of failure time data. Wiley, New York. Meyer, P.-A. (1971). Square integrable martingales, a survey. Lecture Notes
A bootstrap invariance principle for highly nonstationary long memory processes
Kapetanios, George
2004-01-01
This paper presents an invariance principle for highly nonstationary long memory processes, defined as processes with long memory parameter lying in (1, 1.5). This principle provides the tools for showing asymptotic validity of the bootstrap in the context of such processes.
Bennett, Iain; Paracha, Noman; Abrams, Keith; Ray, Joshua
2018-01-01
Rank Preserving Structural Failure Time models are one of the most commonly used statistical methods to adjust for treatment switching in oncology clinical trials. The method is often applied in a decision analytic model without appropriately accounting for additional uncertainty when determining the allocation of health care resources. The aim of the study is to describe novel approaches to adequately account for uncertainty when using a Rank Preserving Structural Failure Time model in a decision analytic model. Using two examples, we tested and compared the performance of the novel Test-based method with the resampling bootstrap method and with the conventional approach of no adjustment. In the first example, we simulated life expectancy using a simple decision analytic model based on a hypothetical oncology trial with treatment switching. In the second example, we applied the adjustment method on published data when no individual patient data were available. Mean estimates of overall and incremental life expectancy were similar across methods. However, the bootstrapped and test-based estimates consistently produced greater estimates of uncertainty compared with the estimate without any adjustment applied. Similar results were observed when using the test based approach on a published data showing that failing to adjust for uncertainty led to smaller confidence intervals. Both the bootstrapping and test-based approaches provide a solution to appropriately incorporate uncertainty, with the benefit that the latter can implemented by researchers in the absence of individual patient data. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Integral equations of hadronic correlation functions a functional- bootstrap approach
Manesis, E K
1974-01-01
A reasonable 'microscopic' foundation of the Feynman hadron-liquid analogy is offered, based on a class of models for hadron production. In an external field formalism, the equivalence (complementarity) of the exclusive and inclusive descriptions of hadronic reactions is specifically expressed in a functional-bootstrap form, and integral equations between inclusive and exclusive correlation functions are derived. Using the latest CERN-ISR data on the two-pion inclusive correlation function, and assuming rapidity translational invariance for the exclusive one, the simplest integral equation is solved in the 'central region' and an exclusive correlation length in rapidity predicted. An explanation is also offered for the unexpected similarity observed between pi /sup +/ pi /sup -/ and pi /sup -/ pi /sup -/ inclusive correlations. (31 refs).
Statistical significance of trends in monthly heavy precipitation over the US
Mahajan, Salil
2011-05-11
Trends in monthly heavy precipitation, defined by a return period of one year, are assessed for statistical significance in observations and Global Climate Model (GCM) simulations over the contiguous United States using Monte Carlo non-parametric and parametric bootstrapping techniques. The results from the two Monte Carlo approaches are found to be similar to each other, and also to the traditional non-parametric Kendall\\'s τ test, implying the robustness of the approach. Two different observational data-sets are employed to test for trends in monthly heavy precipitation and are found to exhibit consistent results. Both data-sets demonstrate upward trends, one of which is found to be statistically significant at the 95% confidence level. Upward trends similar to observations are observed in some climate model simulations of the twentieth century, but their statistical significance is marginal. For projections of the twenty-first century, a statistically significant upwards trend is observed in most of the climate models analyzed. The change in the simulated precipitation variance appears to be more important in the twenty-first century projections than changes in the mean precipitation. Stochastic fluctuations of the climate-system are found to be dominate monthly heavy precipitation as some GCM simulations show a downwards trend even in the twenty-first century projections when the greenhouse gas forcings are strong. © 2011 Springer-Verlag.
An algebraic approach to the analytic bootstrap
Energy Technology Data Exchange (ETDEWEB)
Alday, Luis F. [Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG (United Kingdom); Zhiboedov, Alexander [Center for the Fundamental Laws of Nature, Harvard University, Cambridge, MA 02138 (United States)
2017-04-27
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.
A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data.
Liang, Faming; Kim, Jinsu; Song, Qifan
2016-01-01
Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their computer-intensive nature, which typically require a large number of iterations and a complete scan of the full dataset for each iteration, precludes their use for big data analysis. In this paper, we propose the so-called bootstrap Metropolis-Hastings (BMH) algorithm, which provides a general framework for how to tame powerful MCMC methods to be used for big data analysis; that is to replace the full data log-likelihood by a Monte Carlo average of the log-likelihoods that are calculated in parallel from multiple bootstrap samples. The BMH algorithm possesses an embarrassingly parallel structure and avoids repeated scans of the full dataset in iterations, and is thus feasible for big data problems. Compared to the popular divide-and-combine method, BMH can be generally more efficient as it can asymptotically integrate the whole data information into a single simulation run. The BMH algorithm is very flexible. Like the Metropolis-Hastings algorithm, it can serve as a basic building block for developing advanced MCMC algorithms that are feasible for big data problems. This is illustrated in the paper by the tempering BMH algorithm, which can be viewed as a combination of parallel tempering and the BMH algorithm. BMH can also be used for model selection and optimization by combining with reversible jump MCMC and simulated annealing, respectively.
A Bootstrap Metropolis–Hastings Algorithm for Bayesian Analysis of Big Data
Kim, Jinsu; Song, Qifan
2016-01-01
Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their computer-intensive nature, which typically require a large number of iterations and a complete scan of the full dataset for each iteration, precludes their use for big data analysis. In this paper, we propose the so-called bootstrap Metropolis-Hastings (BMH) algorithm, which provides a general framework for how to tame powerful MCMC methods to be used for big data analysis; that is to replace the full data log-likelihood by a Monte Carlo average of the log-likelihoods that are calculated in parallel from multiple bootstrap samples. The BMH algorithm possesses an embarrassingly parallel structure and avoids repeated scans of the full dataset in iterations, and is thus feasible for big data problems. Compared to the popular divide-and-combine method, BMH can be generally more efficient as it can asymptotically integrate the whole data information into a single simulation run. The BMH algorithm is very flexible. Like the Metropolis-Hastings algorithm, it can serve as a basic building block for developing advanced MCMC algorithms that are feasible for big data problems. This is illustrated in the paper by the tempering BMH algorithm, which can be viewed as a combination of parallel tempering and the BMH algorithm. BMH can also be used for model selection and optimization by combining with reversible jump MCMC and simulated annealing, respectively. PMID:29033469
Extended theory of main ion and impurity rotation and bootstrap current in a shear layer
International Nuclear Information System (INIS)
Kim, Y.B.; Hinton, F.L.; St. John, H.; Taylor, T.S.; Wroblewski, D.
1993-11-01
In this paper, standard neoclassical theory has been extended into the shear layer. Main ion and impurity ion rotation velocity and bootstrap current within shear layer in H-mode are discussed. Inside the H-mode shear layer, standard neoclassical theory is not valid since the ion poloidal gyroradius becomes comparable to pressure gradient and electric field gradient scale length. To allow for arbitrary ratio of ρθi/L n and ρθi/L Er a new kinetic theory of main ion species within electric field shear layer has been developed with the assumption that ρθi/R o is still small. As a consequence, both impurity flows and bootstrap current have to be modified. We present modified expressions of impurity flows and bootstrap current are presented neglecting ion temperature gradient. Comparisons with DIII-D measurements are also discussed
The N=2 superconformal bootstrap
Energy Technology Data Exchange (ETDEWEB)
Beem, Christopher [Institute for Advanced Study, Einstein Drive,Princeton, NJ 08540 (United States); Lemos, Madalena [C. N. Yang Institute for Theoretical Physics, Stony Brook University,Stony Brook, NY 11794-3840 (United States); Liendo, Pedro [IMIP, Humboldt-Universität zu Berlin, IRIS Adlershof,Zum Großen Windkanal 6, 12489 Berlin (Germany); Rastelli, Leonardo [C. N. Yang Institute for Theoretical Physics, Stony Brook University,Stony Brook, NY 11794-3840 (United States); Rees, Balt C. van [Theory Group, Physics Department, CERN,CH-1211 Geneva 23 (Switzerland)
2016-03-29
In this work we initiate the conformal bootstrap program for N=2 superconformal 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.
Kappa statistic for the clustered dichotomous responses from physicians and patients
Kang, Chaeryon; Qaqish, Bahjat; Monaco, Jane; Sheridan, Stacey L.; Cai, Jianwen
2013-01-01
The bootstrap method for estimating the standard error of the kappa statistic in the presence of clustered data is evaluated. Such data arise, for example, in assessing agreement between physicians and their patients regarding their understanding of the physician-patient interaction and discussions. We propose a computationally efficient procedure for generating correlated dichotomous responses for physicians and assigned patients for simulation studies. The simulation result demonstrates that the proposed bootstrap method produces better estimate of the standard error and better coverage performance compared to the asymptotic standard error estimate that ignores dependence among patients within physicians with at least a moderately large number of clusters. An example of an application to a coronary heart disease prevention study is presented. PMID:23533082
DMSP SSM/I Daily and Monthly Polar Gridded Bootstrap Sea Ice Concentrations
National Aeronautics and Space Administration — DMSP SSM/I Daily and Monthly Polar Gridded Bootstrap Sea Ice Concentrations in polar stereographic projection currently include Defense Meteorological Satellite...
Modelling and mapping the suitability of European forest formations at 1-km resolution
DEFF Research Database (Denmark)
Casalegno, Stefano; Amatulli, Giuseppe; Bastrup-Birk, Annemarie
2011-01-01
factors. Here, we used the bootstrap-aggregating machine-learning ensemble classifier Random Forest (RF) to derive a 1-km resolution European forest formation suitability map. The statistical model use as inputs more than 6,000 field data forest inventory plots and a large set of environmental variables...
Classical model of intermediate statistics
International Nuclear Information System (INIS)
Kaniadakis, G.
1994-01-01
In this work we present a classical kinetic model of intermediate statistics. In the case of Brownian particles we show that the Fermi-Dirac (FD) and Bose-Einstein (BE) distributions can be obtained, just as the Maxwell-Boltzmann (MD) distribution, as steady states of a classical kinetic equation that intrinsically takes into account an exclusion-inclusion principle. In our model the intermediate statistics are obtained as steady states of a system of coupled nonlinear kinetic equations, where the coupling constants are the transmutational potentials η κκ' . We show that, besides the FD-BE intermediate statistics extensively studied from the quantum point of view, we can also study the MB-FD and MB-BE ones. Moreover, our model allows us to treat the three-state mixing FD-MB-BE intermediate statistics. For boson and fermion mixing in a D-dimensional space, we obtain a family of FD-BE intermediate statistics by varying the transmutational potential η BF . This family contains, as a particular case when η BF =0, the quantum statistics recently proposed by L. Wu, Z. Wu, and J. Sun [Phys. Lett. A 170, 280 (1992)]. When we consider the two-dimensional FD-BE statistics, we derive an analytic expression of the fraction of fermions. When the temperature T→∞, the system is composed by an equal number of bosons and fermions, regardless of the value of η BF . On the contrary, when T=0, η BF becomes important and, according to its value, the system can be completely bosonic or fermionic, or composed both by bosons and fermions
A generic statistical methodology to predict the maximum pit depth of a localized corrosion process
International Nuclear Information System (INIS)
Jarrah, A.; Bigerelle, M.; Guillemot, G.; Najjar, D.; Iost, A.; Nianga, J.-M.
2011-01-01
Highlights: → We propose a methodology to predict the maximum pit depth in a corrosion process. → Generalized Lambda Distribution and the Computer Based Bootstrap Method are combined. → GLD fit a large variety of distributions both in their central and tail regions. → Minimum thickness preventing perforation can be estimated with a safety margin. → Considering its applications, this new approach can help to size industrial pieces. - Abstract: This paper outlines a new methodology to predict accurately the maximum pit depth related to a localized corrosion process. It combines two statistical methods: the Generalized Lambda Distribution (GLD), to determine a model of distribution fitting with the experimental frequency distribution of depths, and the Computer Based Bootstrap Method (CBBM), to generate simulated distributions equivalent to the experimental one. In comparison with conventionally established statistical methods that are restricted to the use of inferred distributions constrained by specific mathematical assumptions, the major advantage of the methodology presented in this paper is that both the GLD and the CBBM enable a statistical treatment of the experimental data without making any preconceived choice neither on the unknown theoretical parent underlying distribution of pit depth which characterizes the global corrosion phenomenon nor on the unknown associated theoretical extreme value distribution which characterizes the deepest pits. Considering an experimental distribution of depths of pits produced on an aluminium sample, estimations of maximum pit depth using a GLD model are compared to similar estimations based on usual Gumbel and Generalized Extreme Value (GEV) methods proposed in the corrosion engineering literature. The GLD approach is shown having smaller bias and dispersion in the estimation of the maximum pit depth than the Gumbel approach both for its realization and mean. This leads to comparing the GLD approach to the GEV one
Probing NWP model deficiencies by statistical postprocessing
DEFF Research Database (Denmark)
Rosgaard, Martin Haubjerg; Nielsen, Henrik Aalborg; Nielsen, Torben S.
2016-01-01
The objective in this article is twofold. On one hand, a Model Output Statistics (MOS) framework for improved wind speed forecast accuracy is described and evaluated. On the other hand, the approach explored identifies unintuitive explanatory value from a diagnostic variable in an operational....... Based on the statistical model candidates inferred from the data, the lifted index NWP model diagnostic is consistently found among the NWP model predictors of the best performing statistical models across sites....
Using the Bootstrap Concept to Build an Adaptable and Compact Subversion Artifice
National Research Council Canada - National Science Library
Lack, Lindsey
2003-01-01
.... Early tiger teams recognized the possibility of this design and compared it to the two-card bootstrap loader used in mainframes since both exhibit the characteristics of compactness and adaptability...
Coal consumption and economic growth nexus: Evidence from bootstrap panel Granger causality test
Directory of Open Access Journals (Sweden)
Anoruo Emmanuel
2017-01-01
Full Text Available This paper explores the causal relationship between coal consumption and economic growth for a panel of 15 African countries using bootstrap panel Granger causality test. Specifically, this paper uses the Phillips-Perron unit root test to ascertain the order of integration for the coal consumption and economic growth series. A bootstrap panel Granger causality test is employed to determine the direction of causality between coal consumption and economic growth. The results provide evidence of unidirectional causality from economic growth to coal consumption. This finding implies that coal conservation measures may be implemented with little or no adverse impact on economic growth for the sample countries as a group.
Statistical Model of Extreme Shear
DEFF Research Database (Denmark)
Hansen, Kurt Schaldemose; Larsen, Gunner Chr.
2005-01-01
In order to continue cost-optimisation of modern large wind turbines, it is important to continuously increase the knowledge of wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... by a model that, on a statistically consistent basis, describes the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of full-scale measurements recorded with a high sampling rate...
Aspects of statistical model for multifragmentation
International Nuclear Information System (INIS)
Bhattacharyya, P.; Das Gupta, S.; Mekjian, A. Z.
1999-01-01
We deal with two different aspects of an exactly soluble statistical model of fragmentation. First we show, using zero range force and finite temperature Thomas-Fermi theory, that a common link can be found between finite temperature mean field theory and the statistical fragmentation model. We show the latter naturally arises in the spinodal region. Next we show that although the exact statistical model is a canonical model and uses temperature, microcanonical results which use constant energy rather than constant temperature can also be obtained from the canonical model using saddle-point approximation. The methodology is extremely simple to implement and at least in all the examples studied in this work is very accurate. (c) 1999 The American Physical Society
Stationary, high bootstrap fraction plasmas in DIII-D without inductive current control
International Nuclear Information System (INIS)
Politzer, P.A.; Hyatt, A.W.; Luce, T.C.; Prater, R.; Turnbull, A.D.; Ferron, J.R.; Greenfield, C.M.; La Haye, R.J.; Petty, C.C.; Perkins, F.W.; Brennan, D.P.; Lazarus, E.A.; Jayakumar, J.; Wade, M.R.
2005-01-01
We have initiated an experimental program to address some of the questions associated with operation of a tokamak with high bootstrap current fraction under high performance conditions, without assistance from a transformer. In these discharges stationary (or slowly improving) conditions are maintained for > 3.7 s at β N ∼ β p ≤ 3.3. The achievable current and pressure are limited by a relaxation oscillation, involving growth and collapse of an ITB at ρ ≥ 0.6. The pressure gradually increases and the current profile broadens throughout the discharge. Eventually the plasma reaches a more stable, high confinement (H89P ∼ 3) state. Characteristically these plasmas have 65%-85% bootstrap current, 15%-30% NBCD, and 0%-10% ECCD. (author)
Statistical Compression for Climate Model Output
Hammerling, D.; Guinness, J.; Soh, Y. J.
2017-12-01
Numerical climate model simulations run at high spatial and temporal resolutions generate massive quantities of data. As our computing capabilities continue to increase, storing all of the data is not sustainable, and thus is it important to develop methods for representing the full datasets by smaller compressed versions. We propose a statistical compression and decompression algorithm based on storing a set of summary statistics as well as a statistical model describing the conditional distribution of the full dataset given the summary statistics. We decompress the data by computing conditional expectations and conditional simulations from the model given the summary statistics. Conditional expectations represent our best estimate of the original data but are subject to oversmoothing in space and time. Conditional simulations introduce realistic small-scale noise so that the decompressed fields are neither too smooth nor too rough compared with the original data. Considerable attention is paid to accurately modeling the original dataset-one year of daily mean temperature data-particularly with regard to the inherent spatial nonstationarity in global fields, and to determining the statistics to be stored, so that the variation in the original data can be closely captured, while allowing for fast decompression and conditional emulation on modest computers.
Automated statistical modeling of analytical measurement systems
International Nuclear Information System (INIS)
Jacobson, J.J.
1992-01-01
The statistical modeling of analytical measurement systems at the Idaho Chemical Processing Plant (ICPP) has been completely automated through computer software. The statistical modeling of analytical measurement systems is one part of a complete quality control program used by the Remote Analytical Laboratory (RAL) at the ICPP. The quality control program is an integration of automated data input, measurement system calibration, database management, and statistical process control. The quality control program and statistical modeling program meet the guidelines set forth by the American Society for Testing Materials and American National Standards Institute. A statistical model is a set of mathematical equations describing any systematic bias inherent in a measurement system and the precision of a measurement system. A statistical model is developed from data generated from the analysis of control standards. Control standards are samples which are made up at precise known levels by an independent laboratory and submitted to the RAL. The RAL analysts who process control standards do not know the values of those control standards. The object behind statistical modeling is to describe real process samples in terms of their bias and precision and, to verify that a measurement system is operating satisfactorily. The processing of control standards gives us this ability
Statistical modelling for ship propulsion efficiency
DEFF Research Database (Denmark)
Petersen, Jóan Petur; Jacobsen, Daniel J.; Winther, Ole
2012-01-01
This paper presents a state-of-the-art systems approach to statistical modelling of fuel efficiency in ship propulsion, and also a novel and publicly available data set of high quality sensory data. Two statistical model approaches are investigated and compared: artificial neural networks...
Aspect Ratio Scaling of Ideal No-wall Stability Limits in High Bootstrap Fraction Tokamak Plasmas
International Nuclear Information System (INIS)
Menard, J.E.; Bell, M.G.; Bell, R.E.; Gates, D.A.; Kaye, S.M.; LeBlanc, B.P.; Maingi, R.; Sabbagh, S.A.; Soukhanovskii, V.; Stutman, D.
2003-01-01
Recent experiments in the low aspect ratio National Spherical Torus Experiment (NSTX) [M. Ono et al., Nucl. Fusion 40 (2000) 557] have achieved normalized beta values twice the conventional tokamak limit at low internal inductance and with significant bootstrap current. These experimental results have motivated a computational re-examination of the plasma aspect ratio dependence of ideal no-wall magnetohydrodynamic stability limits. These calculations find that the profile-optimized no-wall stability limit in high bootstrap fraction regimes is well described by a nearly aspect ratio invariant normalized beta parameter utilizing the total magnetic field energy density inside the plasma. However, the scaling of normalized beta with internal inductance is found to be strongly aspect ratio dependent at sufficiently low aspect ratio. These calculations and detailed stability analyses of experimental equilibria indicate that the nonrotating plasma no-wall stability limit has been exceeded by as much as 30% in NSTX in a high bootstrap fraction regime
Noncritical String Liouville Theory and Geometric Bootstrap Hypothesis
Hadasz, Leszek; Jaskólski, Zbigniew
The applications of the existing Liouville theories for the description of the longitudinal dynamics of noncritical Nambu-Goto string are analyzed. We show that the recently developed DOZZ solution to the Liouville theory leads to the cut singularities in tree string amplitudes. We propose a new version of the Polyakov geometric approach to Liouville theory and formulate its basic consistency condition — the geometric bootstrap equation. Also in this approach the tree amplitudes develop cut singularities.
Sensometrics: Thurstonian and Statistical Models
DEFF Research Database (Denmark)
Christensen, Rune Haubo Bojesen
. sensR is a package for sensory discrimination testing with Thurstonian models and ordinal supports analysis of ordinal data with cumulative link (mixed) models. While sensR is closely connected to the sensometrics field, the ordinal package has developed into a generic statistical package applicable......This thesis is concerned with the development and bridging of Thurstonian and statistical models for sensory discrimination testing as applied in the scientific discipline of sensometrics. In sensory discrimination testing sensory differences between products are detected and quantified by the use...... and sensory discrimination testing in particular in a series of papers by advancing Thurstonian models for a range of sensory discrimination protocols in addition to facilitating their application by providing software for fitting these models. The main focus is on identifying Thurstonian models...
Statistical modelling for social researchers principles and practice
Tarling, Roger
2008-01-01
This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-l...
Topology for statistical modeling of petascale data.
Energy Technology Data Exchange (ETDEWEB)
Pascucci, Valerio (University of Utah, Salt Lake City, UT); Mascarenhas, Ajith Arthur; Rusek, Korben (Texas A& M University, College Station, TX); Bennett, Janine Camille; Levine, Joshua (University of Utah, Salt Lake City, UT); Pebay, Philippe Pierre; Gyulassy, Attila (University of Utah, Salt Lake City, UT); Thompson, David C.; Rojas, Joseph Maurice (Texas A& M University, College Station, TX)
2011-07-01
This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled 'Topology for Statistical Modeling of Petascale Data', funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program. Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is thus to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, our approach is based on the complementary techniques of combinatorial topology and statistical modeling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modeling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. This document summarizes the technical advances we have made to date that were made possible in whole or in part by MAPD funding. These technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modeling, and (3) new integrated topological and statistical methods.
Acharya, N.; Frei, A.; Owens, E. M.; Chen, J.
2015-12-01
Watersheds located in the Catskill Mountains area, part of the eastern plateau climate region of New York, contributes about 90% of New York City's municipal water supply, serving 9 million New Yorkers with about 1.2 billion gallons of clean drinking water each day. The New York City Department of Environmental Protection has an ongoing series of studies to assess the potential impacts of climate change on the availability of high quality water in this water supply system. Recent studies identify increasing trends in total precipitation and in the frequency of extreme precipitation events in this region. The objectives of the present study are: to analyze the probabilistic structure of extreme precipitation based on historical observations: and to evaluate the abilities of stochastic weather generators (WG), statistical models that produce synthetic weather time series based on observed statistical properties at a particular location, to simulate the statistical properties of extreme precipitation events over this region. The generalized extreme value distribution (GEV) has been applied to the annual block maxima of precipitation for 60 years (1950 to 2009) observed data in order to estimate the events with return periods of 50, 75, and 100 years. These results were then used to evaluate a total of 13 WGs were : 12 parametric WGs including all combinations of three different orders of Markov chain (MC) models (1st , 2nd and 3rd) and four different probability distributions (exponential, gamma, skewed normal and mixed exponential); and one semi parametric WG based on k-nearest neighbor bootstrapping. Preliminary results suggest that three-parameter (skewed normal and mixed exponential distribution) and semi-parametric (k-nearest neighbor bootstrapping) WGs are more consistent with observations. It is also found that first order MC models perform as well as second or third order MC models.
Nonparametric statistics with applications to science and engineering
Kvam, Paul H
2007-01-01
A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provide...
Bayesian models: A statistical primer for ecologists
Hobbs, N. Thompson; Hooten, Mevin B.
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models
Statistical Model-Based Face Pose Estimation
Institute of Scientific and Technical Information of China (English)
GE Xinliang; YANG Jie; LI Feng; WANG Huahua
2007-01-01
A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.
Non-abelian binding energies from the lightcone bootstrap
Energy Technology Data Exchange (ETDEWEB)
Li, Daliang [Department of Physics, Yale University,New Haven, CT 06511 (United States); Department of Physics and Astronomy, Johns Hopkins University,Baltimore, MD 21218 (United States); Meltzer, David [Department of Physics, Yale University,New Haven, CT 06511 (United States); Poland, David [Department of Physics, Yale University,New Haven, CT 06511 (United States); School of Natural Sciences, Institute for Advanced Study,Princeton, NJ 08540 (United States)
2016-02-23
We analytically study the lightcone limit of the conformal bootstrap for 4-point functions containing scalars charged under global symmetries. We show the existence of large spin double-twist operators in various representations of the global symmetry group. We then compute their anomalous dimensions in terms of the central charge C{sub T}, current central charge C{sub J}, and the OPE coefficients of low dimension scalars. In AdS, these results correspond to the binding energy of two-particle states arising from the exchange of gravitons, gauge bosons, and light scalar fields. Using unitarity and crossing symmetry, we show that gravity is universal and attractive among different types of two-particle states, while the gauge binding energy can have either sign as determined by the representation of the two-particle state, with universal ratios fixed by the symmetry group. We apply our results to 4D N=1 SQCD and the 3D O(N) vector models. We also show that in a unitary CFT, if the current central charge C{sub J} stays finite when the global symmetry group becomes infinitely large, such as the N→∞ limit of the O(N) vector model, then the theory must contain an infinite number of higher spin currents.
A 'bootstrapped' Teaching/Learning Procedure
Odusina Odusote, Olusogo
1998-04-01
Erasing preconceived antiphysics ideas by nonscience/nonmajor physics students have elicited diverse teaching methods. Introductory general physics courses at college level have been taught by a 'bootstrap' approach. A concise treatment of the syllabus by the teacher in about 1/2 of the course duration, with brief exercises and examples. Students are then introduced to real life situations - toys, home appliances, sports, disasters, etc, and the embedded physics concepts discussed. Usually this generates a feeling of deja vu, which elicits desire for more. Each application usually encompasses topics in a broad range of the syllabus. The other half of the course is used by students to work individually/groups on assigned and graded home-works and essays, with guidance from the lecture notes and the teacher/supervisor. An end of course examination shows increase in the success rate.
Simple statistical model for branched aggregates
DEFF Research Database (Denmark)
Lemarchand, Claire; Hansen, Jesper Schmidt
2015-01-01
, given that it already has bonds with others. The model is applied here to asphaltene nanoaggregates observed in molecular dynamics simulations of Cooee bitumen. The variation with temperature of the probabilities deduced from this model is discussed in terms of statistical mechanics arguments....... The relevance of the statistical model in the case of asphaltene nanoaggregates is checked by comparing the predicted value of the probability for one molecule to have exactly i bonds with the same probability directly measured in the molecular dynamics simulations. The agreement is satisfactory......We propose a statistical model that can reproduce the size distribution of any branched aggregate, including amylopectin, dendrimers, molecular clusters of monoalcohols, and asphaltene nanoaggregates. It is based on the conditional probability for one molecule to form a new bond with a molecule...
International Nuclear Information System (INIS)
Nemov, V V; Kalyuzhnyj, V N; Kasilov, S V; Drevlak, M; Nuehrenberg, J; Kernbichler, W; Reiman, A; Monticello, D
2004-01-01
For the magnetic field of the Wendelstein 7-X (W7-X) standard high-mirror configuration, computed by the PIES code, taking into account real coil geometry, neoclassical transport and bootstrap current are analysed in the 1/upsilon regime using methods based on the integration along magnetic field lines in a given magnetic field. The zero beta and (beta) = 1% cases are studied. The results are compared to the corresponding results for the vacuum magnetic field directly produced by modular coils. A significant advantage of W7-X over a conventional stellarator resulting from reduced neoclassical transport and from reduced bootstrap current follows from the computations although the neoclassical transport is somewhat larger than that previously obtained for the ideal W7-X model configuration
Matrix Tricks for Linear Statistical Models
Puntanen, Simo; Styan, George PH
2011-01-01
In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple "tricks" which simplify and clarify the treatment of a problem - both for the student and
Statistical Model Checking of Rich Models and Properties
DEFF Research Database (Denmark)
Poulsen, Danny Bøgsted
in undecidability issues for the traditional model checking approaches. Statistical model checking has proven itself a valuable supplement to model checking and this thesis is concerned with extending this software validation technique to stochastic hybrid systems. The thesis consists of two parts: the first part...... motivates why existing model checking technology should be supplemented by new techniques. It also contains a brief introduction to probability theory and concepts covered by the six papers making up the second part. The first two papers are concerned with developing online monitoring techniques...... systems. The fifth paper shows how stochastic hybrid automata are useful for modelling biological systems and the final paper is concerned with showing how statistical model checking is efficiently distributed. In parallel with developing the theory contained in the papers, a substantial part of this work...
Statistical Modelling of Wind Proles - Data Analysis and Modelling
DEFF Research Database (Denmark)
Jónsson, Tryggvi; Pinson, Pierre
The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....
Alden, Caroline B.; Ghosh, Subhomoy; Coburn, Sean; Sweeney, Colm; Karion, Anna; Wright, Robert; Coddington, Ian; Rieker, Gregory B.; Prasad, Kuldeep
2018-03-01
Advances in natural gas extraction technology have led to increased activity in the production and transport sectors in the United States and, as a consequence, an increased need for reliable monitoring of methane leaks to the atmosphere. We present a statistical methodology in combination with an observing system for the detection and attribution of fugitive emissions of methane from distributed potential source location landscapes such as natural gas production sites. We measure long (> 500 m), integrated open-path concentrations of atmospheric methane using a dual frequency comb spectrometer and combine measurements with an atmospheric transport model to infer leak locations and strengths using a novel statistical method, the non-zero minimum bootstrap (NZMB). The new statistical method allows us to determine whether the empirical distribution of possible source strengths for a given location excludes zero. Using this information, we identify leaking source locations (i.e., natural gas wells) through rejection of the null hypothesis that the source is not leaking. The method is tested with a series of synthetic data inversions with varying measurement density and varying levels of model-data mismatch. It is also tested with field observations of (1) a non-leaking source location and (2) a source location where a controlled emission of 3.1 × 10-5 kg s-1 of methane gas is released over a period of several hours. This series of synthetic data tests and outdoor field observations using a controlled methane release demonstrates the viability of the approach for the detection and sizing of very small leaks of methane across large distances (4+ km2 in synthetic tests). The field tests demonstrate the ability to attribute small atmospheric enhancements of 17 ppb to the emitting source location against a background of combined atmospheric (e.g., background methane variability) and measurement uncertainty of 5 ppb (1σ), when measurements are averaged over 2 min. The
Statistical physics of pairwise probability models
DEFF Research Database (Denmark)
Roudi, Yasser; Aurell, Erik; Hertz, John
2009-01-01
(dansk abstrakt findes ikke) Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data......: knowledge of the means and correlations between pairs of elements in the system is sufficient. Not surprisingly, then, using pairwise models for studying neural data has been the focus of many studies in recent years. In this paper, we describe how tools from statistical physics can be employed for studying...
Wang, Yi; Zheng, Tong; Zhao, Ying; Jiang, Jiping; Wang, Yuanyuan; Guo, Liang; Wang, Peng
2013-12-01
In this paper, bootstrapped wavelet neural network (BWNN) was developed for predicting monthly ammonia nitrogen (NH(4+)-N) and dissolved oxygen (DO) in Harbin region, northeast of China. The Morlet wavelet basis function (WBF) was employed as a nonlinear activation function of traditional three-layer artificial neural network (ANN) structure. Prediction intervals (PI) were constructed according to the calculated uncertainties from the model structure and data noise. Performance of BWNN model was also compared with four different models: traditional ANN, WNN, bootstrapped ANN, and autoregressive integrated moving average model. The results showed that BWNN could handle the severely fluctuating and non-seasonal time series data of water quality, and it produced better performance than the other four models. The uncertainty from data noise was smaller than that from the model structure for NH(4+)-N; conversely, the uncertainty from data noise was larger for DO series. Besides, total uncertainties in the low-flow period were the biggest due to complicated processes during the freeze-up period of the Songhua River. Further, a data missing-refilling scheme was designed, and better performances of BWNNs for structural data missing (SD) were observed than incidental data missing (ID). For both ID and SD, temporal method was satisfactory for filling NH(4+)-N series, whereas spatial imputation was fit for DO series. This filling BWNN forecasting method was applied to other areas suffering "real" data missing, and the results demonstrated its efficiency. Thus, the methods introduced here will help managers to obtain informed decisions.
International Nuclear Information System (INIS)
Takei, Nahoko; Tsutsui, Hiroaki; Tsuji-Iio, Shunji; Shimada, Ryuichi; Nakamura, Yukiharu; Kawano, Yasunori; Ozeki, Takahisa; Tobita, Kenji; Sugihara, Masayoshi
2004-01-01
Axisymmetric MHD simulation using the Tokamak Simulation Code demonstrated detailed disruption dynamics triggered by a crash of internal transport barrier in high bootstrap current, high β, reversed shear plasmas. Self-consistent time-evolutions of ohmic current bootstrap current and induced loop voltage profiles inside the disrupting plasma were shown from a view point of disruption characterization and mitigation. In contrast with positive shear plasmas, a particular feature of high bootstrap current reversed shear plasma disruption was computed to be a significant change of plasma current profile, which is normally caused due to resistive diffusion of the electric field induced by the crash of internal transport barrier in a region wider than the internal transport barrier. Discussion based on the simulation results was made on the fastest record of the plasma current quench observed in JT-60U reversed shear plasma disruptions. (author)
Technical and scale efficiency in public and private Irish nursing homes - a bootstrap DEA approach.
Ni Luasa, Shiovan; Dineen, Declan; Zieba, Marta
2016-10-27
This article provides methodological and empirical insights into the estimation of technical efficiency in the nursing home sector. Focusing on long-stay care and using primary data, we examine technical and scale efficiency in 39 public and 73 private Irish nursing homes by applying an input-oriented data envelopment analysis (DEA). We employ robust bootstrap methods to validate our nonparametric DEA scores and to integrate the effects of potential determinants in estimating the efficiencies. Both the homogenous and two-stage double bootstrap procedures are used to obtain confidence intervals for the bias-corrected DEA scores. Importantly, the application of the double bootstrap approach affords true DEA technical efficiency scores after adjusting for the effects of ownership, size, case-mix, and other determinants such as location, and quality. Based on our DEA results for variable returns to scale technology, the average technical efficiency score is 62 %, and the mean scale efficiency is 88 %, with nearly all units operating on the increasing returns to scale part of the production frontier. Moreover, based on the double bootstrap results, Irish nursing homes are less technically efficient, and more scale efficient than the conventional DEA estimates suggest. Regarding the efficiency determinants, in terms of ownership, we find that private facilities are less efficient than the public units. Furthermore, the size of the nursing home has a positive effect, and this reinforces our finding that Irish homes produce at increasing returns to scale. Also, notably, we find that a tendency towards quality improvements can lead to poorer technical efficiency performance.
Parameter tolerance of the SQUID bootstrap circuit
International Nuclear Information System (INIS)
Zhang Guofeng; Dong Hui; Xie Xiaoming; Jiang Mianheng; Zhang Yi; Krause, Hans-Joachim; Braginski, Alex I; Offenhäusser, Andreas
2012-01-01
We recently demonstrated and analysed the voltage-biased SQUID bootstrap circuit (SBC) conceived to suppress the preamplifier noise contribution in the absence of flux modulation readout. Our scheme contains both the additional voltage and current feedbacks. In this study, we analysed the tolerance of the SBC noise suppression performance to spreads in SQUID and SBC circuit parameters. Analytical results were confirmed by experiments. A one-time adjustable current feedback can be used to extend the tolerance to spreads such as those caused by the integrated circuit fabrication process. This should help to improve the fabrication yield of SBC devices integrated on one chip—as required for multi-channel SQUID systems.
Uncertainty the soul of modeling, probability & statistics
Briggs, William
2016-01-01
This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance". The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, suc...
Statistical Models for Social Networks
Snijders, Tom A. B.; Cook, KS; Massey, DS
2011-01-01
Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For
Directory of Open Access Journals (Sweden)
Ibáñez Berta
2009-04-01
Full Text Available Abstract Background The importance of Small Area Variation Analysis for policy-making contrasts with the scarcity of work on the validity of the statistics used in these studies. Our study aims at 1 determining whether variation in utilization rates between health areas is higher than would be expected by chance, 2 estimating the statistical power of the variation statistics; and 3 evaluating the ability of different statistics to compare the variability among different procedures regardless of their rates. Methods Parametric bootstrap techniques were used to derive the empirical distribution for each statistic under the hypothesis of homogeneity across areas. Non-parametric procedures were used to analyze the empirical distribution for the observed statistics and compare the results in six situations (low/medium/high utilization rates and low/high variability. A small scale simulation study was conducted to assess the capacity of each statistic to discriminate between different scenarios with different degrees of variation. Results Bootstrap techniques proved to be good at quantifying the difference between the null hypothesis and the variation observed in each situation, and to construct reliable tests and confidence intervals for each of the variation statistics analyzed. Although the good performance of Systematic Component of Variation (SCV, Empirical Bayes (EB statistic shows better behaviour under the null hypothesis, it is able to detect variability if present, it is not influenced by the procedure rate and it is best able to discriminate between different degrees of heterogeneity. Conclusion The EB statistics seems to be a good alternative to more conventional statistics used in small-area variation analysis in health service research because of its robustness.
Application of the bootstrap method to radiolabeled antibody dosimetry from planar images
International Nuclear Information System (INIS)
Papenfuss, T.; Saunder, T.H.; Schleyer, P.J.; O'Keefe, G.J.; Scott, A.M.
2002-01-01
Full text: Planar imaging dosimetry of radiolabeled antibody treatment uses the MIRD schema to compute dose to an organ from the calculated activity in that and other organs. The calculated activity in an organ is a function of the average count rates in the organ, a standard and an appropriate background measurement. The geometric mean of conjugate averages, together with an attenuation factor is used to provide an approximate attenuation correction. It is sometimes desirable to know the variance of the activity in an organ in order to apply weighted least squares regression to the data. This is particularly important when incorporating more accurate data from autoradiography of biopsied tissue into the analysis, but is also useful when some data points have low signal. While the geometric mean image can be used to calculate the variance of an organ's count rate. It is difficult to calculate the variance of the activity, since the organ in question, the standard and the background all contribute to it. Bootstrap methods are Monte Carlo techniques that can be used to estimate parameters from data and to determine the accuracy of the estimation. By bootstrapping pixel values in the organ, background and standard ROIs, it is possible to calculate many realisations of the organ activity and calculate its variance. As an example, bootstrapping is applied to the pharmacodynamic analysis of 131 I-huA33 in colon. The data includes planar whole body images, and autoradiographs and planar images of a resected colon. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc
Functional summary statistics for the Johnson-Mehl model
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
The Johnson-Mehl germination-growth model is a spatio-temporal point process model which among other things have been used for the description of neurotransmitters datasets. However, for such datasets parametric Johnson-Mehl models fitted by maximum likelihood have yet not been evaluated by means...... of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....
Petersson, K M; Nichols, T E; Poline, J B; Holmes, A P
1999-01-01
Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference. PMID:10466149
The ${\\mathcal N}=2$ superconformal bootstrap
Beem, Christopher; Liendo, Pedro; Rastelli, Leonardo; van Rees, Balt C
2016-01-01
In this work we initiate the conformal bootstrap program for ${\\mathcal N}=2$ superconformal 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 ${\\mathcal N}=2$ 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 ${\\mathcal N}=2$ superconformal field theory.
Bootstrapping Malmquist indices for Danish seiners in the North Sea and Skagerrak
DEFF Research Database (Denmark)
Hoff, Ayoe
2006-01-01
DEA scores or related parameters. The bootstrap method for estimating confidence intervals of deterministic parameters can however be applied to estimate confidence intervals for DEA scores. This method is applied in the present paper for assessing TFP changes between 1987 and 1999 for the fleet...
International Nuclear Information System (INIS)
Oikawa, T.; Suzuki, T.; Isayama, A.; Hayashi, N.; Fujita, T.; Naito, O.; Tuda, T.; Kurita, G.
2005-01-01
Evolution of the current density profile associated with magnetic island formation in a neoclassical tearing mode plasma is measured for the first time in JT-60U by using a motional Stark effect diagnostic. As the island grows, the current density profile turns flat at the radial region of the island and a hollow structure appears at the rational surface. As the island shrinks the deformed region becomes narrower and finally diminishes after the disappearance of the island. In a quiescent plasma without magnetohydrodynamic instabilities, on the other hand, no deformation is observed. The observed deformation in the current density profile associated with the tearing mode is reproduced in a time dependent transport simulation assuming the reduction of the bootstrap current in the radial region of the island. Comparison of the measurement with a calculated steady-state solution also shows that the reduction and recovery of the bootstrap current at the island explains the temporal behaviours of the current density and safety factor profiles. From the experimental observation and simulations, we reach the conclusion that the bootstrap current decreases within the island O-point
Distributions with given marginals and statistical modelling
Fortiana, Josep; Rodriguez-Lallena, José
2002-01-01
This book contains a selection of the papers presented at the meeting `Distributions with given marginals and statistical modelling', held in Barcelona (Spain), July 17-20, 2000. In 24 chapters, this book covers topics such as the theory of copulas and quasi-copulas, the theory and compatibility of distributions, models for survival distributions and other well-known distributions, time series, categorical models, definition and estimation of measures of dependence, monotonicity and stochastic ordering, shape and separability of distributions, hidden truncation models, diagonal families, orthogonal expansions, tests of independence, and goodness of fit assessment. These topics share the use and properties of distributions with given marginals, this being the fourth specialised text on this theme. The innovative aspect of the book is the inclusion of statistical aspects such as modelling, Bayesian statistics, estimation, and tests.
Using i2b2 to Bootstrap Rural Health Analytics and Learning Networks.
Harris, Daniel R; Baus, Adam D; Harper, Tamela J; Jarrett, Traci D; Pollard, Cecil R; Talbert, Jeffery C
2016-08-01
We demonstrate that the open-source i2b2 (Informatics for Integrating Biology and the Bedside) data model can be used to bootstrap rural health analytics and learning networks. These networks promote communication and research initiatives by providing the infrastructure necessary for sharing data and insights across a group of healthcare and research partners. Data integration remains a crucial challenge in connecting rural healthcare sites with a common data sharing and learning network due to the lack of interoperability and standards within electronic health records. The i2b2 data model acts as a point of convergence for disparate data from multiple healthcare sites. A consistent and natural data model for healthcare data is essential for overcoming integration issues, but challenges such as those caused by weak data standardization must still be addressed. We describe our experience in the context of building the West Virginia/Kentucky Health Analytics and Learning Network, a collaborative, multi-state effort connecting rural healthcare sites.
Highton, R
1993-12-01
An analysis of the relationship between the number of loci utilized in an electrophoretic study of genetic relationships and the statistical support for the topology of UPGMA trees is reported for two published data sets. These are Highton and Larson (Syst. Zool.28:579-599, 1979), an analysis of the relationships of 28 species of plethodonine salamanders, and Hedges (Syst. Zool., 35:1-21, 1986), a similar study of 30 taxa of Holarctic hylid frogs. As the number of loci increases, the statistical support for the topology at each node in UPGMA trees was determined by both the bootstrap and jackknife methods. The results show that the bootstrap and jackknife probabilities supporting the topology at some nodes of UPGMA trees increase as the number of loci utilized in a study is increased, as expected for nodes that have groupings that reflect phylogenetic relationships. The pattern of increase varies and is especially rapid in the case of groups with no close relatives. At nodes that likely do not represent correct phylogenetic relationships, the bootstrap probabilities do not increase and often decline with the addition of more loci.
Actuarial statistics with generalized linear mixed models
Antonio, K.; Beirlant, J.
2007-01-01
Over the last decade the use of generalized linear models (GLMs) in actuarial statistics has received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh and Nelder [McCullagh, P., Nelder, J.A., 1989. Generalized linear models. In: Monographs on Statistics
Structured statistical models of inductive reasoning.
Kemp, Charles; Tenenbaum, Joshua B
2009-01-01
Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet both goals and describes [corrected] 4 applications of the framework: a taxonomic model, a spatial model, a threshold model, and a causal model. Each model makes probabilistic inferences about the extensions of novel properties, but the priors for the 4 models are defined over different kinds of structures that capture different relationships between the categories in a domain. The framework therefore shows how statistical inference can operate over structured background knowledge, and the authors argue that this interaction between structure and statistics is critical for explaining the power and flexibility of human reasoning.
López, Erick B; Yamashita, Takashi
2017-02-01
This study examined whether household income mediates the relationship between acculturation and vegetable consumption among Latino adults in the U.S. Data from the 2009 to 2010 National Health and Nutrition Examination Survey were analyzed. Vegetable consumption index was created based on the frequencies of five kinds of vegetables intake. Acculturation was measured with the degree of English language use at home. Path model with bootstrapping technique was employed for mediation analysis. A significant partial mediation relationship was identified. Greater acculturation [95 % bias corrected bootstrap confident interval (BCBCI) = (0.02, 0.33)] was associated with the higher income and in turn, greater vegetable consumption. At the same time, greater acculturation was associated with lower vegetable consumption [95 % BCBCI = (-0.88, -0.07)]. Findings regarding the income as a mediator of the acculturation-dietary behavior relationship inform unique intervention programs and policy changes to address health disparities by race/ethnicity.
Energy Technology Data Exchange (ETDEWEB)
Secchi, Piercesare [MOX, Department of Mathematics, Polytechnic of Milan (Italy); Zio, Enrico [Department of Energy, Polytechnic of Milan, Via Ponzio 34/3, 20133 Milano (Italy)], E-mail: enrico.zio@polimi.it; Di Maio, Francesco [Department of Energy, Polytechnic of Milan, Via Ponzio 34/3, 20133 Milano (Italy)
2008-12-15
For licensing purposes, safety cases of Nuclear Power Plants (NPPs) must be presented at the Regulatory Authority with the necessary confidence on the models used to describe the plant safety behavior. In principle, this requires the repetition of a large number of model runs to account for the uncertainties inherent in the model description of the true plant behavior. The present paper propounds the use of bootstrapped Artificial Neural Networks (ANNs) for performing the numerous model output calculations needed for estimating safety margins with appropriate confidence intervals. Account is given both to the uncertainties inherent in the plant model and to those introduced by the ANN regression models used for performing the repeated safety parameter evaluations. The proposed framework of analysis is first illustrated with reference to a simple analytical model and then to the estimation of the safety margin on the maximum fuel cladding temperature reached during a complete group distribution header blockage scenario in a RBMK-1500 nuclear reactor. The results are compared with those obtained by a traditional parametric approach.
N=4 Superconformal Bootstrap of the K3 CFT
CERN. Geneva
2015-01-01
We study two-dimensional (4,4) superconformal field theories of central charge c=6, corresponding to nonlinear σ models on K3 surfaces, using the superconformal bootstrap. This is made possible through a surprising relation between the BPS N=4 superconformal blocks with c=6 and bosonic Virasoro conformal blocks with c=28, and an exact result on the moduli dependence of a certain integrated BPS 4-point function. Nontrivial bounds on the non-BPS spectrum in the K3 CFT are obtained as functions of the CFT moduli, that interpolate between the free orbifold points and singular CFT points. We observe directly from the CFT perspective the signature of a continuous spectrum above a gap at the singular moduli, and find numerically an upper bound on this gap that is saturated by the A1 N=4 cigar CFT. We also derive an analytic upper bound on the first nonzero eigenvalue of the scalar Laplacian on K3 in the large volume regime, that depends on the K3 moduli data. As two byproducts, we find an exact equivalence...
Statistical modelling in biostatistics and bioinformatics selected papers
Peng, Defen
2014-01-01
This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...
Barrera, Begoña Barrios; Figalli, Alessio; Valdinoci, Enrico
2012-01-01
We prove that $C^{1,\\alpha}$ $s$-minimal surfaces are automatically $C^\\infty$. For this, we develop a new bootstrap regularity theory for solutions of integro-differential equations of very general type, which we believe is of independent interest.
Reconstructing recent human phylogenies with forensic STR loci: A statistical approach
Directory of Open Access Journals (Sweden)
Khan Faisal
2005-09-01
Full Text Available Abstract Background Forensic Short Tandem Repeat (STR loci are effective for the purpose of individual identification, and other forensic applications. Most of these markers have high allelic variability and mutation rate because of which they have limited use in the phylogenetic reconstruction. In the present study, we have carried out a meta-analysis to explore the possibility of using only five STR loci (TPOX, FES, vWA, F13A and Tho1 to carry out phylogenetic assessment based on the allele frequency profile of 20 world population and north Indian Hindus analyzed in the present study. Results Phylogenetic analysis based on two different approaches – genetic distance and maximum likelihood along with statistical bootstrapping procedure involving 1000 replicates was carried out. The ensuing tree topologies and PC plots were further compared with those obtained in earlier phylogenetic investigations. The compiled database of 21 populations got segregated and finely resolved into three basal clusters with very high bootstrap values corresponding to three geo-ethnic groups of African, Orientals, and Caucasians. Conclusion Based on this study we conclude that if appropriate and logistic statistical approaches are followed then even lesser number of forensic STR loci are powerful enough to reconstruct the recent human phylogenies despite of their relatively high mutation rates.
Application of Robust Regression and Bootstrap in Poductivity Analysis of GERD Variable in EU27
Directory of Open Access Journals (Sweden)
Dagmar Blatná
2014-06-01
Full Text Available The GERD is one of Europe 2020 headline indicators being tracked within the Europe 2020 strategy. The headline indicator is the 3% target for the GERD to be reached within the EU by 2020. Eurostat defi nes “GERD” as total gross domestic expenditure on research and experimental development in a percentage of GDP. GERD depends on numerous factors of a general economic background, namely of employment, innovation and research, science and technology. The values of these indicators vary among the European countries, and consequently the occurrence of outliers can be anticipated in corresponding analyses. In such a case, a classical statistical approach – the least squares method – can be highly unreliable, the robust regression methods representing an acceptable and useful tool. The aim of the present paper is to demonstrate the advantages of robust regression and applicability of the bootstrap approach in regression based on both classical and robust methods.
Stochastic models for time series
Doukhan, Paul
2018-01-01
This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit ...
Are medical articles highlighting detailed statistics more cited?
Directory of Open Access Journals (Sweden)
Mike Thelwall
2015-06-01
Full Text Available When conducting a literature review, it is natural to search for articles and read their abstracts in order to select papers to read fully. Hence, informative abstracts are important to ensure that research is read. The description of a paper's methods may help to give confidence that a study is of high quality. This article assesses whether medical articles that mention three statistical methods, each of which is arguably indicative of a more detailed statistical analysis than average, are more highly cited. The results show that medical articles mentioning Bonferroni corrections, bootstrapping and effect size tend to be 7%, 8% and 15% more highly ranked for citations than average, respectively. Although this is consistent with the hypothesis that mentioning more detailed statistical techniques generate more highly cited research, these techniques may also tend to be used in more highly cited areas of Medicine.
Comparison of parametric and bootstrap method in bioequivalence test.
Ahn, Byung-Jin; Yim, Dong-Seok
2009-10-01
The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.
A Stochastic Fractional Dynamics Model of Rainfall Statistics
Kundu, Prasun; Travis, James
2013-04-01
Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is designed to faithfully reflect the scale dependence and is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. The main restriction is the assumption that the statistics of the precipitation field is spatially homogeneous and isotropic and stationary in time. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of the radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment. Some data sets containing periods of non-stationary behavior that involves occasional anomalously correlated rain events, present a challenge for the model.
On Current Drive and Wave Induced Bootstrap Current in Toroidal Plasmas
International Nuclear Information System (INIS)
Hellsten, T.; Johnson, T.
2008-01-01
A comprehensive treatment of wave-particle interactions in toroidal plasmas including collisional relaxation, applicable to heating or anomalous wave induced transport, has been obtained by using Monte Carlo operators satisfying quasi-neutrality. This approach enables a self-consistent treatment of wave-particle interactions applicable to the banana regime in the neoclassical theory. It allows an extension into a regime with large temperature and density gradients, losses and transport of particles by wave-particle interactions making the method applicable to transport barriers. It is found that at large gradients the relationship between radial electric field, parallel velocity, temperature and density gradient in the neoclassical theory is modified such that coefficient in front of the logarithmic ion temperature gradient, which in the standard neoclassical theory is small and counteracts the electric field caused by the density gradient, now changes sign and contributes to the built up of the radial electric field. The possibility to drive current by absorbing the waves on trapped particles has been studied and how the wave-particle interactions affect the bootstrap current. Two new current drive mechanisms are studied: current drive by wave induced bootstrap current and selective detrapping into passing orbits by directed waves.
Statistical Models and Methods for Lifetime Data
Lawless, Jerald F
2011-01-01
Praise for the First Edition"An indispensable addition to any serious collection on lifetime data analysis and . . . a valuable contribution to the statistical literature. Highly recommended . . ."-Choice"This is an important book, which will appeal to statisticians working on survival analysis problems."-Biometrics"A thorough, unified treatment of statistical models and methods used in the analysis of lifetime data . . . this is a highly competent and agreeable statistical textbook."-Statistics in MedicineThe statistical analysis of lifetime or response time data is a key tool in engineering,
Topology for Statistical Modeling of Petascale Data
Energy Technology Data Exchange (ETDEWEB)
Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States); Levine, Joshua [Univ. of Utah, Salt Lake City, UT (United States); Gyulassy, Attila [Univ. of Utah, Salt Lake City, UT (United States); Bremer, P. -T. [Univ. of Utah, Salt Lake City, UT (United States)
2013-10-31
Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, the approach of the entire team involving all three institutions is based on the complementary techniques of combinatorial topology and statistical modelling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modelling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. The overall technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modelling, and (3) new integrated topological and statistical methods. Roughly speaking, the division of labor between our 3 groups (Sandia Labs in Livermore, Texas A&M in College Station, and U Utah in Salt Lake City) is as follows: the Sandia group focuses on statistical methods and their formulation in algebraic terms, and finds the application problems (and data sets) most relevant to this project, the Texas A&M Group develops new algebraic geometry algorithms, in particular with fewnomial theory, and the Utah group develops new algorithms in computational topology via Discrete Morse Theory. However, we hasten to point out that our three groups stay in tight contact via videconference every 2 weeks, so there is much synergy of ideas between the groups. The following of this document is focused on the contributions that had grater direct involvement from the team at the University of Utah in Salt Lake City.
International Nuclear Information System (INIS)
Ozel, M.E.; Mayer-Hasselwander, H.
1985-01-01
This paper discusses the bootstrap scheme which fits well for many astronomical applications. It is based on the well-known sampling plan called ''sampling with replacement''. Digital computers make the method very practical for the investigation of various trends present in a limited set of data which is usually a small fraction of the total population. The authors attempt to apply the method and demonstrate its feasibility. The study indicates that the discrete nature of high energy gamma-ray data makes the bootstrap method especially attractive for gamma-ray astronomy. Present analysis shows that the ratio of pulse strengths is variable with a 99.8% confidence
Dekkers, G.J.M.; Nelissen, J.H.M.
2001-01-01
We look at the contribution of various income components on income inequality and the changes in this in Belgium.Starting from the Shorrocks decomposition, we apply bootstrapping to construct confidence intervals for both the annual decomposition and the changes over time.It appears that the
Statistical models and methods for reliability and survival analysis
Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo
2013-01-01
Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical
A Statistical Approach For Modeling Tropical Cyclones. Synthetic Hurricanes Generator Model
Energy Technology Data Exchange (ETDEWEB)
Pasqualini, Donatella [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-05-11
This manuscript brie y describes a statistical ap- proach to generate synthetic tropical cyclone tracks to be used in risk evaluations. The Synthetic Hur- ricane Generator (SynHurG) model allows model- ing hurricane risk in the United States supporting decision makers and implementations of adaptation strategies to extreme weather. In the literature there are mainly two approaches to model hurricane hazard for risk prediction: deterministic-statistical approaches, where the storm key physical parameters are calculated using physi- cal complex climate models and the tracks are usually determined statistically from historical data; and sta- tistical approaches, where both variables and tracks are estimated stochastically using historical records. SynHurG falls in the second category adopting a pure stochastic approach.
Model-generated air quality statistics for application in vegetation response models in Alberta
International Nuclear Information System (INIS)
McVehil, G.E.; Nosal, M.
1990-01-01
To test and apply vegetation response models in Alberta, air pollution statistics representative of various parts of the Province are required. At this time, air quality monitoring data of the requisite accuracy and time resolution are not available for most parts of Alberta. Therefore, there exists a need to develop appropriate air quality statistics. The objectives of the work reported here were to determine the applicability of model generated air quality statistics and to develop by modelling, realistic and representative time series of hourly SO 2 concentrations that could be used to generate the statistics demanded by vegetation response models
Performance modeling, loss networks, and statistical multiplexing
Mazumdar, Ravi
2009-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I
Steinberg, P. D.; Brener, G.; Duffy, D.; Nearing, G. S.; Pelissier, C.
2017-12-01
Hyperparameterization, of statistical models, i.e. automated model scoring and selection, such as evolutionary algorithms, grid searches, and randomized searches, can improve forecast model skill by reducing errors associated with model parameterization, model structure, and statistical properties of training data. Ensemble Learning Models (Elm), and the related Earthio package, provide a flexible interface for automating the selection of parameters and model structure for machine learning models common in climate science and land cover classification, offering convenient tools for loading NetCDF, HDF, Grib, or GeoTiff files, decomposition methods like PCA and manifold learning, and parallel training and prediction with unsupervised and supervised classification, clustering, and regression estimators. Continuum Analytics is using Elm to experiment with statistical soil moisture forecasting based on meteorological forcing data from NASA's North American Land Data Assimilation System (NLDAS). There Elm is using the NSGA-2 multiobjective optimization algorithm for optimizing statistical preprocessing of forcing data to improve goodness-of-fit for statistical models (i.e. feature engineering). This presentation will discuss Elm and its components, including dask (distributed task scheduling), xarray (data structures for n-dimensional arrays), and scikit-learn (statistical preprocessing, clustering, classification, regression), and it will show how NSGA-2 is being used for automate selection of soil moisture forecast statistical models for North America.
Statistical Models of Adaptive Immune populations
Sethna, Zachary; Callan, Curtis; Walczak, Aleksandra; Mora, Thierry
The availability of large (104-106 sequences) datasets of B or T cell populations from a single individual allows reliable fitting of complex statistical models for naïve generation, somatic selection, and hypermutation. It is crucial to utilize a probabilistic/informational approach when modeling these populations. The inferred probability distributions allow for population characterization, calculation of probability distributions of various hidden variables (e.g. number of insertions), as well as statistical properties of the distribution itself (e.g. entropy). In particular, the differences between the T cell populations of embryonic and mature mice will be examined as a case study. Comparing these populations, as well as proposed mixed populations, provides a concrete exercise in model creation, comparison, choice, and validation.
Tropical geometry of statistical models.
Pachter, Lior; Sturmfels, Bernd
2004-11-16
This article presents a unified mathematical framework for inference in graphical models, building on the observation that graphical models are algebraic varieties. From this geometric viewpoint, observations generated from a model are coordinates of a point in the variety, and the sum-product algorithm is an efficient tool for evaluating specific coordinates. Here, we address the question of how the solutions to various inference problems depend on the model parameters. The proposed answer is expressed in terms of tropical algebraic geometry. The Newton polytope of a statistical model plays a key role. Our results are applied to the hidden Markov model and the general Markov model on a binary tree.
Complex data modeling and computationally intensive methods for estimation and prediction
Secchi, Piercesare; Advances in Complex Data Modeling and Computational Methods in Statistics
2015-01-01
The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held...
12th Workshop on Stochastic Models, Statistics and Their Applications
Rafajłowicz, Ewaryst; Szajowski, Krzysztof
2015-01-01
This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.
Statistical Validation of Engineering and Scientific Models: Background
International Nuclear Information System (INIS)
Hills, Richard G.; Trucano, Timothy G.
1999-01-01
A tutorial is presented discussing the basic issues associated with propagation of uncertainty analysis and statistical validation of engineering and scientific models. The propagation of uncertainty tutorial illustrates the use of the sensitivity method and the Monte Carlo method to evaluate the uncertainty in predictions for linear and nonlinear models. Four example applications are presented; a linear model, a model for the behavior of a damped spring-mass system, a transient thermal conduction model, and a nonlinear transient convective-diffusive model based on Burger's equation. Correlated and uncorrelated model input parameters are considered. The model validation tutorial builds on the material presented in the propagation of uncertainty tutoriaI and uses the damp spring-mass system as the example application. The validation tutorial illustrates several concepts associated with the application of statistical inference to test model predictions against experimental observations. Several validation methods are presented including error band based, multivariate, sum of squares of residuals, and optimization methods. After completion of the tutorial, a survey of statistical model validation literature is presented and recommendations for future work are made
Conformal bootstrap, universality and gravitational scattering
Directory of Open Access Journals (Sweden)
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.
Multiple commodities in statistical microeconomics: Model and market
Baaquie, Belal E.; Yu, Miao; Du, Xin
2016-11-01
A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.
Statistical models for optimizing mineral exploration
International Nuclear Information System (INIS)
Wignall, T.K.; DeGeoffroy, J.
1987-01-01
The primary purpose of mineral exploration is to discover ore deposits. The emphasis of this volume is on the mathematical and computational aspects of optimizing mineral exploration. The seven chapters that make up the main body of the book are devoted to the description and application of various types of computerized geomathematical models. These chapters include: (1) the optimal selection of ore deposit types and regions of search, as well as prospecting selected areas, (2) designing airborne and ground field programs for the optimal coverage of prospecting areas, and (3) delineating and evaluating exploration targets within prospecting areas by means of statistical modeling. Many of these statistical programs are innovative and are designed to be useful for mineral exploration modeling. Examples of geomathematical models are applied to exploring for six main types of base and precious metal deposits, as well as other mineral resources (such as bauxite and uranium)
Bootstrapping quarks and gluons
Energy Technology Data Exchange (ETDEWEB)
Chew, G.F.
1979-04-01
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 quarks and gluons
International Nuclear Information System (INIS)
Chew, G.F.
1979-04-01
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
Flouri, Marilena; Zhai, Shuyan; Mathew, Thomas; Bebu, Ionut
2017-05-01
This paper addresses the problem of deriving one-sided tolerance limits and two-sided tolerance intervals for a ratio of two random variables that follow a bivariate normal distribution, or a lognormal/normal distribution. The methodology that is developed uses nonparametric tolerance limits based on a parametric bootstrap sample, coupled with a bootstrap calibration in order to improve accuracy. The methodology is also adopted for computing confidence limits for the median of the ratio random variable. Numerical results are reported to demonstrate the accuracy of the proposed approach. The methodology is illustrated using examples where ratio random variables are of interest: an example on the radioactivity count in reverse transcriptase assays and an example from the area of cost-effectiveness analysis in health economics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Check of the bootstrap conditions for the gluon Reggeization
International Nuclear Information System (INIS)
Papa, A.
2000-01-01
The property of gluon Reggeization plays an essential role in the derivation of the Balitsky-Fadin-Kuraev-Lipatov (BFKL) equation for the cross sections at high energy √s in perturbative QCD. This property has been proved to all orders of perturbation theory in the leading logarithmic approximation and it is assumed to be valid also in the next-to-leading logarithmic approximation, where it has been checked only to the first three orders of perturbation theory. From s-channel unitarity, however, very stringent 'bootstrap' conditions can be derived which, if fulfilled, leave no doubts that gluon Reggeization holds
A SQUID Bootstrap Circuit with a Large Parameter Tolerance
International Nuclear Information System (INIS)
Zhang Guo-Feng; Kong Xiang-Yan; Xie Xiao-Ming; Zhang Yi; Krause Hans-Joachim; Offenhäusser Andreas
2013-01-01
The voltage biased (SQUID) bootstrap circuit (SBC) was recently introduced as an effective means to reduce the preamplifier noise contribution. We analyze the tolerances of the SBC noise suppression performance to spreads in SQUID and SBC circuit parameters. It is found that the tolerance to spread mainly caused by the integrated circuit fabrication process could be extended by a one-time adjustable current feedback. A helium-cooled niobium SQUID with a loop inductance of 350 pH is employed to experimentally verify the analysis. From this work, design criteria for fully integrated SBC devices with a high yield can be derived
Robustness of S1 statistic with Hodges-Lehmann for skewed distributions
Ahad, Nor Aishah; Yahaya, Sharipah Soaad Syed; Yin, Lee Ping
2016-10-01
Analysis of variance (ANOVA) is a common use parametric method to test the differences in means for more than two groups when the populations are normally distributed. ANOVA is highly inefficient under the influence of non- normal and heteroscedastic settings. When the assumptions are violated, researchers are looking for alternative such as Kruskal-Wallis under nonparametric or robust method. This study focused on flexible method, S1 statistic for comparing groups using median as the location estimator. S1 statistic was modified by substituting the median with Hodges-Lehmann and the default scale estimator with the variance of Hodges-Lehmann and MADn to produce two different test statistics for comparing groups. Bootstrap method was used for testing the hypotheses since the sampling distributions of these modified S1 statistics are unknown. The performance of the proposed statistic in terms of Type I error was measured and compared against the original S1 statistic, ANOVA and Kruskal-Wallis. The propose procedures show improvement compared to the original statistic especially under extremely skewed distribution.
Calia, Clara; Darling, Stephen; Havelka, Jelena; Allen, Richard J
2018-05-01
Immediate serial recall of digits is better when the digits are shown by highlighting them in a familiar array, such as a phone keypad, compared with presenting them serially in a single location, a pattern referred to as "visuospatial bootstrapping." This pattern implies the establishment of temporary links between verbal and spatial working memory, alongside access to information in long-term memory. However, the role of working memory control processes like those implied by the "Central Executive" in bootstrapping has not been directly investigated. Here, we report a study addressing this issue, focusing on executive processes of attentional shifting. Tasks in which information has to be sequenced are thought to be heavily dependent on shifting. Memory for digits presented in keypads versus single locations was assessed under two secondary task load conditions, one with and one without a sequencing requirement, and hence differing in the degree to which they invoke shifting. Results provided clear evidence that multimodal binding (visuospatial bootstrapping) can operate independently of this form of executive control process.
Statistical physics of pairwise probability models
Directory of Open Access Journals (Sweden)
Yasser Roudi
2009-11-01
Full Text Available Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data: knowledge of the means and correlations between pairs of elements in the system is sufficient. Not surprisingly, then, using pairwise models for studying neural data has been the focus of many studies in recent years. In this paper, we describe how tools from statistical physics can be employed for studying and using pairwise models. We build on our previous work on the subject and study the relation between different methods for fitting these models and evaluating their quality. In particular, using data from simulated cortical networks we study how the quality of various approximate methods for inferring the parameters in a pairwise model depends on the time bin chosen for binning the data. We also study the effect of the size of the time bin on the model quality itself, again using simulated data. We show that using finer time bins increases the quality of the pairwise model. We offer new ways of deriving the expressions reported in our previous work for assessing the quality of pairwise models.
Sample Reuse in Statistical Remodeling.
1987-08-01
as the jackknife and bootstrap, is an expansion of the functional, T(Fn), or of its distribution function or both. Frangos and Schucany (1987a) used...accelerated bootstrap. In the same report Frangos and Schucany demonstrated the small sample superiority of that approach over the proposals that take...higher order terms of an Edgeworth expansion into account. In a second report Frangos and Schucany (1987b) examined the small sample performance of
Statistical transmutation in doped quantum dimer models.
Lamas, C A; Ralko, A; Cabra, D C; Poilblanc, D; Pujol, P
2012-07-06
We prove a "statistical transmutation" symmetry of doped quantum dimer models on the square, triangular, and kagome lattices: the energy spectrum is invariant under a simultaneous change of statistics (i.e., bosonic into fermionic or vice versa) of the holes and of the signs of all the dimer resonance loops. This exact transformation enables us to define the duality equivalence between doped quantum dimer Hamiltonians and provides the analytic framework to analyze dynamical statistical transmutations. We investigate numerically the doping of the triangular quantum dimer model with special focus on the topological Z(2) dimer liquid. Doping leads to four (instead of two for the square lattice) inequivalent families of Hamiltonians. Competition between phase separation, superfluidity, supersolidity, and fermionic phases is investigated in the four families.
Directory of Open Access Journals (Sweden)
Milenka Ocampo
2009-01-01
Full Text Available El presente trabajo muestra, en base a evidencia empírica, que las diferencias entre la educación pública y privada han acentuado en el tiempo la desigualdad de ingresos existente en Bolivia. Inicialmente, se realiza un análisis descriptivo de las diferencias en calidad, infraestructura y cobertura entre la educación pública y privada. Posteriormente, empleando técnicas microeconométricas y tests de hipótesis bajo Bootstrap, se verifica que las diferencias entre ambos tipos de educación son significativas para explicar una parte de la desigualdad de ingresos generada entre 1999 y 2006 en Bolivia. Adicionalmente, se aplican el método Bootstrap Moon para asegurar la robustez de los resultados.
Textual information access statistical models
Gaussier, Eric
2013-01-01
This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. The problems considered are linked to applications aiming at facilitating information access:- information extraction and retrieval;- text classification and clustering;- opinion mining;- comprehension aids (automatic summarization, machine translation, visualization).In order to give the reader as complete a description as possible, the focus is placed on the probability models used in the applications
Model for neural signaling leap statistics
International Nuclear Information System (INIS)
Chevrollier, Martine; Oria, Marcos
2011-01-01
We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5 0 C, awaken regime) and Levy statistics (T = 35.5 0 C, sleeping period), characterized by rare events of long range connections.
Model for neural signaling leap statistics
Chevrollier, Martine; Oriá, Marcos
2011-03-01
We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T = 37.5°C, awaken regime) and Lévy statistics (T = 35.5°C, sleeping period), characterized by rare events of long range connections.
Computational statistics and biometry: which discipline drives which?
Directory of Open Access Journals (Sweden)
Edler, Lutz
2005-06-01
Full Text Available A biometrician's work is defined through the biological or medical problem and the mathematical and statistical methods needed for its solution. This requires in most instances statistical data analysis and the use of methods of computational statistics. At first, it seems quite obvious that the computational needs of the biometric problem determine what has to be developed by the discipline of computational statistics. However, viewing the development of biometry and computational statistics in Germany for the past decades in more details reveals an interesting interaction between the activities of the German Region of the International Biometric Society and groups engaged in computational statistics within Germany. Exact methods of statistical inference and permutation tests, simulations and the use of the Bootstrap, and interactive graphical statistical methods are examples of this fruitful reciprocal benefit. This contribution examines therefore relationships between the historical development of biometry and computational statistics in Germany using as sources of information contributions to the scientific literature, presentations and sessions at scientific conferences on biometry and on computational statistics which influenced the development of both disciplines and exhibits a reciprocal dependency. The annual workshops organized on the Reisensburg now for more than 30 years are recognized as an outstanding factor of this interrelationship. This work aims at the definition of the present status of computational statistics in the German Region of the International Biometric Society and intends to guide and to foster the discussion of the future development of this discipline among biometricians.
WE-A-201-02: Modern Statistical Modeling
Energy Technology Data Exchange (ETDEWEB)
Niemierko, A.
2016-06-15
Chris Marshall: Memorial Introduction Donald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”. Don developed an interest in chemistry at school by “reading a book” - a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self-taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio-Statistics and Epidemiology Core Unit working in part on a sickle-cell disease. After retirement he remained active as Professor Emeritus. Don served for several years as a consultant to the Nuclear
WE-A-201-02: Modern Statistical Modeling
International Nuclear Information System (INIS)
Niemierko, A.
2016-01-01
Chris Marshall: Memorial Introduction Donald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”. Don developed an interest in chemistry at school by “reading a book” - a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self-taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio-Statistics and Epidemiology Core Unit working in part on a sickle-cell disease. After retirement he remained active as Professor Emeritus. Don served for several years as a consultant to the Nuclear
Bayesian models a statistical primer for ecologists
Hobbs, N Thompson
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili
A symbol of uniqueness: the cluster bootstrap for the 3-loop MHV heptagon
Energy Technology Data Exchange (ETDEWEB)
Drummond, J.M. [School of Physics & Astronomy, University of Southampton, Highfield, Southampton, SO17 1BJ (United Kingdom); Theory Division, Physics Department, CERN, CH-1211 Geneva 23 (Switzerland); LAPTh, CNRS, Université de Savoie, F-74941 Annecy-le-Vieux Cedex (France); Papathanasiou, G. [LAPTh, CNRS, Université de Savoie, F-74941 Annecy-le-Vieux Cedex (France); Spradlin, M. [Department of Physics, Brown University, Providence, RI 02912 (United States)
2015-03-16
Seven-particle scattering amplitudes in planar super-Yang-Mills theory are believed to belong to a special class of generalised polylogarithm functions called heptagon functions. These are functions with physical branch cuts whose symbols may be written in terms of the 42 cluster A-coordinates on Gr (4,7). Motivated by the success of the hexagon bootstrap programme for constructing six-particle amplitudes we initiate the systematic study of the symbols of heptagon functions. We find that there is exactly one such symbol of weight six which satisfies the MHV last-entry condition and is finite in the 7∥6 collinear limit. This unique symbol is both dihedral and parity-symmetric, and remarkably its collinear limit is exactly the symbol of the three-loop six-particle MHV amplitude, although none of these properties were assumed a priori. It must therefore be the symbol of the three-loop seven-particle MHV amplitude. The simplicity of its construction suggests that the n-gon bootstrap may be surprisingly powerful for n>6.
Boiret, Mathieu; Meunier, Loïc; Ginot, Yves-Michel
2011-02-20
A near infrared (NIR) method was developed for determination of tablet potency of active pharmaceutical ingredient (API) in a complex coated tablet matrix. The calibration set contained samples from laboratory and production scale batches. The reference values were obtained by high performance liquid chromatography (HPLC) and partial least squares (PLS) regression was used to establish a model. The model was challenged by calculating tablet potency of two external test sets. Root mean square errors of prediction were respectively equal to 2.0% and 2.7%. To use this model with a second spectrometer from the production field, a calibration transfer method called piecewise direct standardisation (PDS) was used. After the transfer, the root mean square error of prediction of the first test set was 2.4% compared to 4.0% without transferring the spectra. A statistical technique using bootstrap of PLS residuals was used to estimate confidence intervals of tablet potency calculations. This method requires an optimised PLS model, selection of the bootstrap number and determination of the risk. In the case of a chemical analysis, the tablet potency value will be included within the confidence interval calculated by the bootstrap method. An easy to use graphical interface was developed to easily determine if the predictions, surrounded by minimum and maximum values, are within the specifications defined by the regulatory organisation. Copyright © 2010 Elsevier B.V. All rights reserved.
arXiv The S-matrix Bootstrap II: Two Dimensional Amplitudes
Paulos, Miguel F.; Toledo, Jonathan; van Rees, Balt C.; Vieira, Pedro
2017-11-22
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.
International Nuclear Information System (INIS)
Painter, C.L.; Daly, D.S.; Welsh, T.L.
1996-09-01
Department of Energy contractors responsible for the safe operation of non-reactor nuclear facilities need to establish maximum inventory limits on both radioactive and hazardous materials stored, used, or processed at their facilities. These contractors need to ensure that established maximum limits are not exceeded. This necessity is derived from the requirement to demonstrate that a non-reactor facility can by safely operated during normal and abnormal conditions. The 222-S Laboratory has established that a maximum of 800 core equivalent samples (CES)may be stored at the Laboratory. Using the CES definition one can determine the maximum allowed curies pre radionuclide permitted. These estimates were made using a variation on a statistical technique called smoothed-bootstrapping. Smoothed- bootstrapping is a method analogous to Monte Carlo simulation using a smoothed empirical probability distribution. This report discusses the application of the smoothed bootstrap technique to predicting the curie inventory retained in the numerous waste tank samples for the radionuclides of concern and the uncertainty associated with such a prediction
Equilibrium statistical mechanics of lattice models
Lavis, David A
2015-01-01
Most interesting and difficult problems in equilibrium statistical mechanics concern models which exhibit phase transitions. For graduate students and more experienced researchers this book provides an invaluable reference source of approximate and exact solutions for a comprehensive range of such models. Part I contains background material on classical thermodynamics and statistical mechanics, together with a classification and survey of lattice models. The geometry of phase transitions is described and scaling theory is used to introduce critical exponents and scaling laws. An introduction is given to finite-size scaling, conformal invariance and Schramm—Loewner evolution. Part II contains accounts of classical mean-field methods. The parallels between Landau expansions and catastrophe theory are discussed and Ginzburg—Landau theory is introduced. The extension of mean-field theory to higher-orders is explored using the Kikuchi—Hijmans—De Boer hierarchy of approximations. In Part III the use of alge...
Computational and Statistical Models: A Comparison for Policy Modeling of Childhood Obesity
Mabry, Patricia L.; Hammond, Ross; Ip, Edward Hak-Sing; Huang, Terry T.-K.
As systems science methodologies have begun to emerge as a set of innovative approaches to address complex problems in behavioral, social science, and public health research, some apparent conflicts with traditional statistical methodologies for public health have arisen. Computational modeling is an approach set in context that integrates diverse sources of data to test the plausibility of working hypotheses and to elicit novel ones. Statistical models are reductionist approaches geared towards proving the null hypothesis. While these two approaches may seem contrary to each other, we propose that they are in fact complementary and can be used jointly to advance solutions to complex problems. Outputs from statistical models can be fed into computational models, and outputs from computational models can lead to further empirical data collection and statistical models. Together, this presents an iterative process that refines the models and contributes to a greater understanding of the problem and its potential solutions. The purpose of this panel is to foster communication and understanding between statistical and computational modelers. Our goal is to shed light on the differences between the approaches and convey what kinds of research inquiries each one is best for addressing and how they can serve complementary (and synergistic) roles in the research process, to mutual benefit. For each approach the panel will cover the relevant "assumptions" and how the differences in what is assumed can foster misunderstandings. The interpretations of the results from each approach will be compared and contrasted and the limitations for each approach will be delineated. We will use illustrative examples from CompMod, the Comparative Modeling Network for Childhood Obesity Policy. The panel will also incorporate interactive discussions with the audience on the issues raised here.
Kleibergen, F.R.
2003-01-01
We show that the sensitivity of the limit distribution of commonly used GMM statistics to weak and many instruments results from superfluous elements in the higher order expansion of these statistics. When the instruments are strong and their number is small, these elements are of higher order and
Spherical Process Models for Global Spatial Statistics
Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.
2017-01-01
Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture
Model for neural signaling leap statistics
Energy Technology Data Exchange (ETDEWEB)
Chevrollier, Martine; Oria, Marcos, E-mail: oria@otica.ufpb.br [Laboratorio de Fisica Atomica e Lasers Departamento de Fisica, Universidade Federal da ParaIba Caixa Postal 5086 58051-900 Joao Pessoa, Paraiba (Brazil)
2011-03-01
We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5{sup 0}C, awaken regime) and Levy statistics (T = 35.5{sup 0}C, sleeping period), characterized by rare events of long range connections.
Analysis and Evaluation of Statistical Models for Integrated Circuits Design
Directory of Open Access Journals (Sweden)
Sáenz-Noval J.J.
2011-10-01
Full Text Available Statistical models for integrated circuits (IC allow us to estimate the percentage of acceptable devices in the batch before fabrication. Actually, Pelgrom is the statistical model most accepted in the industry; however it was derived from a micrometer technology, which does not guarantee reliability in nanometric manufacturing processes. This work considers three of the most relevant statistical models in the industry and evaluates their limitations and advantages in analog design, so that the designer has a better criterion to make a choice. Moreover, it shows how several statistical models can be used for each one of the stages and design purposes.
Bootstrap Dynamical Symmetry Breaking
Directory of Open Access Journals (Sweden)
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.
A Modified Jonckheere Test Statistic for Ordered Alternatives in Repeated Measures Design
Directory of Open Access Journals (Sweden)
Hatice Tül Kübra AKDUR
2016-09-01
Full Text Available In this article, a new test based on Jonckheere test [1] for randomized blocks which have dependent observations within block is presented. A weighted sum for each block statistic rather than the unweighted sum proposed by Jonckheereis included. For Jonckheere type statistics, the main assumption is independency of observations within block. In the case of repeated measures design, the assumption of independence is violated. The weighted Jonckheere type statistic for the situation of dependence for different variance-covariance structure and the situation based on ordered alternative hypothesis structure of each block on the design is used. Also, the proposed statistic is compared to the existing test based on Jonckheere in terms of type I error rates by performing Monte Carlo simulation. For the strong correlations, circular bootstrap version of the proposed Jonckheere test provides lower rates of type I error.
The issue of statistical power for overall model fit in evaluating structural equation models
Directory of Open Access Journals (Sweden)
Richard HERMIDA
2015-06-01
Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.
Understanding and forecasting polar stratospheric variability with statistical models
Directory of Open Access Journals (Sweden)
C. Blume
2012-07-01
Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely the multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. The period from 2005 to 2011 can be hindcasted to a certain extent, where MLP performs significantly better than the remaining models. However, variability remains that cannot be statistically hindcasted within the current framework, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a winter 2011/12 with warm and weak vortex conditions. A vortex breakdown is predicted for late January, early February 2012.
Improved model for statistical alignment
Energy Technology Data Exchange (ETDEWEB)
Miklos, I.; Toroczkai, Z. (Zoltan)
2001-01-01
The statistical approach to molecular sequence evolution involves the stochastic modeling of the substitution, insertion and deletion processes. Substitution has been modeled in a reliable way for more than three decades by using finite Markov-processes. Insertion and deletion, however, seem to be more difficult to model, and thc recent approaches cannot acceptably deal with multiple insertions and deletions. A new method based on a generating function approach is introduced to describe the multiple insertion process. The presented algorithm computes the approximate joint probability of two sequences in 0(13) running time where 1 is the geometric mean of the sequence lengths.
Daily precipitation statistics in regional climate models
DEFF Research Database (Denmark)
Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel
2003-01-01
An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...
Infinite Random Graphs as Statistical Mechanical Models
DEFF Research Database (Denmark)
Durhuus, Bergfinnur Jøgvan; Napolitano, George Maria
2011-01-01
We discuss two examples of infinite random graphs obtained as limits of finite statistical mechanical systems: a model of two-dimensional dis-cretized quantum gravity defined in terms of causal triangulated surfaces, and the Ising model on generic random trees. For the former model we describe a ...
An R2 statistic for fixed effects in the linear mixed model.
Edwards, Lloyd J; Muller, Keith E; Wolfinger, Russell D; Qaqish, Bahjat F; Schabenberger, Oliver
2008-12-20
Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data. The value and familiarity of the R(2) statistic in the linear univariate model naturally creates great interest in extending it to the linear mixed model. We define and describe how to compute a model R(2) statistic for the linear mixed model by using only a single model. The proposed R(2) statistic measures multivariate association between the repeated outcomes and the fixed effects in the linear mixed model. The R(2) statistic arises as a 1-1 function of an appropriate F statistic for testing all fixed effects (except typically the intercept) in a full model. The statistic compares the full model with a null model with all fixed effects deleted (except typically the intercept) while retaining exactly the same covariance structure. Furthermore, the R(2) statistic leads immediately to a natural definition of a partial R(2) statistic. A mixed model in which ethnicity gives a very small p-value as a longitudinal predictor of blood pressure (BP) compellingly illustrates the value of the statistic. In sharp contrast to the extreme p-value, a very small R(2) , a measure of statistical and scientific importance, indicates that ethnicity has an almost negligible association with the repeated BP outcomes for the study.
PCA-based bootstrap confidence interval tests for gene-disease association involving multiple SNPs
Directory of Open Access Journals (Sweden)
Xue Fuzhong
2010-01-01
Full Text Available Abstract Background Genetic association study is currently the primary vehicle for identification and characterization of disease-predisposing variant(s which usually involves multiple single-nucleotide polymorphisms (SNPs available. However, SNP-wise association tests raise concerns over multiple testing. Haplotype-based methods have the advantage of being able to account for correlations between neighbouring SNPs, yet assuming Hardy-Weinberg equilibrium (HWE and potentially large number degrees of freedom can harm its statistical power and robustness. Approaches based on principal component analysis (PCA are preferable in this regard but their performance varies with methods of extracting principal components (PCs. Results PCA-based bootstrap confidence interval test (PCA-BCIT, which directly uses the PC scores to assess gene-disease association, was developed and evaluated for three ways of extracting PCs, i.e., cases only(CAES, controls only(COES and cases and controls combined(CES. Extraction of PCs with COES is preferred to that with CAES and CES. Performance of the test was examined via simulations as well as analyses on data of rheumatoid arthritis and heroin addiction, which maintains nominal level under null hypothesis and showed comparable performance with permutation test. Conclusions PCA-BCIT is a valid and powerful method for assessing gene-disease association involving multiple SNPs.
Mixed deterministic statistical modelling of regional ozone air pollution
Kalenderski, Stoitchko
2011-03-17
We develop a physically motivated statistical model for regional ozone air pollution by separating the ground-level pollutant concentration field into three components, namely: transport, local production and large-scale mean trend mostly dominated by emission rates. The model is novel in the field of environmental spatial statistics in that it is a combined deterministic-statistical model, which gives a new perspective to the modelling of air pollution. The model is presented in a Bayesian hierarchical formalism, and explicitly accounts for advection of pollutants, using the advection equation. We apply the model to a specific case of regional ozone pollution-the Lower Fraser valley of British Columbia, Canada. As a predictive tool, we demonstrate that the model vastly outperforms existing, simpler modelling approaches. Our study highlights the importance of simultaneously considering different aspects of an air pollution problem as well as taking into account the physical bases that govern the processes of interest. © 2011 John Wiley & Sons, Ltd..
Adaptive Maneuvering Frequency Method of Current Statistical Model
Institute of Scientific and Technical Information of China (English)
Wei Sun; Yongjian Yang
2017-01-01
Current statistical model(CSM) has a good performance in maneuvering target tracking. However, the fixed maneuvering frequency will deteriorate the tracking results, such as a serious dynamic delay, a slowly converging speedy and a limited precision when using Kalman filter(KF) algorithm. In this study, a new current statistical model and a new Kalman filter are proposed to improve the performance of maneuvering target tracking. The new model which employs innovation dominated subjection function to adaptively adjust maneuvering frequency has a better performance in step maneuvering target tracking, while a fluctuant phenomenon appears. As far as this problem is concerned, a new adaptive fading Kalman filter is proposed as well. In the new Kalman filter, the prediction values are amended in time by setting judgment and amendment rules,so that tracking precision and fluctuant phenomenon of the new current statistical model are improved. The results of simulation indicate the effectiveness of the new algorithm and the practical guiding significance.
Speech emotion recognition based on statistical pitch model
Institute of Scientific and Technical Information of China (English)
WANG Zhiping; ZHAO Li; ZOU Cairong
2006-01-01
A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech.The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85%if the traditional parameters are utilized.
Statistical modelling of citation exchange between statistics journals.
Varin, Cristiano; Cattelan, Manuela; Firth, David
2016-01-01
Rankings of scholarly journals based on citation data are often met with scepticism by the scientific community. Part of the scepticism is due to disparity between the common perception of journals' prestige and their ranking based on citation counts. A more serious concern is the inappropriate use of journal rankings to evaluate the scientific influence of researchers. The paper focuses on analysis of the table of cross-citations among a selection of statistics journals. Data are collected from the Web of Science database published by Thomson Reuters. Our results suggest that modelling the exchange of citations between journals is useful to highlight the most prestigious journals, but also that journal citation data are characterized by considerable heterogeneity, which needs to be properly summarized. Inferential conclusions require care to avoid potential overinterpretation of insignificant differences between journal ratings. Comparison with published ratings of institutions from the UK's research assessment exercise shows strong correlation at aggregate level between assessed research quality and journal citation 'export scores' within the discipline of statistics.
Statistical validation of normal tissue complication probability models.
Xu, Cheng-Jian; van der Schaaf, Arjen; Van't Veld, Aart A; Langendijk, Johannes A; Schilstra, Cornelis
2012-09-01
To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use. Copyright © 2012 Elsevier Inc. All rights reserved.
Statistical Validation of Normal Tissue Complication Probability Models
Energy Technology Data Exchange (ETDEWEB)
Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Veld, Aart A. van' t; Langendijk, Johannes A. [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schilstra, Cornelis [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Radiotherapy Institute Friesland, Leeuwarden (Netherlands)
2012-09-01
Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.
Shell model in large spaces and statistical spectroscopy
International Nuclear Information System (INIS)
Kota, V.K.B.
1996-01-01
For many nuclear structure problems of current interest it is essential to deal with shell model in large spaces. For this, three different approaches are now in use and two of them are: (i) the conventional shell model diagonalization approach but taking into account new advances in computer technology; (ii) the shell model Monte Carlo method. A brief overview of these two methods is given. Large space shell model studies raise fundamental questions regarding the information content of the shell model spectrum of complex nuclei. This led to the third approach- the statistical spectroscopy methods. The principles of statistical spectroscopy have their basis in nuclear quantum chaos and they are described (which are substantiated by large scale shell model calculations) in some detail. (author)
Advances in statistical models for data analysis
Minerva, Tommaso; Vichi, Maurizio
2015-01-01
This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.
Computationally efficient statistical differential equation modeling using homogenization
Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.
2013-01-01
Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.
Fluctuations and correlations in statistical models of hadron production
International Nuclear Information System (INIS)
Gorenstein, M. I.
2012-01-01
An extension of the standard concept of the statistical ensembles is suggested. Namely, the statistical ensembles with extensive quantities fluctuating according to an externally given distribution are introduced. Applications in the statistical models of multiple hadron production in high energy physics are discussed.
DEFF Research Database (Denmark)
Davis, Jerrold I.; Stevenson, Dennis W.; Petersen, Gitte
2004-01-01
elements of Xyridaceae. A comparison was conducted of jackknife and bootstrap values, as computed using strict-consensus (SC) and frequency-within-replicates (FWR) approaches. Jackknife values tend to be higher than bootstrap values, and for each of these methods support values obtained with the FWR...
Growth curve models and statistical diagnostics
Pan, Jian-Xin
2002-01-01
Growth-curve models are generalized multivariate analysis-of-variance models. These models are especially useful for investigating growth problems on short times in economics, biology, medical research, and epidemiology. This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. The authors provide complete proofs of theorems as well as practical data sets and MATLAB code.
Explanation of Two Anomalous Results in Statistical Mediation Analysis
Fritz, Matthew S.; Taylor, Aaron B.; MacKinnon, David P.
2012-01-01
Previous studies of different methods of testing mediation models have consistently found two anomalous results. The first result is elevated Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap tests not found in nonresampling tests or in resampling tests that did not include a bias correction. This is of special…
Advanced data analysis in neuroscience integrating statistical and computational models
Durstewitz, Daniel
2017-01-01
This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerfu...
On the optimization of a steady-state bootstrap-reactor
International Nuclear Information System (INIS)
Polevoy, A.R.; Martynov, A.A.; Medvedev, S.Yu.
1993-01-01
A commercial fusion tokamak-reactor may be economically acceptable only for low recirculating power fraction r 0 ≡ P CD /P α BS ≡I BS /I > 0.9 to sustain the steady-state operation mode for high plasma densities > 1.5 10 20 m -3 , fulfilled the divertor conditions. This paper presents the approximate expressions for the optimal set of reactor parameters for r BS /I∼1, based on the self-consistent plasma simulations by 1.5D ASTRA code. The linear MHD stability analysis for ideal n=1 kink and ballooning modes has been carried out to determine the conditions of stabilization for bootstrap steady state tokamak reactor BSSTR configurations. (author) 10 refs., 1 tab
A Bootstrap Approach to Computing Uncertainty in Inferred Oil and Gas Reserve Estimates
International Nuclear Information System (INIS)
Attanasi, Emil D.; Coburn, Timothy C.
2004-01-01
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
Borsboom, D.; Haig, B.D.
2013-01-01
Unlike most other statistical frameworks, Bayesian statistical inference is wedded to a particular approach in the philosophy of science (see Howson & Urbach, 2006); this approach is called Bayesianism. Rather than being concerned with model fitting, this position in the philosophy of science
Direct measurement of fast transients by using boot-strapped waveform averaging
Olsson, Mattias; Edman, Fredrik; Karki, Khadga Jung
2018-03-01
An approximation to coherent sampling, also known as boot-strapped waveform averaging, is presented. The method uses digital cavities to determine the condition for coherent sampling. It can be used to increase the effective sampling rate of a repetitive signal and the signal to noise ratio simultaneously. The method is demonstrated by using it to directly measure the fluorescence lifetime from Rhodamine 6G by digitizing the signal from a fast avalanche photodiode. The obtained lifetime of 4.0 ns is in agreement with the known values.
Cellular automata and statistical mechanical models
International Nuclear Information System (INIS)
Rujan, P.
1987-01-01
The authors elaborate on the analogy between the transfer matrix of usual lattice models and the master equation describing the time development of cellular automata. Transient and stationary properties of probabilistic automata are linked to surface and bulk properties, respectively, of restricted statistical mechanical systems. It is demonstrated that methods of statistical physics can be successfully used to describe the dynamic and the stationary behavior of such automata. Some exact results are derived, including duality transformations, exact mappings, disorder, and linear solutions. Many examples are worked out in detail to demonstrate how to use statistical physics in order to construct cellular automata with desired properties. This approach is considered to be a first step toward the design of fully parallel, probabilistic systems whose computational abilities rely on the cooperative behavior of their components
Directory of Open Access Journals (Sweden)
C. B. Alden
2018-03-01
Full Text Available Advances in natural gas extraction technology have led to increased activity in the production and transport sectors in the United States and, as a consequence, an increased need for reliable monitoring of methane leaks to the atmosphere. We present a statistical methodology in combination with an observing system for the detection and attribution of fugitive emissions of methane from distributed potential source location landscapes such as natural gas production sites. We measure long (> 500 m, integrated open-path concentrations of atmospheric methane using a dual frequency comb spectrometer and combine measurements with an atmospheric transport model to infer leak locations and strengths using a novel statistical method, the non-zero minimum bootstrap (NZMB. The new statistical method allows us to determine whether the empirical distribution of possible source strengths for a given location excludes zero. Using this information, we identify leaking source locations (i.e., natural gas wells through rejection of the null hypothesis that the source is not leaking. The method is tested with a series of synthetic data inversions with varying measurement density and varying levels of model–data mismatch. It is also tested with field observations of (1 a non-leaking source location and (2 a source location where a controlled emission of 3.1 × 10−5 kg s−1 of methane gas is released over a period of several hours. This series of synthetic data tests and outdoor field observations using a controlled methane release demonstrates the viability of the approach for the detection and sizing of very small leaks of methane across large distances (4+ km2 in synthetic tests. The field tests demonstrate the ability to attribute small atmospheric enhancements of 17 ppb to the emitting source location against a background of combined atmospheric (e.g., background methane variability and measurement uncertainty of 5 ppb (1σ, when
Analytic bounds and emergence of AdS{sub 2} physics from the conformal bootstrap
Energy Technology Data Exchange (ETDEWEB)
Mazáč, Dalimil [Perimeter Institute for Theoretical Physics,Waterloo, ON N2L 2Y5 (Canada); Department of Physics and Astronomy, University of Waterloo,ON N2L 3G1 (Canada)
2017-04-26
We study analytically the constraints of the conformal bootstrap on the low-lying spectrum of operators in field theories with global conformal symmetry in one and two spacetime dimensions. We introduce a new class of linear functionals acting on the conformal bootstrap equation. In 1D, we use the new basis to construct extremal functionals leading to the optimal upper bound on the gap above identity in the OPE of two identical primary operators of integer or half-integer scaling dimension. We also prove an upper bound on the twist gap in 2D theories with global conformal symmetry. When the external scaling dimensions are large, our functionals provide a direct point of contact between crossing in a 1D CFT and scattering of massive particles in large AdS{sub 2}. In particular, CFT crossing can be shown to imply that appropriate OPE coefficients exhibit an exponential suppression characteristic of massive bound states, and that the 2D flat-space S-matrix should be analytic away from the real axis.
Growth Curve Models and Applications : Indian Statistical Institute
2017-01-01
Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas. There is no one-size-fits-all approach to growth measurement. The selected papers in this volume build on presentations from the GCM workshop held at the Indian Statistical Institute, Giridih, on March 28-29, 2016. They represent recent trends in GCM research on different subject areas, both theoretical and applied. This book includes tools and possibilities for further work through new techniques and modification of existing ones. The volume includes original studies, theoretical findings and case studies from a wide range of app lied work, and these contributions have been externally r...
Improving statistical reasoning theoretical models and practical implications
Sedlmeier, Peter
1999-01-01
This book focuses on how statistical reasoning works and on training programs that can exploit people''s natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications are traced in a neural network model of human performance on statistical reasoning problems. This book apppeals to judgment and decision making researchers and other cognitive scientists, as well as to teachers of statistics and probabilistic reasoning.
Improved Correction of Misclassification Bias With Bootstrap Imputation.
van Walraven, Carl
2018-07-01
Diagnostic codes used in administrative database research can create bias due to misclassification. Quantitative bias analysis (QBA) can correct for this bias, requires only code sensitivity and specificity, but may return invalid results. Bootstrap imputation (BI) can also address misclassification bias but traditionally requires multivariate models to accurately estimate disease probability. This study compared misclassification bias correction using QBA and BI. Serum creatinine measures were used to determine severe renal failure status in 100,000 hospitalized patients. Prevalence of severe renal failure in 86 patient strata and its association with 43 covariates was determined and compared with results in which renal failure status was determined using diagnostic codes (sensitivity 71.3%, specificity 96.2%). Differences in results (misclassification bias) were then corrected with QBA or BI (using progressively more complex methods to estimate disease probability). In total, 7.4% of patients had severe renal failure. Imputing disease status with diagnostic codes exaggerated prevalence estimates [median relative change (range), 16.6% (0.8%-74.5%)] and its association with covariates [median (range) exponentiated absolute parameter estimate difference, 1.16 (1.01-2.04)]. QBA produced invalid results 9.3% of the time and increased bias in estimates of both disease prevalence and covariate associations. BI decreased misclassification bias with increasingly accurate disease probability estimates. QBA can produce invalid results and increase misclassification bias. BI avoids invalid results and can importantly decrease misclassification bias when accurate disease probability estimates are used.
Statistical Inference on the Canadian Middle Class
Directory of Open Access Journals (Sweden)
Russell Davidson
2018-03-01
Full Text Available Conventional wisdom says that the middle classes in many developed countries have recently suffered losses, in terms of both the share of the total population belonging to the middle class, and also their share in total income. Here, distribution-free methods are developed for inference on these shares, by means of deriving expressions for their asymptotic variances of sample estimates, and the covariance of the estimates. Asymptotic inference can be undertaken based on asymptotic normality. Bootstrap inference can be expected to be more reliable, and appropriate bootstrap procedures are proposed. As an illustration, samples of individual earnings drawn from Canadian census data are used to test various hypotheses about the middle-class shares, and confidence intervals for them are computed. It is found that, for the earlier censuses, sample sizes are large enough for asymptotic and bootstrap inference to be almost identical, but that, in the twenty-first century, the bootstrap fails on account of a strange phenomenon whereby many presumably different incomes in the data are rounded to one and the same value. Another difference between the centuries is the appearance of heavy right-hand tails in the income distributions of both men and women.
Solar radiation data - statistical analysis and simulation models
Energy Technology Data Exchange (ETDEWEB)
Mustacchi, C; Cena, V; Rocchi, M; Haghigat, F
1984-01-01
The activities consisted in collecting meteorological data on magnetic tape for ten european locations (with latitudes ranging from 42/sup 0/ to 56/sup 0/ N), analysing the multi-year sequences, developing mathematical models to generate synthetic sequences having the same statistical properties of the original data sets, and producing one or more Short Reference Years (SRY's) for each location. The meteorological parameters examinated were (for all the locations) global + diffuse radiation on horizontal surface, dry bulb temperature, sunshine duration. For some of the locations additional parameters were available, namely, global, beam and diffuse radiation on surfaces other than horizontal, wet bulb temperature, wind velocity, cloud type, cloud cover. The statistical properties investigated were mean, variance, autocorrelation, crosscorrelation with selected parameters, probability density function. For all the meteorological parameters, various mathematical models were built: linear regression, stochastic models of the AR and the DAR type. In each case, the model with the best statistical behaviour was selected for the production of a SRY for the relevant parameter/location.
Statistical Model Checking for Biological Systems
DEFF Research Database (Denmark)
David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel
2014-01-01
Statistical Model Checking (SMC) is a highly scalable simulation-based verification approach for testing and estimating the probability that a stochastic system satisfies a given linear temporal property. The technique has been applied to (discrete and continuous time) Markov chains, stochastic...
Right-sizing statistical models for longitudinal data.
Wood, Phillip K; Steinley, Douglas; Jackson, Kristina M
2015-12-01
Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to "right-size" the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting, overly parsimonious models to more complex, better-fitting alternatives and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically underidentified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A 3-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation-covariation patterns. The orthogonal free curve slope intercept (FCSI) growth model is considered a general model that includes, as special cases, many models, including the factor mean (FM) model (McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, hierarchical linear models (HLMs), repeated-measures multivariate analysis of variance (MANOVA), and the linear slope intercept (linearSI) growth model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparing several candidate parametric growth and chronometric models in a Monte Carlo study. (c) 2015 APA, all rights reserved).
Statistical models based on conditional probability distributions
International Nuclear Information System (INIS)
Narayanan, R.S.
1991-10-01
We present a formulation of statistical mechanics models based on conditional probability distribution rather than a Hamiltonian. We show that it is possible to realize critical phenomena through this procedure. Closely linked with this formulation is a Monte Carlo algorithm, in which a configuration generated is guaranteed to be statistically independent from any other configuration for all values of the parameters, in particular near the critical point. (orig.)
A statistical model for mapping morphological shape
Directory of Open Access Journals (Sweden)
Li Jiahan
2010-07-01
Full Text Available Abstract Background Living things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine. Results We derived a statistical model for mapping specific genes or quantitative trait loci (QTLs that control morphological shape. The model was formulated within the mixture framework, in which different types of shape are thought to result from genotypic discrepancies at a QTL. The EM algorithm was implemented to estimate QTL genotype-specific shapes based on a shape correspondence analysis. Computer simulation was used to investigate the statistical property of the model. Conclusion By identifying specific QTLs for morphological shape, the model developed will help to ask, disseminate and address many major integrative biological and genetic questions and challenges in the genetic control of biological shape and function.
A condition for small bootstrap current in three-dimensional toroidal configurations
Energy Technology Data Exchange (ETDEWEB)
Mikhailov, M. I., E-mail: mikhaylov-mi@nrcki.ru [National Russian Research Center Kurchatov Institute (Russian Federation); Nührenberg, J.; Zille, R. [Max-Planck-Institut für Plasmaphysik (Germany)
2016-11-15
It is shown that, if the maximum of the magnetic field strength on a magnetic surface in a threedimensional magnetic confinement configuration with stellarator symmetry constitutes a line that is orthogonal to the field lines and crosses the symmetry line, then the bootstrap current density is smaller compared to that in quasi-axisymmetric (qa) [J. Nührenberg et al., in Proc. of Joint Varenna−Lausanne Int. Workshop on Theory of Fusion Plasmas, Varenna, 1994, p. 3] and quasi-helically (qh) symmetric [J. Nührenberg and R. Zille, Phys. Lett. A 129, 113 (1988)] configurations.
Bootstrap finance: the art of start-ups.
Bhide, A
1992-01-01
Entrepreneurship is more popular than ever: courses are full, policymakers emphasize new ventures, managers yearn to go off on their own. Would-be founders often misplace their energies, however. Believing in a "big money" model of entrepreneurship, they spend a lot of time trying to attract investors instead of using wits and hustle to get their ideas off the ground. A study of 100 of the 1989 Inc. "500" list of fastest growing U.S. start-ups attests to the value of bootstrapping. In fact, what it takes to start a business often conflicts with what venture capitalists require. Investors prefer solid plans, well-defined markets, and track records. Entrepreneurs are heavy on energy and enthusiasm but may be short on credentials. They thrive in rapidly changing environments where uncertain prospects may scare off established companies. Rolling with the punches is often more important than formal plans. Striving to adhere to investors' criteria can diminish the flexibility--the try-it, fix-it approach--an entrepreneur needs to make a new venture work. Seven principles are basic for successful start-ups: get operational fast; look for quick break-even, cash-generating projects; offer high-value products or services that can sustain direct personal selling; don't try to hire the crack team; keep growth in check; focus on cash; and cultivate banks early. Growth and change are the start-up's natural environment. But change is also the reward for success: just as ventures grow, their founders usually have to take a fresh look at everything again: roles, organization, even the very policies that got the business up and running.
Statistics of weighted Poisson events and its applications
International Nuclear Information System (INIS)
Bohm, G.; Zech, G.
2014-01-01
The statistics of the sum of random weights where the number of weights is Poisson distributed has important applications in nuclear physics, particle physics and astrophysics. Events are frequently weighted according to their acceptance or relevance to a certain type of reaction. The sum is described by the compound Poisson distribution (CPD) which is shortly reviewed. It is shown that the CPD can be approximated by a scaled Poisson distribution (SPD). The SPD is applied to parameter estimation in situations where the data are distorted by resolution effects. It performs considerably better than the normal approximation that is usually used. A special Poisson bootstrap technique is presented which permits to derive confidence limits for observations following the CPD
Statistical model selection with “Big Data”
Directory of Open Access Journals (Sweden)
Jurgen A. Doornik
2015-12-01
Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.
Statistical shape and appearance models of bones.
Sarkalkan, Nazli; Weinans, Harrie; Zadpoor, Amir A
2014-03-01
When applied to bones, statistical shape models (SSM) and statistical appearance models (SAM) respectively describe the mean shape and mean density distribution of bones within a certain population as well as the main modes of variations of shape and density distribution from their mean values. The availability of this quantitative information regarding the detailed anatomy of bones provides new opportunities for diagnosis, evaluation, and treatment of skeletal diseases. The potential of SSM and SAM has been recently recognized within the bone research community. For example, these models have been applied for studying the effects of bone shape on the etiology of osteoarthritis, improving the accuracy of clinical osteoporotic fracture prediction techniques, design of orthopedic implants, and surgery planning. This paper reviews the main concepts, methods, and applications of SSM and SAM as applied to bone. Copyright © 2013 Elsevier Inc. All rights reserved.
Statistical models and NMR analysis of polymer microstructure
Statistical models can be used in conjunction with NMR spectroscopy to study polymer microstructure and polymerization mechanisms. Thus, Bernoullian, Markovian, and enantiomorphic-site models are well known. Many additional models have been formulated over the years for additional situations. Typica...
N=4 superconformal bootstrap of the K3 CFT
Energy Technology Data Exchange (ETDEWEB)
Lin, Ying-Hsuan; Shao, Shu-Heng [Jefferson Physical Laboratory, Harvard University,17 Oxford Street, Cambridge, MA 02138 (United States); Simmons-Duffin, David [School of Natural Sciences, Institute for Advanced Study,1 Einstein Drive, Princeton, NJ 08540 (United States); Wang, Yifan [Center for Theoretical Physics, Massachusetts Institute of Technology,77 Massachusetts Ave, Cambridge, MA 02139 (United States); Yin, Xi [Jefferson Physical Laboratory, Harvard University,17 Oxford Street, Cambridge, MA 02138 (United States)
2017-05-23
We study two-dimensional (4,4) superconformal field theories of central charge c=6, corresponding to nonlinear sigma models on K3 surfaces, using the superconformal bootstrap. This is made possible through a surprising relation between the BPS N=4 superconformal blocks with c=6 and bosonic Virasoro conformal blocks with c=28, and an exact result on the moduli dependence of a certain integrated BPS 4-point function. Nontrivial bounds on the non-BPS spectrum in the K3 CFT are obtained as functions of the CFT moduli, that interpolate between the free orbifold points and singular CFT points. We observe directly from the CFT perspective the signature of a continuous spectrum above a gap at the singular moduli, and find numerically an upper bound on this gap that is saturated by the A{sub 1}N=4 cigar CFT. We also derive an analytic upper bound on the first nonzero eigenvalue of the scalar Laplacian on K3 in the large volume regime, that depends on the K3 moduli data. As two byproducts, we find an exact equivalence between a class of BPS N=2 superconformal blocks and Virasoro conformal blocks in two dimensions, and an upper bound on the four-point functions of operators of sufficiently low scaling dimension in three and four dimensional CFTs.
Kolmogorov complexity, pseudorandom generators and statistical models testing
Czech Academy of Sciences Publication Activity Database
Šindelář, Jan; Boček, Pavel
2002-01-01
Roč. 38, č. 6 (2002), s. 747-759 ISSN 0023-5954 R&D Projects: GA ČR GA102/99/1564 Institutional research plan: CEZ:AV0Z1075907 Keywords : Kolmogorov complexity * pseudorandom generators * statistical models testing Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.341, year: 2002
Brandic, Ivona; Music, Dejan; Dustdar, Schahram
Nowadays, novel computing paradigms as for example Cloud Computing are gaining more and more on importance. In case of Cloud Computing users pay for the usage of the computing power provided as a service. Beforehand they can negotiate specific functional and non-functional requirements relevant for the application execution. However, providing computing power as a service bears different research challenges. On one hand dynamic, versatile, and adaptable services are required, which can cope with system failures and environmental changes. On the other hand, human interaction with the system should be minimized. In this chapter we present the first results in establishing adaptable, versatile, and dynamic services considering negotiation bootstrapping and service mediation achieved in context of the Foundations of Self-Governing ICT Infrastructures (FoSII) project. We discuss novel meta-negotiation and SLA mapping solutions for Cloud services bridging the gap between current QoS models and Cloud middleware and representing important prerequisites for the establishment of autonomic Cloud services.
Visualization of the variability of 3D statistical shape models by animation.
Lamecker, Hans; Seebass, Martin; Lange, Thomas; Hege, Hans-Christian; Deuflhard, Peter
2004-01-01
Models of the 3D shape of anatomical objects and the knowledge about their statistical variability are of great benefit in many computer assisted medical applications like images analysis, therapy or surgery planning. Statistical model of shapes have successfully been applied to automate the task of image segmentation. The generation of 3D statistical shape models requires the identification of corresponding points on two shapes. This remains a difficult problem, especially for shapes of complicated topology. In order to interpret and validate variations encoded in a statistical shape model, visual inspection is of great importance. This work describes the generation and interpretation of statistical shape models of the liver and the pelvic bone.
Applied systems ecology: models, data, and statistical methods
Energy Technology Data Exchange (ETDEWEB)
Eberhardt, L L
1976-01-01
In this report, systems ecology is largely equated to mathematical or computer simulation modelling. The need for models in ecology stems from the necessity to have an integrative device for the diversity of ecological data, much of which is observational, rather than experimental, as well as from the present lack of a theoretical structure for ecology. Different objectives in applied studies require specialized methods. The best predictive devices may be regression equations, often non-linear in form, extracted from much more detailed models. A variety of statistical aspects of modelling, including sampling, are discussed. Several aspects of population dynamics and food-chain kinetics are described, and it is suggested that the two presently separated approaches should be combined into a single theoretical framework. It is concluded that future efforts in systems ecology should emphasize actual data and statistical methods, as well as modelling.
The use of statistical models in heavy-ion reactions studies
International Nuclear Information System (INIS)
Stokstad, R.G.
1984-01-01
This chapter reviews the use of statistical models to describe nuclear level densities and the decay of equilibrated nuclei. The statistical models of nuclear structure and nuclear reactions presented here have wide application in the analysis of heavy-ion reaction data. Applications are illustrated with examples of gamma-ray decay, the emission of light particles and heavier clusters of nucleons, and fission. In addition to the compound nucleus, the treatment of equilibrated fragments formed in binary reactions is discussed. The statistical model is shown to be an important tool for the identification of products from nonequilibrium decay
Multivariate statistical modelling based on generalized linear models
Fahrmeir, Ludwig
1994-01-01
This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2006-01-01
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on bo
Asymptotic distribution of ∆AUC, NRIs, and IDI based on theory of U-statistics.
Demler, Olga V; Pencina, Michael J; Cook, Nancy R; D'Agostino, Ralph B
2017-09-20
The change in area under the curve (∆AUC), the integrated discrimination improvement (IDI), and net reclassification index (NRI) are commonly used measures of risk prediction model performance. Some authors have reported good validity of associated methods of estimating their standard errors (SE) and construction of confidence intervals, whereas others have questioned their performance. To address these issues, we unite the ∆AUC, IDI, and three versions of the NRI under the umbrella of the U-statistics family. We rigorously show that the asymptotic behavior of ∆AUC, NRIs, and IDI fits the asymptotic distribution theory developed for U-statistics. We prove that the ∆AUC, NRIs, and IDI are asymptotically normal, unless they compare nested models under the null hypothesis. In the latter case, asymptotic normality and existing SE estimates cannot be applied to ∆AUC, NRIs, or IDI. In the former case, SE formulas proposed in the literature are equivalent to SE formulas obtained from U-statistics theory if we ignore adjustment for estimated parameters. We use Sukhatme-Randles-deWet condition to determine when adjustment for estimated parameters is necessary. We show that adjustment is not necessary for SEs of the ∆AUC and two versions of the NRI when added predictor variables are significant and normally distributed. The SEs of the IDI and three-category NRI should always be adjusted for estimated parameters. These results allow us to define when existing formulas for SE estimates can be used and when resampling methods such as the bootstrap should be used instead when comparing nested models. We also use the U-statistic theory to develop a new SE estimate of ∆AUC. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Active Learning with Statistical Models.
1995-01-01
Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with
Parametric analysis of the statistical model of the stick-slip process
Lima, Roberta; Sampaio, Rubens
2017-06-01
In this paper it is performed a parametric analysis of the statistical model of the response of a dry-friction oscillator. The oscillator is a spring-mass system which moves over a base with a rough surface. Due to this roughness, the mass is subject to a dry-frictional force modeled as a Coulomb friction. The system is stochastically excited by an imposed bang-bang base motion. The base velocity is modeled by a Poisson process for which a probabilistic model is fully specified. The excitation induces in the system stochastic stick-slip oscillations. The system response is composed by a random sequence alternating stick and slip-modes. With realizations of the system, a statistical model is constructed for this sequence. In this statistical model, the variables of interest of the sequence are modeled as random variables, as for example, the number of time intervals in which stick or slip occur, the instants at which they begin, and their duration. Samples of the system response are computed by integration of the dynamic equation of the system using independent samples of the base motion. Statistics and histograms of the random variables which characterize the stick-slip process are estimated for the generated samples. The objective of the paper is to analyze how these estimated statistics and histograms vary with the system parameters, i.e., to make a parametric analysis of the statistical model of the stick-slip process.
A Range-Based Test for the Parametric Form of the Volatility in Diffusion Models
DEFF Research Database (Denmark)
Podolskij, Mark; Ziggel, Daniel
statistic. Under rather weak assumptions on the drift and volatility we prove weak convergence of the test statistic to a centered mixed Gaussian distribution. As a consequence we obtain a test, which is consistent for any fixed alternative. Moreover, we present a parametric bootstrap procedure which...
Directory of Open Access Journals (Sweden)
Gu Xun
2007-03-01
Full Text Available Abstract Background Phylogenetically related miRNAs (miRNA families convey important information of the function and evolution of miRNAs. Due to the special sequence features of miRNAs, pair-wise sequence identity between miRNA precursors alone is often inadequate for unequivocally judging the phylogenetic relationships between miRNAs. Most of the current methods for miRNA classification rely heavily on manual inspection and lack measurements of the reliability of the results. Results In this study, we designed an analysis pipeline (the Phylogeny-Bootstrap-Cluster (PBC pipeline to identify miRNA families based on branch stability in the bootstrap trees derived from overlapping genome-wide miRNA sequence sets. We tested the PBC analysis pipeline with the miRNAs from six animal species, H. sapiens, M. musculus, G. gallus, D. rerio, D. melanogaster, and C. elegans. The resulting classification was compared with the miRNA families defined in miRBase. The two classifications were largely consistent. Conclusion The PBC analysis pipeline is an efficient method for classifying large numbers of heterogeneous miRNA sequences. It requires minimum human involvement and provides measurements of the reliability of the classification results.
arXiv Bootstrapping the QCD soft anomalous dimension
Almelid, Øyvind; Gardi, Einan; McLeod, Andrew; White, Chris D.
2017-09-18
The soft anomalous dimension governs the infrared singularities of scattering amplitudes to all orders in perturbative quantum field theory, and is a crucial ingredient in both formal and phenomenological applications of non-abelian gauge theories. It has recently been computed at three-loop order for massless partons by explicit evaluation of all relevant Feynman diagrams. In this paper, we show how the same result can be obtained, up to an overall numerical factor, using a bootstrap procedure. We first give a geometrical argument for the fact that the result can be expressed in terms of single-valued harmonic polylogarithms. We then use symmetry considerations as well as known properties of scattering amplitudes in collinear and high-energy (Regge) limits to constrain an ansatz of basis functions. This is a highly non-trivial cross-check of the result, and our methods pave the way for greatly simplified higher-order calculations.
Peraza-Rodriguez, H.; Reynolds-Barredo, J. M.; Sanchez, R.; Tribaldos, V.; Geiger, J.
2018-02-01
The recently developed free-plasma-boundary version of the SIESTA MHD equilibrium code (Hirshman et al 2011 Phys. Plasmas 18 062504; Peraza-Rodriguez et al 2017 Phys. Plasmas 24 082516) is used for the first time to study scenarios with considerable bootstrap currents for the Wendelstein 7-X (W7-X) stellarator. Bootstrap currents in the range of tens of kAs can lead to the formation of unwanted magnetic island chains or stochastic regions within the plasma and alter the boundary rotational transform due to the small shear in W7-X. The latter issue is of relevance since the island divertor operation of W7-X relies on a proper positioning of magnetic island chains at the plasma edge to control the particle and energy exhaust towards the divertor plates. Two scenarios are examined with the new free-plasma-boundary capabilities of SIESTA: a freely evolving bootstrap current one that illustrates the difficulties arising from the dislocation of the boundary islands, and a second one in which off-axis electron cyclotron current drive (ECCD) is applied to compensate the effects of the bootstrap current and keep the island divertor configuration intact. SIESTA finds that off-axis ECCD is indeed able to keep the location and phase of the edge magnetic island chain unchanged, but it may also lead to an undesired stochastization of parts of the confined plasma if the EC deposition radial profile becomes too narrow.
Study on Semi-Parametric Statistical Model of Safety Monitoring of Cracks in Concrete Dams
Directory of Open Access Journals (Sweden)
Chongshi Gu
2013-01-01
Full Text Available Cracks are one of the hidden dangers in concrete dams. The study on safety monitoring models of concrete dam cracks has always been difficult. Using the parametric statistical model of safety monitoring of cracks in concrete dams, with the help of the semi-parametric statistical theory, and considering the abnormal behaviors of these cracks, the semi-parametric statistical model of safety monitoring of concrete dam cracks is established to overcome the limitation of the parametric model in expressing the objective model. Previous projects show that the semi-parametric statistical model has a stronger fitting effect and has a better explanation for cracks in concrete dams than the parametric statistical model. However, when used for forecast, the forecast capability of the semi-parametric statistical model is equivalent to that of the parametric statistical model. The modeling of the semi-parametric statistical model is simple, has a reasonable principle, and has a strong practicality, with a good application prospect in the actual project.
Academic Carelessness, Bootstrapping, and the Cybernetic Investigator
Directory of Open Access Journals (Sweden)
Hannah Drayson
2017-11-01
Full Text Available The following discussion is concerned with certain forms of poor practice in academic publishing that give rise to “academic urban legends.” It suggests that rather than simply consider phenomena such as poor citation practices and circular reporting as mistakes, misunderstandings, and evidence of lack of rigor, we might also read them as evidence of a particular kind of creativity—for which misunderstandings, assump-tions, and failures of diligence are mechanisms by which potentially influential ideas manifest. Reflecting particularly on a critique of the debate surrounding pharmaceutical cognitive enhancement and its use by university staff and students, the following will argue that investigators within the disciplines concerned with the effects or development of these technologies are themselves implicated as potential subjects. Alongside reflections from science fiction studies that offer insights into the experiential dimension of reading and misreading, this paper offers some insights regarding how we might think of mistakes and misunderstandings as a form of bootstrapping and a source of creativity in scientific and technological development.
Statistical models for competing risk analysis
International Nuclear Information System (INIS)
Sather, H.N.
1976-08-01
Research results on three new models for potential applications in competing risks problems. One section covers the basic statistical relationships underlying the subsequent competing risks model development. Another discusses the problem of comparing cause-specific risk structure by competing risks theory in two homogeneous populations, P1 and P2. Weibull models which allow more generality than the Berkson and Elveback models are studied for the effect of time on the hazard function. The use of concomitant information for modeling single-risk survival is extended to the multiple failure mode domain of competing risks. The model used to illustrate the use of this methodology is a life table model which has constant hazards within pre-designated intervals of the time scale. Two parametric models for bivariate dependent competing risks, which provide interesting alternatives, are proposed and examined
SoS contract verification using statistical model checking
Directory of Open Access Journals (Sweden)
Alessandro Mignogna
2013-11-01
Full Text Available Exhaustive formal verification for systems of systems (SoS is impractical and cannot be applied on a large scale. In this paper we propose to use statistical model checking for efficient verification of SoS. We address three relevant aspects for systems of systems: 1 the model of the SoS, which includes stochastic aspects; 2 the formalization of the SoS requirements in the form of contracts; 3 the tool-chain to support statistical model checking for SoS. We adapt the SMC technique for application to heterogeneous SoS. We extend the UPDM/SysML specification language to express the SoS requirements that the implemented strategies over the SoS must satisfy. The requirements are specified with a new contract language specifically designed for SoS, targeting a high-level English- pattern language, but relying on an accurate semantics given by the standard temporal logics. The contracts are verified against the UPDM/SysML specification using the Statistical Model Checker (SMC PLASMA combined with the simulation engine DESYRE, which integrates heterogeneous behavioral models through the functional mock-up interface (FMI standard. The tool-chain allows computing an estimation of the satisfiability of the contracts by the SoS. The results help the system architect to trade-off different solutions to guide the evolution of the SoS.