Statistical Methods in Integrative Genomics
Richardson, Sylvia; Tseng, George C.; Sun, Wei
2016-01-01
Statistical methods in integrative genomics aim to answer important biology questions by jointly analyzing multiple types of genomic data (vertical integration) or aggregating the same type of data across multiple studies (horizontal integration). In this article, we introduce different types of genomic data and data resources, and then review statistical methods of integrative genomics, with emphasis on the motivation and rationale of these methods. We conclude with some summary points and future research directions. PMID:27482531
Permutation statistical methods an integrated approach
Berry, Kenneth J; Johnston, Janis E
2016-01-01
This research monograph provides a synthesis of a number of statistical tests and measures, which, at first consideration, appear disjoint and unrelated. Numerous comparisons of permutation and classical statistical methods are presented, and the two methods are compared via probability values and, where appropriate, measures of effect size. Permutation statistical methods, compared to classical statistical methods, do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This text takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field in statistics. This topic is new in that it took modern computing power to make permutation methods available to people working in the mainstream of research. This research monograph addresses a statistically-informed audience, and can also easily serve as a ...
Zeng, Irene Sui Lan; Lumley, Thomas
2018-01-01
Integrated omics is becoming a new channel for investigating the complex molecular system in modern biological science and sets a foundation for systematic learning for precision medicine. The statistical/machine learning methods that have emerged in the past decade for integrated omics are not only innovative but also multidisciplinary with integrated knowledge in biology, medicine, statistics, machine learning, and artificial intelligence. Here, we review the nontrivial classes of learning methods from the statistical aspects and streamline these learning methods within the statistical learning framework. The intriguing findings from the review are that the methods used are generalizable to other disciplines with complex systematic structure, and the integrated omics is part of an integrated information science which has collated and integrated different types of information for inferences and decision making. We review the statistical learning methods of exploratory and supervised learning from 42 publications. We also discuss the strengths and limitations of the extended principal component analysis, cluster analysis, network analysis, and regression methods. Statistical techniques such as penalization for sparsity induction when there are fewer observations than the number of features and using Bayesian approach when there are prior knowledge to be integrated are also included in the commentary. For the completeness of the review, a table of currently available software and packages from 23 publications for omics are summarized in the appendix.
Szulc, Stefan
1965-01-01
Statistical Methods provides a discussion of the principles of the organization and technique of research, with emphasis on its application to the problems in social statistics. This book discusses branch statistics, which aims to develop practical ways of collecting and processing numerical data and to adapt general statistical methods to the objectives in a given field.Organized into five parts encompassing 22 chapters, this book begins with an overview of how to organize the collection of such information on individual units, primarily as accomplished by government agencies. This text then
Pliske, Rebecca M.; Caldwell, Tracy L.; Calin-Jageman, Robert J.; Taylor-Ritzler, Tina
2015-01-01
We developed a two-semester series of intensive (six-contact hours per week) behavioral research methods courses with an integrated statistics curriculum. Our approach includes the use of team-based learning, authentic projects, and Excel and SPSS. We assessed the effectiveness of our approach by examining our students' content area scores on the…
Ciaccio, Mark F; Finkle, Justin D; Xue, Albert Y; Bagheri, Neda
2014-07-01
An organism's ability to maintain a desired physiological response relies extensively on how cellular and molecular signaling networks interpret and react to environmental cues. The capacity to quantitatively predict how networks respond to a changing environment by modifying signaling regulation and phenotypic responses will help inform and predict the impact of a changing global enivronment on organisms and ecosystems. Many computational strategies have been developed to resolve cue-signal-response networks. However, selecting a strategy that answers a specific biological question requires knowledge both of the type of data being collected, and of the strengths and weaknesses of different computational regimes. We broadly explore several computational approaches, and we evaluate their accuracy in predicting a given response. Specifically, we describe how statistical algorithms can be used in the context of integrative and comparative biology to elucidate the genomic, proteomic, and/or cellular networks responsible for robust physiological response. As a case study, we apply this strategy to a dataset of quantitative levels of protein abundance from the mussel, Mytilus galloprovincialis, to uncover the temperature-dependent signaling network. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.
Energy Technology Data Exchange (ETDEWEB)
Jha, Sumit Kumar [University of Central Florida, Orlando; Pullum, Laura L [ORNL; Ramanathan, Arvind [ORNL
2016-01-01
Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.
Understanding advanced statistical methods
Westfall, Peter
2013-01-01
Introduction: Probability, Statistics, and ScienceReality, Nature, Science, and ModelsStatistical Processes: Nature, Design and Measurement, and DataModelsDeterministic ModelsVariabilityParametersPurely Probabilistic Statistical ModelsStatistical Models with Both Deterministic and Probabilistic ComponentsStatistical InferenceGood and Bad ModelsUses of Probability ModelsRandom Variables and Their Probability DistributionsIntroductionTypes of Random Variables: Nominal, Ordinal, and ContinuousDiscrete Probability Distribution FunctionsContinuous Probability Distribution FunctionsSome Calculus-Derivatives and Least SquaresMore Calculus-Integrals and Cumulative Distribution FunctionsProbability Calculation and SimulationIntroductionAnalytic Calculations, Discrete and Continuous CasesSimulation-Based ApproximationGenerating Random NumbersIdentifying DistributionsIntroductionIdentifying Distributions from Theory AloneUsing Data: Estimating Distributions via the HistogramQuantiles: Theoretical and Data-Based Estimate...
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
Statistical inference an integrated approach
Migon, Helio S; Louzada, Francisco
2014-01-01
Introduction Information The concept of probability Assessing subjective probabilities An example Linear algebra and probability Notation Outline of the bookElements of Inference Common statistical modelsLikelihood-based functions Bayes theorem Exchangeability Sufficiency and exponential family Parameter elimination Prior Distribution Entirely subjective specification Specification through functional forms Conjugacy with the exponential family Non-informative priors Hierarchical priors Estimation Introduction to decision theoryBayesian point estimation Classical point estimation Empirical Bayes estimation Comparison of estimators Interval estimation Estimation in the Normal model Approximating Methods The general problem of inference Optimization techniquesAsymptotic theory Other analytical approximations Numerical integration methods Simulation methods Hypothesis Testing Introduction Classical hypothesis testingBayesian hypothesis testing Hypothesis testing and confidence intervalsAsymptotic tests Prediction...
Functional integral approach to classical statistical dynamics
International Nuclear Information System (INIS)
Jensen, R.V.
1980-04-01
A functional integral method is developed for the statistical solution of nonlinear stochastic differential equations which arise in classical dynamics. The functional integral approach provides a very natural and elegant derivation of the statistical dynamical equations that have been derived using the operator formalism of Martin, Siggia, and Rose
Methods of statistical physics
Akhiezer, Aleksandr I
1981-01-01
Methods of Statistical Physics is an exposition of the tools of statistical mechanics, which evaluates the kinetic equations of classical and quantized systems. The book also analyzes the equations of macroscopic physics, such as the equations of hydrodynamics for normal and superfluid liquids and macroscopic electrodynamics. The text gives particular attention to the study of quantum systems. This study begins with a discussion of problems of quantum statistics with a detailed description of the basics of quantum mechanics along with the theory of measurement. An analysis of the asymptotic be
Multimodal integration in statistical learning
DEFF Research Database (Denmark)
Mitchell, Aaron; Christiansen, Morten Hyllekvist; Weiss, Dan
2014-01-01
, we investigated the ability of adults to integrate audio and visual input during statistical learning. We presented learners with a speech stream synchronized with a video of a speaker’s face. In the critical condition, the visual (e.g., /gi/) and auditory (e.g., /mi/) signals were occasionally...... facilitated participants’ ability to segment the speech stream. Our results therefore demonstrate that participants can integrate audio and visual input to perceive the McGurk illusion during statistical learning. We interpret our findings as support for modality-interactive accounts of statistical learning.......Recent advances in the field of statistical learning have established that learners are able to track regularities of multimodal stimuli, yet it is unknown whether the statistical computations are performed on integrated representations or on separate, unimodal representations. In the present study...
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
Statistical methods for forecasting
Abraham, Bovas
2009-01-01
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists."This book, it must be said, lives up to the words on its advertising cover: ''Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.'' It does just that!"-Journal of the Royal Statistical Society"A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series ...
Probability and statistics with integrated software routines
Deep, Ronald
2005-01-01
Probability & Statistics with Integrated Software Routines is a calculus-based treatment of probability concurrent with and integrated with statistics through interactive, tailored software applications designed to enhance the phenomena of probability and statistics. The software programs make the book unique.The book comes with a CD containing the interactive software leading to the Statistical Genie. The student can issue commands repeatedly while making parameter changes to observe the effects. Computer programming is an excellent skill for problem solvers, involving design, prototyping, data gathering, testing, redesign, validating, etc, all wrapped up in the scientific method.See also: CD to accompany Probability and Stats with Integrated Software Routines (0123694698)* Incorporates more than 1,000 engaging problems with answers* Includes more than 300 solved examples* Uses varied problem solving methods
Nonequilibrium statistical mechanics ensemble method
Eu, Byung Chan
1998-01-01
In this monograph, nonequilibrium statistical mechanics is developed by means of ensemble methods on the basis of the Boltzmann equation, the generic Boltzmann equations for classical and quantum dilute gases, and a generalised Boltzmann equation for dense simple fluids The theories are developed in forms parallel with the equilibrium Gibbs ensemble theory in a way fully consistent with the laws of thermodynamics The generalised hydrodynamics equations are the integral part of the theory and describe the evolution of macroscopic processes in accordance with the laws of thermodynamics of systems far removed from equilibrium Audience This book will be of interest to researchers in the fields of statistical mechanics, condensed matter physics, gas dynamics, fluid dynamics, rheology, irreversible thermodynamics and nonequilibrium phenomena
Statistical inference an integrated Bayesianlikelihood approach
Aitkin, Murray
2010-01-01
Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications. This novel approach provides new solutions to difficult model comparison problems and offers direct Bayesian counterparts of frequentist t-tests and other standard statistical methods for hypothesis testing.After an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood approach used throughout. It pre
Statistical methods and materials characterisation
International Nuclear Information System (INIS)
Wallin, K.R.W.
2010-01-01
Statistics is a wide mathematical area, which covers a myriad of analysis and estimation options, some of which suit special cases better than others. A comprehensive coverage of the whole area of statistics would be an enormous effort and would also be outside the capabilities of this author. Therefore, this does not intend to be a textbook on statistical methods available for general data analysis and decision making. Instead it will highlight a certain special statistical case applicable to mechanical materials characterization. The methods presented here do not in any way rule out other statistical methods by which to analyze mechanical property material data. (orig.)
Statistical methods in quality assurance
International Nuclear Information System (INIS)
Eckhard, W.
1980-01-01
During the different phases of a production process - planning, development and design, manufacturing, assembling, etc. - most of the decision rests on a base of statistics, the collection, analysis and interpretation of data. Statistical methods can be thought of as a kit of tools to help to solve problems in the quality functions of the quality loop with respect to produce quality products and to reduce quality costs. Various statistical methods are represented, typical examples for their practical application are demonstrated. (RW)
Statistical methods for quality improvement
National Research Council Canada - National Science Library
Ryan, Thomas P
2011-01-01
...."-TechnometricsThis new edition continues to provide the most current, proven statistical methods for quality control and quality improvementThe use of quantitative methods offers numerous benefits...
Statistical methods for ranking data
Alvo, Mayer
2014-01-01
This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.
Statistical methods in nonlinear dynamics
Indian Academy of Sciences (India)
Sensitivity to initial conditions in nonlinear dynamical systems leads to exponential divergence of trajectories that are initially arbitrarily close, and hence to unpredictability. Statistical methods have been found to be helpful in extracting useful information about such systems. In this paper, we review briefly some statistical ...
Statistical Methods in Psychology Journals.
Willkinson, Leland
1999-01-01
Proposes guidelines for revising the American Psychological Association (APA) publication manual or other APA materials to clarify the application of statistics in research reports. The guidelines are intended to induce authors and editors to recognize the thoughtless application of statistical methods. Contains 54 references. (SLD)
Diverse methods for integrable models
Fehér, G.
2017-01-01
This thesis is centered around three topics, sharing integrability as a common theme. This thesis explores different methods in the field of integrable models. The first two chapters are about integrable lattice models in statistical physics. The last chapter describes an integrable quantum chain.
Directory of Open Access Journals (Sweden)
Jiabo Chen
2016-10-01
Full Text Available Source apportionment of river water pollution is critical in water resource management and aquatic conservation. Comprehensive application of various GIS-based multivariate statistical methods was performed to analyze datasets (2009–2011 on water quality in the Liao River system (China. Cluster analysis (CA classified the 12 months of the year into three groups (May–October, February–April and November–January and the 66 sampling sites into three groups (groups A, B and C based on similarities in water quality characteristics. Discriminant analysis (DA determined that temperature, dissolved oxygen (DO, pH, chemical oxygen demand (CODMn, 5-day biochemical oxygen demand (BOD5, NH4+–N, total phosphorus (TP and volatile phenols were significant variables affecting temporal variations, with 81.2% correct assignments. Principal component analysis (PCA and positive matrix factorization (PMF identified eight potential pollution factors for each part of the data structure, explaining more than 61% of the total variance. Oxygen-consuming organics from cropland and woodland runoff were the main latent pollution factor for group A. For group B, the main pollutants were oxygen-consuming organics, oil, nutrients and fecal matter. For group C, the evaluated pollutants primarily included oxygen-consuming organics, oil and toxic organics.
Statistical methods for physical science
Stanford, John L
1994-01-01
This volume of Methods of Experimental Physics provides an extensive introduction to probability and statistics in many areas of the physical sciences, with an emphasis on the emerging area of spatial statistics. The scope of topics covered is wide-ranging-the text discusses a variety of the most commonly used classical methods and addresses newer methods that are applicable or potentially important. The chapter authors motivate readers with their insightful discussions, augmenting their material withKey Features* Examines basic probability, including coverage of standard distributions, time s
Statistical methods in nuclear theory
International Nuclear Information System (INIS)
Shubin, Yu.N.
1974-01-01
The paper outlines statistical methods which are widely used for describing properties of excited states of nuclei and nuclear reactions. It discusses physical assumptions lying at the basis of known distributions between levels (Wigner, Poisson distributions) and of widths of highly excited states (Porter-Thomas distribution, as well as assumptions used in the statistical theory of nuclear reactions and in the fluctuation analysis. The author considers the random matrix method, which consists in replacing the matrix elements of a residual interaction by random variables with a simple statistical distribution. Experimental data are compared with results of calculations using the statistical model. The superfluid nucleus model is considered with regard to superconducting-type pair correlations
Robust statistical methods with R
Jureckova, Jana
2005-01-01
Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on practical application.The authors work from underlying mathematical tools to implementation, paying special attention to the computational aspects. They cover the whole range of robust methods, including differentiable statistical functions, distance of measures, influence functions, and asymptotic distributions, in a rigorous yet approachable manner. Highlighting hands-on problem solving, many examples and computational algorithms using the R software supplement the discussion. The book examines the characteristics of robustness, estimators of real parameter, large sample properties, and goodness-of-fit tests. It...
Statistical Methods for Fuzzy Data
Viertl, Reinhard
2011-01-01
Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy m
Statistical methods in spatial genetics
DEFF Research Database (Denmark)
Guillot, Gilles; Leblois, Raphael; Coulon, Aurelie
2009-01-01
The joint analysis of spatial and genetic data is rapidly becoming the norm in population genetics. More and more studies explicitly describe and quantify the spatial organization of genetic variation and try to relate it to underlying ecological processes. As it has become increasingly difficult...... to keep abreast with the latest methodological developments, we review the statistical toolbox available to analyse population genetic data in a spatially explicit framework. We mostly focus on statistical concepts but also discuss practical aspects of the analytical methods, highlighting not only...
Statistical methods for quality assurance
International Nuclear Information System (INIS)
Rinne, H.; Mittag, H.J.
1989-01-01
This is the first German-language textbook on quality assurance and the fundamental statistical methods that is suitable for private study. The material for this book has been developed from a course of Hagen Open University and is characterized by a particularly careful didactical design which is achieved and supported by numerous illustrations and photographs, more than 100 exercises with complete problem solutions, many fully displayed calculation examples, surveys fostering a comprehensive approach, bibliography with comments. The textbook has an eye to practice and applications, and great care has been taken by the authors to avoid abstraction wherever appropriate, to explain the proper conditions of application of the testing methods described, and to give guidance for suitable interpretation of results. The testing methods explained also include latest developments and research results in order to foster their adoption in practice. (orig.) [de
Order statistics & inference estimation methods
Balakrishnan, N
1991-01-01
The literature on order statistics and inferenc eis quite extensive and covers a large number of fields ,but most of it is dispersed throughout numerous publications. This volume is the consolidtion of the most important results and places an emphasis on estimation. Both theoretical and computational procedures are presented to meet the needs of researchers, professionals, and students. The methods of estimation discussed are well-illustrated with numerous practical examples from both the physical and life sciences, including sociology,psychology,a nd electrical and chemical engineering. A co
Vortex methods and vortex statistics
International Nuclear Information System (INIS)
Chorin, A.J.
1993-05-01
Vortex methods originated from the observation that in incompressible, inviscid, isentropic flow vorticity (or, more accurately, circulation) is a conserved quantity, as can be readily deduced from the absence of tangential stresses. Thus if the vorticity is known at time t = 0, one can deduce the flow at a later time by simply following it around. In this narrow context, a vortex method is a numerical method that makes use of this observation. Even more generally, the analysis of vortex methods leads, to problems that are closely related to problems in quantum physics and field theory, as well as in harmonic analysis. A broad enough definition of vortex methods ends up by encompassing much of science. Even the purely computational aspects of vortex methods encompass a range of ideas for which vorticity may not be the best unifying theme. The author restricts himself in these lectures to a special class of numerical vortex methods, those that are based on a Lagrangian transport of vorticity in hydrodynamics by smoothed particles (''blobs'') and those whose understanding contributes to the understanding of blob methods. Vortex methods for inviscid flow lead to systems of ordinary differential equations that can be readily clothed in Hamiltonian form, both in three and two space dimensions, and they can preserve exactly a number of invariants of the Euler equations, including topological invariants. Their viscous versions resemble Langevin equations. As a result, they provide a very useful cartoon of statistical hydrodynamics, i.e., of turbulence, one that can to some extent be analyzed analytically and more importantly, explored numerically, with important implications also for superfluids, superconductors, and even polymers. In the authors view, vortex ''blob'' methods provide the most promising path to the understanding of these phenomena
Statistics of spatially integrated speckle intensity difference
DEFF Research Database (Denmark)
Hanson, Steen Grüner; Yura, Harold
2009-01-01
We consider the statistics of the spatially integrated speckle intensity difference obtained from two separated finite collecting apertures. For fully developed speckle, closed-form analytic solutions for both the probability density function and the cumulative distribution function are derived...... here for both arbitrary values of the mean number of speckles contained within an aperture and the degree of coherence of the optical field. Additionally, closed-form expressions are obtained for the corresponding nth statistical moments....
Bayes linear statistics, theory & methods
Goldstein, Michael
2007-01-01
Bayesian methods combine information available from data with any prior information available from expert knowledge. The Bayes linear approach follows this path, offering a quantitative structure for expressing beliefs, and systematic methods for adjusting these beliefs, given observational data. The methodology differs from the full Bayesian methodology in that it establishes simpler approaches to belief specification and analysis based around expectation judgements. Bayes Linear Statistics presents an authoritative account of this approach, explaining the foundations, theory, methodology, and practicalities of this important field. The text provides a thorough coverage of Bayes linear analysis, from the development of the basic language to the collection of algebraic results needed for efficient implementation, with detailed practical examples. The book covers:The importance of partial prior specifications for complex problems where it is difficult to supply a meaningful full prior probability specification...
THE GROWTH POINTS OF STATISTICAL METHODS
Orlov A. I.
2014-01-01
On the basis of a new paradigm of applied mathematical statistics, data analysis and economic-mathematical methods are identified; we have also discussed five topical areas in which modern applied statistics is developing as well as the other statistical methods, i.e. five "growth points" – nonparametric statistics, robustness, computer-statistical methods, statistics of interval data, statistics of non-numeric data
Mathematical methods in quantum and statistical mechanics
International Nuclear Information System (INIS)
Fishman, L.
1977-01-01
The mathematical structure and closed-form solutions pertaining to several physical problems in quantum and statistical mechanics are examined in some detail. The J-matrix method, introduced previously for s-wave scattering and based upon well-established Hilbert Space theory and related generalized integral transformation techniques, is extended to treat the lth partial wave kinetic energy and Coulomb Hamiltonians within the context of square integrable (L 2 ), Laguerre (Slater), and oscillator (Gaussian) basis sets. The theory of relaxation in statistical mechanics within the context of the theory of linear integro-differential equations of the Master Equation type and their corresponding Markov processes is examined. Several topics of a mathematical nature concerning various computational aspects of the L 2 approach to quantum scattering theory are discussed
Statistical Methodologies to Integrate Experimental and Computational Research
Parker, P. A.; Johnson, R. T.; Montgomery, D. C.
2008-01-01
Development of advanced algorithms for simulating engine flow paths requires the integration of fundamental experiments with the validation of enhanced mathematical models. In this paper, we provide an overview of statistical methods to strategically and efficiently conduct experiments and computational model refinement. Moreover, the integration of experimental and computational research efforts is emphasized. With a statistical engineering perspective, scientific and engineering expertise is combined with statistical sciences to gain deeper insights into experimental phenomenon and code development performance; supporting the overall research objectives. The particular statistical methods discussed are design of experiments, response surface methodology, and uncertainty analysis and planning. Their application is illustrated with a coaxial free jet experiment and a turbulence model refinement investigation. Our goal is to provide an overview, focusing on concepts rather than practice, to demonstrate the benefits of using statistical methods in research and development, thereby encouraging their broader and more systematic application.
Statistical methods in radiation physics
Turner, James E; Bogard, James S
2012-01-01
This statistics textbook, with particular emphasis on radiation protection and dosimetry, deals with statistical solutions to problems inherent in health physics measurements and decision making. The authors begin with a description of our current understanding of the statistical nature of physical processes at the atomic level, including radioactive decay and interactions of radiation with matter. Examples are taken from problems encountered in health physics, and the material is presented such that health physicists and most other nuclear professionals will more readily understand the application of statistical principles in the familiar context of the examples. Problems are presented at the end of each chapter, with solutions to selected problems provided online. In addition, numerous worked examples are included throughout the text.
Statistical inference via fiducial methods
Salomé, Diemer
1998-01-01
In this thesis the attention is restricted to inductive reasoning using a mathematical probability model. A statistical procedure prescribes, for every theoretically possible set of data, the inference about the unknown of interest. ... Zie: Summary
The Monte Carlo method the method of statistical trials
Shreider, YuA
1966-01-01
The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensio
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...
Register-based statistics statistical methods for administrative data
Wallgren, Anders
2014-01-01
This book provides a comprehensive and up to date treatment of theory and practical implementation in Register-based statistics. It begins by defining the area, before explaining how to structure such systems, as well as detailing alternative approaches. It explains how to create statistical registers, how to implement quality assurance, and the use of IT systems for register-based statistics. Further to this, clear details are given about the practicalities of implementing such statistical methods, such as protection of privacy and the coordination and coherence of such an undertaking. Thi
Statistical methods in physical mapping
International Nuclear Information System (INIS)
Nelson, D.O.
1995-05-01
One of the great success stories of modern molecular genetics has been the ability of biologists to isolate and characterize the genes responsible for serious inherited diseases like fragile X syndrome, cystic fibrosis and myotonic muscular dystrophy. This dissertation concentrates on constructing high-resolution physical maps. It demonstrates how probabilistic modeling and statistical analysis can aid molecular geneticists in the tasks of planning, execution, and evaluation of physical maps of chromosomes and large chromosomal regions. The dissertation is divided into six chapters. Chapter 1 provides an introduction to the field of physical mapping, describing the role of physical mapping in gene isolation and ill past efforts at mapping chromosomal regions. The next two chapters review and extend known results on predicting progress in large mapping projects. Such predictions help project planners decide between various approaches and tactics for mapping large regions of the human genome. Chapter 2 shows how probability models have been used in the past to predict progress in mapping projects. Chapter 3 presents new results, based on stationary point process theory, for progress measures for mapping projects based on directed mapping strategies. Chapter 4 describes in detail the construction of all initial high-resolution physical map for human chromosome 19. This chapter introduces the probability and statistical models involved in map construction in the context of a large, ongoing physical mapping project. Chapter 5 concentrates on one such model, the trinomial model. This chapter contains new results on the large-sample behavior of this model, including distributional results, asymptotic moments, and detection error rates. In addition, it contains an optimality result concerning experimental procedures based on the trinomial model. The last chapter explores unsolved problems and describes future work
Statistical methods in physical mapping
Energy Technology Data Exchange (ETDEWEB)
Nelson, David O. [Univ. of California, Berkeley, CA (United States)
1995-05-01
One of the great success stories of modern molecular genetics has been the ability of biologists to isolate and characterize the genes responsible for serious inherited diseases like fragile X syndrome, cystic fibrosis and myotonic muscular dystrophy. This dissertation concentrates on constructing high-resolution physical maps. It demonstrates how probabilistic modeling and statistical analysis can aid molecular geneticists in the tasks of planning, execution, and evaluation of physical maps of chromosomes and large chromosomal regions. The dissertation is divided into six chapters. Chapter 1 provides an introduction to the field of physical mapping, describing the role of physical mapping in gene isolation and ill past efforts at mapping chromosomal regions. The next two chapters review and extend known results on predicting progress in large mapping projects. Such predictions help project planners decide between various approaches and tactics for mapping large regions of the human genome. Chapter 2 shows how probability models have been used in the past to predict progress in mapping projects. Chapter 3 presents new results, based on stationary point process theory, for progress measures for mapping projects based on directed mapping strategies. Chapter 4 describes in detail the construction of all initial high-resolution physical map for human chromosome 19. This chapter introduces the probability and statistical models involved in map construction in the context of a large, ongoing physical mapping project. Chapter 5 concentrates on one such model, the trinomial model. This chapter contains new results on the large-sample behavior of this model, including distributional results, asymptotic moments, and detection error rates. In addition, it contains an optimality result concerning experimental procedures based on the trinomial model. The last chapter explores unsolved problems and describes future work.
Statistical learning methods: Basics, control and performance
Energy Technology Data Exchange (ETDEWEB)
Zimmermann, J. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de
2006-04-01
The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms.
Statistical learning methods: Basics, control and performance
International Nuclear Information System (INIS)
Zimmermann, J.
2006-01-01
The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms
Multivariate statistical methods a primer
Manly, Bryan FJ
2004-01-01
THE MATERIAL OF MULTIVARIATE ANALYSISExamples of Multivariate DataPreview of Multivariate MethodsThe Multivariate Normal DistributionComputer ProgramsGraphical MethodsChapter SummaryReferencesMATRIX ALGEBRAThe Need for Matrix AlgebraMatrices and VectorsOperations on MatricesMatrix InversionQuadratic FormsEigenvalues and EigenvectorsVectors of Means and Covariance MatricesFurther Reading Chapter SummaryReferencesDISPLAYING MULTIVARIATE DATAThe Problem of Displaying Many Variables in Two DimensionsPlotting index VariablesThe Draftsman's PlotThe Representation of Individual Data P:ointsProfiles o
Statistical data analysis using SAS intermediate statistical methods
Marasinghe, Mervyn G
2018-01-01
The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitab...
Thermodynamics and statistical mechanics an integrated approach
Shell, M Scott
2015-01-01
Learn classical thermodynamics alongside statistical mechanics with this fresh approach to the subjects. Molecular and macroscopic principles are explained in an integrated, side-by-side manner to give students a deep, intuitive understanding of thermodynamics and equip them to tackle future research topics that focus on the nanoscale. Entropy is introduced from the get-go, providing a clear explanation of how the classical laws connect to the molecular principles, and closing the gap between the atomic world and thermodynamics. Notation is streamlined throughout, with a focus on general concepts and simple models, for building basic physical intuition and gaining confidence in problem analysis and model development. Well over 400 guided end-of-chapter problems are included, addressing conceptual, fundamental, and applied skill sets. Numerous worked examples are also provided together with handy shaded boxes to emphasize key concepts, making this the complete teaching package for students in chemical engineer...
Directory of Open Access Journals (Sweden)
Jay Krishna Thakur
2015-08-01
Full Text Available The aim of this work is to investigate new approaches using methods based on statistics and geo-statistics for spatio-temporal optimization of groundwater monitoring networks. The formulated and integrated methods were tested with the groundwater quality data set of Bitterfeld/Wolfen, Germany. Spatially, the monitoring network was optimized using geo-statistical methods. Temporal optimization of the monitoring network was carried out using Sen’s method (1968. For geostatistical network optimization, a geostatistical spatio-temporal algorithm was used to identify redundant wells in 2- and 2.5-D Quaternary and Tertiary aquifers. Influences of interpolation block width, dimension, contaminant association, groundwater flow direction and aquifer homogeneity on statistical and geostatistical methods for monitoring network optimization were analysed. The integrated approach shows 37% and 28% redundancies in the monitoring network in Quaternary aquifer and Tertiary aquifer respectively. The geostatistical method also recommends 41 and 22 new monitoring wells in the Quaternary and Tertiary aquifers respectively. In temporal optimization, an overall optimized sampling interval was recommended in terms of lower quartile (238 days, median quartile (317 days and upper quartile (401 days in the research area of Bitterfeld/Wolfen. Demonstrated methods for improving groundwater monitoring network can be used in real monitoring network optimization with due consideration given to influencing factors.
Statistical methods for nuclear material management
Energy Technology Data Exchange (ETDEWEB)
Bowen W.M.; Bennett, C.A. (eds.)
1988-12-01
This book is intended as a reference manual of statistical methodology for nuclear material management practitioners. It describes statistical methods currently or potentially important in nuclear material management, explains the choice of methods for specific applications, and provides examples of practical applications to nuclear material management problems. Together with the accompanying training manual, which contains fully worked out problems keyed to each chapter, this book can also be used as a textbook for courses in statistical methods for nuclear material management. It should provide increased understanding and guidance to help improve the application of statistical methods to nuclear material management problems.
Statistical methods for nuclear material management
International Nuclear Information System (INIS)
Bowen, W.M.; Bennett, C.A.
1988-12-01
This book is intended as a reference manual of statistical methodology for nuclear material management practitioners. It describes statistical methods currently or potentially important in nuclear material management, explains the choice of methods for specific applications, and provides examples of practical applications to nuclear material management problems. Together with the accompanying training manual, which contains fully worked out problems keyed to each chapter, this book can also be used as a textbook for courses in statistical methods for nuclear material management. It should provide increased understanding and guidance to help improve the application of statistical methods to nuclear material management problems
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,
Multivariate statistical methods a first course
Marcoulides, George A
2014-01-01
Multivariate statistics refer to an assortment of statistical methods that have been developed to handle situations in which multiple variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical analysis. An introductory text for students learning multivariate statistical methods for the first time, this book keeps mathematical details to a minimum while conveying the basic principles. One of the principal strategies used throughout the book--in addition to the presentation of actual data analyses--is poin
Advanced statistical methods in data science
Chen, Jiahua; Lu, Xuewen; Yi, Grace; Yu, Hao
2016-01-01
This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a fu...
Statistical Methods for Environmental Pollution Monitoring
Energy Technology Data Exchange (ETDEWEB)
Gilbert, Richard O. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
1987-01-01
The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. The book is logically divided into three parts. Chapters 1, 2, and 3 are introductory chapters. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Some statistical techniques given here are not commonly seen in statistics book. For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17). Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. For example, only brief mention could be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Also, no discussion of methods for assessing risks from environmental pollution could be included.
Statistical methods and challenges in connectome genetics
Pluta, Dustin; Yu, Zhaoxia; Shen, Tong; Chen, Chuansheng; Xue, Gui; Ombao, Hernando
2018-01-01
The study of genetic influences on brain connectivity, known as connectome genetics, is an exciting new direction of research in imaging genetics. We here review recent results and current statistical methods in this area, and discuss some
Statistical methods in personality assessment research.
Schinka, J A; LaLone, L; Broeckel, J A
1997-06-01
Emerging models of personality structure and advances in the measurement of personality and psychopathology suggest that research in personality and personality assessment has entered a stage of advanced development, in this article we examine whether researchers in these areas have taken advantage of new and evolving statistical procedures. We conducted a review of articles published in the Journal of Personality, Assessment during the past 5 years. Of the 449 articles that included some form of data analysis, 12.7% used only descriptive statistics, most employed only univariate statistics, and fewer than 10% used multivariate methods of data analysis. We discuss the cost of using limited statistical methods, the possible reasons for the apparent reluctance to employ advanced statistical procedures, and potential solutions to this technical shortcoming.
Kissick, David J.; Muir, Ryan D.; Sullivan, Shane Z.; Oglesbee, Robert A.; Simpson, Garth J.
2013-02-01
Despite the ubiquitous use of multi-photon and confocal microscopy measurements in biology, the core techniques typically suffer from fundamental compromises between signal to noise (S/N) and linear dynamic range (LDR). In this study, direct synchronous digitization of voltage transients coupled with statistical analysis is shown to allow S/N approaching the theoretical maximum throughout an LDR spanning more than 8 decades, limited only by the dark counts of the detector on the low end and by the intrinsic nonlinearities of the photomultiplier tube (PMT) detector on the high end. Synchronous digitization of each voltage transient represents a fundamental departure from established methods in confocal/multi-photon imaging, which are currently based on either photon counting or signal averaging. High information-density data acquisition (up to 3.2 GB/s of raw data) enables the smooth transition between the two modalities on a pixel-by-pixel basis and the ultimate writing of much smaller files (few kB/s). Modeling of the PMT response allows extraction of key sensor parameters from the histogram of voltage peak-heights. Applications in second harmonic generation (SHG) microscopy are described demonstrating S/N approaching the shot-noise limit of the detector over large dynamic ranges.
Method for statistical data analysis of multivariate observations
Gnanadesikan, R
1997-01-01
A practical guide for multivariate statistical techniques-- now updated and revised In recent years, innovations in computer technology and statistical methodologies have dramatically altered the landscape of multivariate data analysis. This new edition of Methods for Statistical Data Analysis of Multivariate Observations explores current multivariate concepts and techniques while retaining the same practical focus of its predecessor. It integrates methods and data-based interpretations relevant to multivariate analysis in a way that addresses real-world problems arising in many areas of inte
Spatial analysis statistics, visualization, and computational methods
Oyana, Tonny J
2015-01-01
An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis-containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS-as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statisti...
Workshop on Analytical Methods in Statistics
Jurečková, Jana; Maciak, Matúš; Pešta, Michal
2017-01-01
This volume collects authoritative contributions on analytical methods and mathematical statistics. The methods presented include resampling techniques; the minimization of divergence; estimation theory and regression, eventually under shape or other constraints or long memory; and iterative approximations when the optimal solution is difficult to achieve. It also investigates probability distributions with respect to their stability, heavy-tailness, Fisher information and other aspects, both asymptotically and non-asymptotically. The book not only presents the latest mathematical and statistical methods and their extensions, but also offers solutions to real-world problems including option pricing. The selected, peer-reviewed contributions were originally presented at the workshop on Analytical Methods in Statistics, AMISTAT 2015, held in Prague, Czech Republic, November 10-13, 2015.
Statistical Methods for Stochastic Differential Equations
Kessler, Mathieu; Sorensen, Michael
2012-01-01
The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research. The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a sp
Statistical methods for spatio-temporal systems
Finkenstadt, Barbel
2006-01-01
Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities.Contributed by leading researchers in the field, each self-contained chapter starts with an introduction of the topic and progresses to recent research results. Presenting specific examples of epidemic data of bovine tuberculosis, gastroenteric disease, and the U.K. foot-and-mouth outbreak, the first chapter uses stochastic models, such as point process models, to provide the probabilistic backbone that facilitates statistical inference from data. The next chapter discusses the critical issue of modeling random growth objects in diverse biological systems, such as bacteria colonies, tumors, and plant populations. The subsequent chapter examines data transformation tools using examples from ecology and air quality data, followed by a chapter on space-time co...
Statistical methods and challenges in connectome genetics
Pluta, Dustin
2018-03-12
The study of genetic influences on brain connectivity, known as connectome genetics, is an exciting new direction of research in imaging genetics. We here review recent results and current statistical methods in this area, and discuss some of the persistent challenges and possible directions for future work.
Statistic methods for searching inundated radioactive entities
International Nuclear Information System (INIS)
Dubasov, Yu.V.; Krivokhatskij, A.S.; Khramov, N.N.
1993-01-01
The problem of searching flooded radioactive object in a present area was considered. Various models of the searching route plotting are discussed. It is shown that spiral route by random points from the centre of the area examined is the most efficient one. The conclusion is made that, when searching flooded radioactive objects, it is advisable to use multidimensional statistical methods of classification
Application of Turchin's method of statistical regularization
Zelenyi, Mikhail; Poliakova, Mariia; Nozik, Alexander; Khudyakov, Alexey
2018-04-01
During analysis of experimental data, one usually needs to restore a signal after it has been convoluted with some kind of apparatus function. According to Hadamard's definition this problem is ill-posed and requires regularization to provide sensible results. In this article we describe an implementation of the Turchin's method of statistical regularization based on the Bayesian approach to the regularization strategy.
Thermodynamics and statistical mechanics an integrated approach
Hardy, Robert J
2014-01-01
This textbook brings together the fundamentals of the macroscopic and microscopic aspects of thermal physics by presenting thermodynamics and statistical mechanics as complementary theories based on small numbers of postulates. The book is designed to give the instructor flexibility in structuring courses for advanced undergraduates and/or beginning graduate students and is written on the principle that a good text should also be a good reference. The presentation of thermodynamics follows the logic of Clausius and Kelvin while relating the concepts involved to familiar phenomena and the mod
Statistical Methods for Unusual Count Data
DEFF Research Database (Denmark)
Guthrie, Katherine A.; Gammill, Hilary S.; Kamper-Jørgensen, Mads
2016-01-01
microchimerism data present challenges for statistical analysis, including a skewed distribution, excess zero values, and occasional large values. Methods for comparing microchimerism levels across groups while controlling for covariates are not well established. We compared statistical models for quantitative...... microchimerism values, applied to simulated data sets and 2 observed data sets, to make recommendations for analytic practice. Modeling the level of quantitative microchimerism as a rate via Poisson or negative binomial model with the rate of detection defined as a count of microchimerism genome equivalents per...
The statistical process control methods - SPC
Directory of Open Access Journals (Sweden)
Floreková Ľubica
1998-03-01
Full Text Available Methods of statistical evaluation of quality SPC (item 20 of the documentation system of quality control of ISO norm, series 900 of various processes, products and services belong amongst basic qualitative methods that enable us to analyse and compare data pertaining to various quantitative parameters. Also they enable, based on the latter, to propose suitable interventions with the aim of improving these processes, products and services. Theoretical basis and applicatibily of the principles of the: - diagnostics of a cause and effects, - Paret analysis and Lorentz curve, - number distribution and frequency curves of random variable distribution, - Shewhart regulation charts, are presented in the contribution.
Statistical methods towards more efficient infiltration measurements.
Franz, T; Krebs, P
2006-01-01
A comprehensive knowledge about the infiltration situation in a catchment is required for operation and maintenance. Due to the high expenditures, an optimisation of necessary measurement campaigns is essential. Methods based on multivariate statistics were developed to improve the information yield of measurements by identifying appropriate gauge locations. The methods have a high degree of freedom against data needs. They were successfully tested on real and artificial data. For suitable catchments, it is estimated that the optimisation potential amounts up to 30% accuracy improvement compared to nonoptimised gauge distributions. Beside this, a correlation between independent reach parameters and dependent infiltration rates could be identified, which is not dominated by the groundwater head.
Statistical trend analysis methods for temporal phenomena
International Nuclear Information System (INIS)
Lehtinen, E.; Pulkkinen, U.; Poern, K.
1997-04-01
We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods
Statistical trend analysis methods for temporal phenomena
Energy Technology Data Exchange (ETDEWEB)
Lehtinen, E.; Pulkkinen, U. [VTT Automation, (Finland); Poern, K. [Poern Consulting, Nykoeping (Sweden)
1997-04-01
We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods. 14 refs, 10 figs.
Statistical methods for assessment of blend homogeneity
DEFF Research Database (Denmark)
Madsen, Camilla
2002-01-01
In this thesis the use of various statistical methods to address some of the problems related to assessment of the homogeneity of powder blends in tablet production is discussed. It is not straight forward to assess the homogeneity of a powder blend. The reason is partly that in bulk materials......, it is shown how to set up parametric acceptance criteria for the batch that gives a high confidence that future samples with a probability larger than a specified value will pass the USP threeclass criteria. Properties and robustness of proposed changes to the USP test for content uniformity are investigated...
Statistical methods with applications to demography and life insurance
Khmaladze, Estáte V
2013-01-01
Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes, Statistical Methods with Applications to Demography and Life Insurance presents contemporary statistical techniques for analyzing life distributions and life insurance problems. It not only contains traditional material but also incorporates new problems and techniques not discussed in existing actuarial literature. The book mainly focuses on the analysis of an individual life and describes statistical methods based on empirical and related processes. Coverage ranges from analyzing the tails of distributions of lifetimes to modeling population dynamics with migrations. To help readers understand the technical points, the text covers topics such as the Stieltjes, Wiener, and Itô integrals. It also introduces other themes of interest in demography, including mixtures of distributions, analysis of longevity and extreme value theory, and the age structure of a population. In addi...
Identifying User Profiles from Statistical Grouping Methods
Directory of Open Access Journals (Sweden)
Francisco Kelsen de Oliveira
2018-02-01
Full Text Available This research aimed to group users into subgroups according to their levels of knowledge about technology. Statistical hierarchical and non-hierarchical clustering methods were studied, compared and used in the creations of the subgroups from the similarities of the skill levels with these users’ technology. The research sample consisted of teachers who answered online questionnaires about their skills with the use of software and hardware with educational bias. The statistical methods of grouping were performed and showed the possibilities of groupings of the users. The analyses of these groups allowed to identify the common characteristics among the individuals of each subgroup. Therefore, it was possible to define two subgroups of users, one with skill in technology and another with skill with technology, so that the partial results of the research showed two main algorithms for grouping with 92% similarity in the formation of groups of users with skill with technology and the other with little skill, confirming the accuracy of the techniques of discrimination against individuals.
Statistical sampling method for releasing decontaminated vehicles
International Nuclear Information System (INIS)
Lively, J.W.; Ware, J.A.
1996-01-01
Earth moving vehicles (e.g., dump trucks, belly dumps) commonly haul radiologically contaminated materials from a site being remediated to a disposal site. Traditionally, each vehicle must be surveyed before being released. The logistical difficulties of implementing the traditional approach on a large scale demand that an alternative be devised. A statistical method (MIL-STD-105E, open-quotes Sampling Procedures and Tables for Inspection by Attributesclose quotes) for assessing product quality from a continuous process was adapted to the vehicle decontamination process. This method produced a sampling scheme that automatically compensates and accommodates fluctuating batch sizes and changing conditions without the need to modify or rectify the sampling scheme in the field. Vehicles are randomly selected (sampled) upon completion of the decontamination process to be surveyed for residual radioactive surface contamination. The frequency of sampling is based on the expected number of vehicles passing through the decontamination process in a given period and the confidence level desired. This process has been successfully used for 1 year at the former uranium mill site in Monticello, Utah (a CERCLA regulated clean-up site). The method forces improvement in the quality of the decontamination process and results in a lower likelihood that vehicles exceeding the surface contamination standards are offered for survey. Implementation of this statistical sampling method on Monticello Projects has resulted in more efficient processing of vehicles through decontamination and radiological release, saved hundreds of hours of processing time, provided a high level of confidence that release limits are met, and improved the radiological cleanliness of vehicles leaving the controlled site
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.
Application of blended learning in teaching statistical methods
Directory of Open Access Journals (Sweden)
Barbara Dębska
2012-12-01
Full Text Available The paper presents the application of a hybrid method (blended learning - linking traditional education with on-line education to teach selected problems of mathematical statistics. This includes the teaching of the application of mathematical statistics to evaluate laboratory experimental results. An on-line statistics course was developed to form an integral part of the module ‘methods of statistical evaluation of experimental results’. The course complies with the principles outlined in the Polish National Framework of Qualifications with respect to the scope of knowledge, skills and competencies that students should have acquired at course completion. The paper presents the structure of the course and the educational content provided through multimedia lessons made accessible on the Moodle platform. Following courses which used the traditional method of teaching and courses which used the hybrid method of teaching, students test results were compared and discussed to evaluate the effectiveness of the hybrid method of teaching when compared to the effectiveness of the traditional method of teaching.
Statistical Software for State Space Methods
Directory of Open Access Journals (Sweden)
Jacques J. F. Commandeur
2011-05-01
Full Text Available In this paper we review the state space approach to time series analysis and establish the notation that is adopted in this special volume of the Journal of Statistical Software. We first provide some background on the history of state space methods for the analysis of time series. This is followed by a concise overview of linear Gaussian state space analysis including the modelling framework and appropriate estimation methods. We discuss the important class of unobserved component models which incorporate a trend, a seasonal, a cycle, and fixed explanatory and intervention variables for the univariate and multivariate analysis of time series. We continue the discussion by presenting methods for the computation of different estimates for the unobserved state vector: filtering, prediction, and smoothing. Estimation approaches for the other parameters in the model are also considered. Next, we discuss how the estimation procedures can be used for constructing confidence intervals, detecting outlier observations and structural breaks, and testing model assumptions of residual independence, homoscedasticity, and normality. We then show how ARIMA and ARIMA components models fit in the state space framework to time series analysis. We also provide a basic introduction for non-Gaussian state space models. Finally, we present an overview of the software tools currently available for the analysis of time series with state space methods as they are discussed in the other contributions to this special volume.
Application of pedagogy reflective in statistical methods course and practicum statistical methods
Julie, Hongki
2017-08-01
Subject Elementary Statistics, Statistical Methods and Statistical Methods Practicum aimed to equip students of Mathematics Education about descriptive statistics and inferential statistics. The students' understanding about descriptive and inferential statistics were important for students on Mathematics Education Department, especially for those who took the final task associated with quantitative research. In quantitative research, students were required to be able to present and describe the quantitative data in an appropriate manner, to make conclusions from their quantitative data, and to create relationships between independent and dependent variables were defined in their research. In fact, when students made their final project associated with quantitative research, it was not been rare still met the students making mistakes in the steps of making conclusions and error in choosing the hypothetical testing process. As a result, they got incorrect conclusions. This is a very fatal mistake for those who did the quantitative research. There were some things gained from the implementation of reflective pedagogy on teaching learning process in Statistical Methods and Statistical Methods Practicum courses, namely: 1. Twenty two students passed in this course and and one student did not pass in this course. 2. The value of the most accomplished student was A that was achieved by 18 students. 3. According all students, their critical stance could be developed by them, and they could build a caring for each other through a learning process in this course. 4. All students agreed that through a learning process that they undergo in the course, they can build a caring for each other.
On two methods of statistical image analysis
Missimer, J; Knorr, U; Maguire, RP; Herzog, H; Seitz, RJ; Tellman, L; Leenders, K.L.
1999-01-01
The computerized brain atlas (CBA) and statistical parametric mapping (SPM) are two procedures for voxel-based statistical evaluation of PET activation studies. Each includes spatial standardization of image volumes, computation of a statistic, and evaluation of its significance. In addition,
Statistical methods for astronomical data analysis
Chattopadhyay, Asis Kumar
2014-01-01
This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for ...
Seasonal UK Drought Forecasting using Statistical Methods
Richardson, Doug; Fowler, Hayley; Kilsby, Chris; Serinaldi, Francesco
2016-04-01
In the UK drought is a recurrent feature of climate with potentially large impacts on public water supply. Water companies' ability to mitigate the impacts of drought by managing diminishing availability depends on forward planning and it would be extremely valuable to improve forecasts of drought on monthly to seasonal time scales. By focusing on statistical forecasting methods, this research aims to provide techniques that are simpler, faster and computationally cheaper than physically based models. In general, statistical forecasting is done by relating the variable of interest (some hydro-meteorological variable such as rainfall or streamflow, or a drought index) to one or more predictors via some formal dependence. These predictors are generally antecedent values of the response variable or external factors such as teleconnections. A candidate model is Generalised Additive Models for Location, Scale and Shape parameters (GAMLSS). GAMLSS is a very flexible class allowing for more general distribution functions (e.g. highly skewed and/or kurtotic distributions) and the modelling of not just the location parameter but also the scale and shape parameters. Additionally GAMLSS permits the forecasting of an entire distribution, allowing the output to be assessed in probabilistic terms rather than simply the mean and confidence intervals. Exploratory analysis of the relationship between long-memory processes (e.g. large-scale atmospheric circulation patterns, sea surface temperatures and soil moisture content) and drought should result in the identification of suitable predictors to be included in the forecasting model, and further our understanding of the drivers of UK drought.
Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.
Wang, James Z.; Du, Yanping
Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…
Hybrid perturbation methods based on statistical time series models
San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario
2016-04-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.
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.
Integral equation methods for electromagnetics
Volakis, John
2012-01-01
This text/reference is a detailed look at the development and use of integral equation methods for electromagnetic analysis, specifically for antennas and radar scattering. Developers and practitioners will appreciate the broad-based approach to understanding and utilizing integral equation methods and the unique coverage of historical developments that led to the current state-of-the-art. In contrast to existing books, Integral Equation Methods for Electromagnetics lays the groundwork in the initial chapters so students and basic users can solve simple problems and work their way up to the mo
Costache, Romulus; Zaharia, Liliana
2017-06-01
Given the significant worldwide human and economic losses caused due to floods annually, reducing the negative consequences of these hazards is a major concern in development strategies at different spatial scales. A basic step in flood risk management is identifying areas susceptible to flood occurrences. This paper proposes a methodology allowing the identification of areas with high potential of accelerated surface run-off and consequently, of flash-flood occurrences. The methodology involves assessment and mapping in GIS environment of flash flood potential index (FFPI), by integrating two statistical methods: frequency ratio and weights-of-evidence. The methodology was applied for Bâsca Chiojdului River catchment (340 km2), located in the Carpathians Curvature region (Romania). Firstly, the areas with torrential phenomena were identified and the main factors controlling the surface run-off were selected (in this study nine geographical factors were considered). Based on the features of the considered factors, many classes were set for each of them. In the next step, the weights of each class/category of the considered factors were determined, by identifying their spatial relationships with the presence or absence of torrential phenomena. Finally, the weights for each class/category of geographical factors were summarized in GIS, resulting the FFPI values for each of the two statistical methods. These values were divided into five classes of intensity and were mapped. The final results were used to estimate the flash-flood potential and also to identify the most susceptible areas to this phenomenon. Thus, the high and very high values of FFPI characterize more than one-third of the study catchment. The result validation was performed by (i) quantifying the rate of the number of pixels corresponding to the torrential phenomena considered for the study (training area) and for the results' testing (validating area) and (ii) plotting the ROC (receiver operating
Statistical learning methods in high-energy and astrophysics analysis
Energy Technology Data Exchange (ETDEWEB)
Zimmermann, J. [Forschungszentrum Juelich GmbH, Zentrallabor fuer Elektronik, 52425 Juelich (Germany) and Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de; Kiesling, C. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)
2004-11-21
We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application.
Development of a Research Methods and Statistics Concept Inventory
Veilleux, Jennifer C.; Chapman, Kate M.
2017-01-01
Research methods and statistics are core courses in the undergraduate psychology major. To assess learning outcomes, it would be useful to have a measure that assesses research methods and statistical literacy beyond course grades. In two studies, we developed and provided initial validation results for a research methods and statistical knowledge…
Statistical learning methods in high-energy and astrophysics analysis
International Nuclear Information System (INIS)
Zimmermann, J.; Kiesling, C.
2004-01-01
We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application
van den Broek, PLC; van Egmond, J; van Rijn, CM; Takens, F; Coenen, AML; Booij, LHDJ
2005-01-01
Background: This study assessed the feasibility of online calculation of the correlation integral (C(r)) aiming to apply C(r)derived statistics. For real-time application it is important to reduce calculation time. It is shown how our method works for EEG time series. Methods: To achieve online
Broek, P.L.C. van den; Egmond, J. van; Rijn, C.M. van; Takens, F.; Coenen, A.M.L.; Booij, L.H.D.J.
2005-01-01
This study assessed the feasibility of online calculation of the correlation integral (C(r)) aiming to apply C(r)-derived statistics. For real-time application it is important to reduce calculation time. It is shown how our method works for EEG time series. Methods: To achieve online calculation of
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
Best Practices in Teaching Statistics and Research Methods in the Behavioral Sciences [with CD-ROM
Dunn, Dana S., Ed.; Smith, Randolph A., Ed.; Beins, Barney, Ed.
2007-01-01
This book provides a showcase for "best practices" in teaching statistics and research methods in two- and four-year colleges and universities. A helpful resource for teaching introductory, intermediate, and advanced statistics and/or methods, the book features coverage of: (1) ways to integrate these courses; (2) how to promote ethical conduct;…
Statistical methods of estimating mining costs
Long, K.R.
2011-01-01
Until it was defunded in 1995, the U.S. Bureau of Mines maintained a Cost Estimating System (CES) for prefeasibility-type economic evaluations of mineral deposits and estimating costs at producing and non-producing mines. This system had a significant role in mineral resource assessments to estimate costs of developing and operating known mineral deposits and predicted undiscovered deposits. For legal reasons, the U.S. Geological Survey cannot update and maintain CES. Instead, statistical tools are under development to estimate mining costs from basic properties of mineral deposits such as tonnage, grade, mineralogy, depth, strip ratio, distance from infrastructure, rock strength, and work index. The first step was to reestimate "Taylor's Rule" which relates operating rate to available ore tonnage. The second step was to estimate statistical models of capital and operating costs for open pit porphyry copper mines with flotation concentrators. For a sample of 27 proposed porphyry copper projects, capital costs can be estimated from three variables: mineral processing rate, strip ratio, and distance from nearest railroad before mine construction began. Of all the variables tested, operating costs were found to be significantly correlated only with strip ratio.
Innovative statistical methods for public health data
Wilson, Jeffrey
2015-01-01
The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference, and it can be used in graduate level classes.
Methods of contemporary mathematical statistical physics
2009-01-01
This volume presents a collection of courses introducing the reader to the recent progress with attention being paid to laying solid grounds and developing various basic tools. An introductory chapter on lattice spin models is useful as a background for other lectures of the collection. The topics include new results on phase transitions for gradient lattice models (with introduction to the techniques of the reflection positivity), stochastic geometry reformulation of classical and quantum Ising models, the localization/delocalization transition for directed polymers. A general rigorous framework for theory of metastability is presented and particular applications in the context of Glauber and Kawasaki dynamics of lattice models are discussed. A pedagogical account of several recently discussed topics in nonequilibrium statistical mechanics with an emphasis on general principles is followed by a discussion of kinetically constrained spin models that are reflecting important peculiar features of glassy dynamic...
MSD Recombination Method in Statistical Machine Translation
Gros, Jerneja Žganec
2008-11-01
Freely available tools and language resources were used to build the VoiceTRAN statistical machine translation (SMT) system. Various configuration variations of the system are presented and evaluated. The VoiceTRAN SMT system outperformed the baseline conventional rule-based MT system in all English-Slovenian in-domain test setups. To further increase the generalization capability of the translation model for lower-coverage out-of-domain test sentences, an "MSD-recombination" approach was proposed. This approach not only allows a better exploitation of conventional translation models, but also performs well in the more demanding translation direction; that is, into a highly inflectional language. Using this approach in the out-of-domain setup of the English-Slovenian JRC-ACQUIS task, we have achieved significant improvements in translation quality.
Bayesian statistic methods and theri application in probabilistic simulation models
Directory of Open Access Journals (Sweden)
Sergio Iannazzo
2007-03-01
Full Text Available Bayesian statistic methods are facing a rapidly growing level of interest and acceptance in the field of health economics. The reasons of this success are probably to be found on the theoretical fundaments of the discipline that make these techniques more appealing to decision analysis. To this point should be added the modern IT progress that has developed different flexible and powerful statistical software framework. Among them probably one of the most noticeably is the BUGS language project and its standalone application for MS Windows WinBUGS. Scope of this paper is to introduce the subject and to show some interesting applications of WinBUGS in developing complex economical models based on Markov chains. The advantages of this approach reside on the elegance of the code produced and in its capability to easily develop probabilistic simulations. Moreover an example of the integration of bayesian inference models in a Markov model is shown. This last feature let the analyst conduce statistical analyses on the available sources of evidence and exploit them directly as inputs in the economic model.
Statistical methods for categorical data analysis
Powers, Daniel
2008-01-01
This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/
Information Geometry, Inference Methods and Chaotic Energy Levels Statistics
Cafaro, Carlo
2008-01-01
In this Letter, we propose a novel information-geometric characterization of chaotic (integrable) energy level statistics of a quantum antiferromagnetic Ising spin chain in a tilted (transverse) external magnetic field. Finally, we conjecture our results might find some potential physical applications in quantum energy level statistics.
Statistical methods and computing for big data
Wang, Chun; Chen, Ming-Hui; Schifano, Elizabeth; Wu, Jing
2016-01-01
Big data are data on a massive scale in terms of volume, intensity, and complexity that exceed the capacity of standard analytic tools. They present opportunities as well as challenges to statisticians. The role of computational statisticians in scientific discovery from big data analyses has been under-recognized even by peer statisticians. This article summarizes recent methodological and software developments in statistics that address the big data challenges. Methodologies are grouped into three classes: subsampling-based, divide and conquer, and online updating for stream data. As a new contribution, the online updating approach is extended to variable selection with commonly used criteria, and their performances are assessed in a simulation study with stream data. Software packages are summarized with focuses on the open source R and R packages, covering recent tools that help break the barriers of computer memory and computing power. Some of the tools are illustrated in a case study with a logistic regression for the chance of airline delay. PMID:27695593
Statistical methods and computing for big data.
Wang, Chun; Chen, Ming-Hui; Schifano, Elizabeth; Wu, Jing; Yan, Jun
2016-01-01
Big data are data on a massive scale in terms of volume, intensity, and complexity that exceed the capacity of standard analytic tools. They present opportunities as well as challenges to statisticians. The role of computational statisticians in scientific discovery from big data analyses has been under-recognized even by peer statisticians. This article summarizes recent methodological and software developments in statistics that address the big data challenges. Methodologies are grouped into three classes: subsampling-based, divide and conquer, and online updating for stream data. As a new contribution, the online updating approach is extended to variable selection with commonly used criteria, and their performances are assessed in a simulation study with stream data. Software packages are summarized with focuses on the open source R and R packages, covering recent tools that help break the barriers of computer memory and computing power. Some of the tools are illustrated in a case study with a logistic regression for the chance of airline delay.
Simple statistical methods for software engineering data and patterns
Pandian, C Ravindranath
2015-01-01
Although there are countless books on statistics, few are dedicated to the application of statistical methods to software engineering. Simple Statistical Methods for Software Engineering: Data and Patterns fills that void. Instead of delving into overly complex statistics, the book details simpler solutions that are just as effective and connect with the intuition of problem solvers.Sharing valuable insights into software engineering problems and solutions, the book not only explains the required statistical methods, but also provides many examples, review questions, and case studies that prov
Grassmann methods in lattice field theory and statistical mechanics
International Nuclear Information System (INIS)
Bilgici, E.; Gattringer, C.; Huber, P.
2006-01-01
Full text: In two dimensions models of loops can be represented as simple Grassmann integrals. In our work we explore the generalization of these techniques to lattice field theories and statistical mechanic systems in three and four dimensions. We discuss possible strategies and applications for representations of loop and surface models as Grassmann integrals. (author)
Cratering statistics on asteroids: Methods and perspectives
Chapman, C.
2014-07-01
Crater size-frequency distributions (SFDs) on the surfaces of solid-surfaced bodies in the solar system have provided valuable insights about planetary surface processes and about impactor populations since the first spacecraft images were obtained in the 1960s. They can be used to determine relative age differences between surficial units, to obtain absolute model ages if the impactor flux and scaling laws are understood, to assess various endogenic planetary or asteroidal processes that degrade craters or resurface units, as well as assess changes in impactor populations across the solar system and/or with time. The first asteroid SFDs were measured from Galileo images of Gaspra and Ida (cf., Chapman 2002). Despite the superficial simplicity of these studies, they are fraught with many difficulties, including confusion by secondary and/or endogenic cratering and poorly understood aspects of varying target properties (including regoliths, ejecta blankets, and nearly-zero-g rubble piles), widely varying attributes of impactors, and a host of methodological problems including recognizability of degraded craters, which is affected by illumination angle and by the ''personal equations'' of analysts. Indeed, controlled studies (Robbins et al. 2014) demonstrate crater-density differences of a factor of two or more between experienced crater counters. These inherent difficulties have been especially apparent in divergent results for Vesta from different members of the Dawn Science Team (cf. Russell et al. 2013). Indeed, they have been exacerbated by misuse of a widely available tool (Craterstats: hrscview.fu- berlin.de/craterstats.html), which incorrectly computes error bars for proper interpretation of cumulative SFDs, resulting in derived model ages specified to three significant figures and interpretations of statistically insignificant kinks. They are further exacerbated, and for other small-body crater SFDs analyzed by the Berlin group, by stubbornly adopting
Statistical methods for handling incomplete data
Kim, Jae Kwang
2013-01-01
""… this book nicely blends the theoretical material and its application through examples, and will be of interest to students and researchers as a textbook or a reference book. Extensive coverage of recent advances in handling missing data provides resources and guidelines for researchers and practitioners in implementing the methods in new settings. … I plan to use this as a textbook for my teaching and highly recommend it.""-Biometrics, September 2014
Dai, Mingwei; Ming, Jingsi; Cai, Mingxuan; Liu, Jin; Yang, Can; Wan, Xiang; Xu, Zongben
2017-09-15
Results from genome-wide association studies (GWAS) suggest that a complex phenotype is often affected by many variants with small effects, known as 'polygenicity'. Tens of thousands of samples are often required to ensure statistical power of identifying these variants with small effects. However, it is often the case that a research group can only get approval for the access to individual-level genotype data with a limited sample size (e.g. a few hundreds or thousands). Meanwhile, summary statistics generated using single-variant-based analysis are becoming publicly available. The sample sizes associated with the summary statistics datasets are usually quite large. How to make the most efficient use of existing abundant data resources largely remains an open question. In this study, we propose a statistical approach, IGESS, to increasing statistical power of identifying risk variants and improving accuracy of risk prediction by i ntegrating individual level ge notype data and s ummary s tatistics. An efficient algorithm based on variational inference is developed to handle the genome-wide analysis. Through comprehensive simulation studies, we demonstrated the advantages of IGESS over the methods which take either individual-level data or summary statistics data as input. We applied IGESS to perform integrative analysis of Crohns Disease from WTCCC and summary statistics from other studies. IGESS was able to significantly increase the statistical power of identifying risk variants and improve the risk prediction accuracy from 63.2% ( ±0.4% ) to 69.4% ( ±0.1% ) using about 240 000 variants. The IGESS software is available at https://github.com/daviddaigithub/IGESS . zbxu@xjtu.edu.cn or xwan@comp.hkbu.edu.hk or eeyang@hkbu.edu.hk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
ASPECTS OF INTEGRATION MANAGEMENT METHODS
Directory of Open Access Journals (Sweden)
Artemy Varshapetian
2015-10-01
Full Text Available For manufacturing companies to succeed in today's unstable economic environment, it is necessary to restructure the main components of its activities: designing innovative product, production using modern reconfigurable manufacturing systems, a business model that takes into account the global strategy and management methods using modern management models and tools. The first three components are discussed in numerous publications, for example, (Koren, 2010 and is therefore not considered in the article. A large number of publications devoted to the methods and tools of production management, for example (Halevi, 2007. On the basis of what was said in the article discusses the possibility of the integration of only three methods have received in recent years, the most widely used, namely: Six Sigma method - SS (George et al., 2005 and supplements its-Design for six sigm? - DFSS (Taguchi, 2003; Lean production transformed with the development to the "Lean management" and further to the "Lean thinking" - Lean (Hirano et al., 2006; Theory of Constraints, developed E.Goldratt - TOC (Dettmer, 2001. The article investigates some aspects of this integration: applications in diverse fields, positive features, changes in management structure, etc.
Statistical methods and their applications in constructional engineering
International Nuclear Information System (INIS)
1977-01-01
An introduction into the basic terms of statistics is followed by a discussion of elements of the probability theory, customary discrete and continuous distributions, simulation methods, statistical supporting framework dynamics, and a cost-benefit analysis of the methods introduced. (RW) [de
Methods for enhancing numerical integration
International Nuclear Information System (INIS)
Doncker, Elise de
2003-01-01
We give a survey of common strategies for numerical integration (adaptive, Monte-Carlo, Quasi-Monte Carlo), and attempt to delineate their realm of applicability. The inherent accuracy and error bounds for basic integration methods are given via such measures as the degree of precision of cubature rules, the index of a family of lattice rules, and the discrepancy of uniformly distributed point sets. Strategies incorporating these basic methods often use paradigms to reduce the error by, e.g., increasing the number of points in the domain or decreasing the mesh size, locally or uniformly. For these processes the order of convergence of the strategy is determined by the asymptotic behavior of the error, and may be too slow in practice for the type of problem at hand. For certain problem classes we may be able to improve the effectiveness of the method or strategy by such techniques as transformations, absorbing a difficult part of the integrand into a weight function, suitable partitioning of the domain, transformations and extrapolation or convergence acceleration. Situations warranting the use of these techniques (possibly in an 'automated' way) are described and illustrated by sample applications
Online Statistics Labs in MSW Research Methods Courses: Reducing Reluctance toward Statistics
Elliott, William; Choi, Eunhee; Friedline, Terri
2013-01-01
This article presents results from an evaluation of an online statistics lab as part of a foundations research methods course for master's-level social work students. The article discusses factors that contribute to an environment in social work that fosters attitudes of reluctance toward learning and teaching statistics in research methods…
Application of nonparametric statistic method for DNBR limit calculation
International Nuclear Information System (INIS)
Dong Bo; Kuang Bo; Zhu Xuenong
2013-01-01
Background: Nonparametric statistical method is a kind of statistical inference method not depending on a certain distribution; it calculates the tolerance limits under certain probability level and confidence through sampling methods. The DNBR margin is one important parameter of NPP design, which presents the safety level of NPP. Purpose and Methods: This paper uses nonparametric statistical method basing on Wilks formula and VIPER-01 subchannel analysis code to calculate the DNBR design limits (DL) of 300 MW NPP (Nuclear Power Plant) during the complete loss of flow accident, simultaneously compared with the DL of DNBR through means of ITDP to get certain DNBR margin. Results: The results indicate that this method can gain 2.96% DNBR margin more than that obtained by ITDP methodology. Conclusions: Because of the reduction of the conservation during analysis process, the nonparametric statistical method can provide greater DNBR margin and the increase of DNBR margin is benefited for the upgrading of core refuel scheme. (authors)
International Nuclear Information System (INIS)
Gonchar, N.S.
1986-01-01
This paper presents a mathematical method developed for investigating a class of systems of infinite-dimensional integral equations which have application in statistical mechanics. Necessary and sufficient conditions are obtained for the uniqueness and bifurcation of the solution of this class of systems of equations. Problems of equilibrium statistical mechanics are considered on the basis of this method
An integrating factor matrix method to find first integrals
International Nuclear Information System (INIS)
Saputra, K V I; Quispel, G R W; Van Veen, L
2010-01-01
In this paper we develop an integrating factor matrix method to derive conditions for the existence of first integrals. We use this novel method to obtain first integrals, along with the conditions for their existence, for two- and three-dimensional Lotka-Volterra systems with constant terms. The results are compared to previous results obtained by other methods.
The estimation of the measurement results with using statistical methods
International Nuclear Information System (INIS)
Ukrmetrteststandard, 4, Metrologichna Str., 03680, Kyiv (Ukraine))" data-affiliation=" (State Enterprise Ukrmetrteststandard, 4, Metrologichna Str., 03680, Kyiv (Ukraine))" >Velychko, O; UkrNDIspirtbioprod, 3, Babushkina Lane, 03190, Kyiv (Ukraine))" data-affiliation=" (State Scientific Institution UkrNDIspirtbioprod, 3, Babushkina Lane, 03190, Kyiv (Ukraine))" >Gordiyenko, T
2015-01-01
The row of international standards and guides describe various statistical methods that apply for a management, control and improvement of processes with the purpose of realization of analysis of the technical measurement results. The analysis of international standards and guides on statistical methods estimation of the measurement results recommendations for those applications in laboratories is described. For realization of analysis of standards and guides the cause-and-effect Ishikawa diagrams concerting to application of statistical methods for estimation of the measurement results are constructed
The estimation of the measurement results with using statistical methods
Velychko, O.; Gordiyenko, T.
2015-02-01
The row of international standards and guides describe various statistical methods that apply for a management, control and improvement of processes with the purpose of realization of analysis of the technical measurement results. The analysis of international standards and guides on statistical methods estimation of the measurement results recommendations for those applications in laboratories is described. For realization of analysis of standards and guides the cause-and-effect Ishikawa diagrams concerting to application of statistical methods for estimation of the measurement results are constructed.
Statistical methods for accurately determining criticality code bias
International Nuclear Information System (INIS)
Trumble, E.F.; Kimball, K.D.
1997-01-01
A system of statistically treating validation calculations for the purpose of determining computer code bias is provided in this paper. The following statistical treatments are described: weighted regression analysis, lower tolerance limit, lower tolerance band, and lower confidence band. These methods meet the criticality code validation requirements of ANS 8.1. 8 refs., 5 figs., 4 tabs
Statistics of Monte Carlo methods used in radiation transport calculation
International Nuclear Information System (INIS)
Datta, D.
2009-01-01
Radiation transport calculation can be carried out by using either deterministic or statistical methods. Radiation transport calculation based on statistical methods is basic theme of the Monte Carlo methods. The aim of this lecture is to describe the fundamental statistics required to build the foundations of Monte Carlo technique for radiation transport calculation. Lecture note is organized in the following way. Section (1) will describe the introduction of Basic Monte Carlo and its classification towards the respective field. Section (2) will describe the random sampling methods, a key component of Monte Carlo radiation transport calculation, Section (3) will provide the statistical uncertainty of Monte Carlo estimates, Section (4) will describe in brief the importance of variance reduction techniques while sampling particles such as photon, or neutron in the process of radiation transport
Longitudinal data analysis a handbook of modern statistical methods
Fitzmaurice, Garrett; Verbeke, Geert; Molenberghs, Geert
2008-01-01
Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data. After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint
Statistical methods for evaluating the attainment of cleanup standards
Energy Technology Data Exchange (ETDEWEB)
Gilbert, R.O.; Simpson, J.C.
1992-12-01
This document is the third volume in a series of volumes sponsored by the US Environmental Protection Agency (EPA), Statistical Policy Branch, that provide statistical methods for evaluating the attainment of cleanup Standards at Superfund sites. Volume 1 (USEPA 1989a) provides sampling designs and tests for evaluating attainment of risk-based standards for soils and solid media. Volume 2 (USEPA 1992) provides designs and tests for evaluating attainment of risk-based standards for groundwater. The purpose of this third volume is to provide statistical procedures for designing sampling programs and conducting statistical tests to determine whether pollution parameters in remediated soils and solid media at Superfund sites attain site-specific reference-based standards. This.document is written for individuals who may not have extensive training or experience with statistical methods. The intended audience includes EPA regional remedial project managers, Superfund-site potentially responsible parties, state environmental protection agencies, and contractors for these groups.
Complex Data Modeling and Computationally Intensive Statistical Methods
Mantovan, Pietro
2010-01-01
The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time financial data, system control datasets. The analysis of this data poses new challenging problems and requires the development of novel statistical models and computational methods, fueling many fascinating and fast growing research areas of modern statistics. The book offers a wide variety of statistical methods and is addressed to statistici
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
DEFF Research Database (Denmark)
Hauschild, A.C.; Baumbach, Jan; Baumbach, J.
2012-01-01
sophisticated statistical learning techniques for VOC-based feature selection and supervised classification into patient groups. We analyzed breath data from 84 volunteers, each of them either suffering from chronic obstructive pulmonary disease (COPD), or both COPD and bronchial carcinoma (COPD + BC), as well...... as from 35 healthy volunteers, comprising a control group (CG). We standardized and integrated several statistical learning methods to provide a broad overview of their potential for distinguishing the patient groups. We found that there is strong potential for separating MCC/IMS chromatograms of healthy...... patients from healthy controls. We conclude that these statistical learning methods have a generally high accuracy when applied to well-structured, medical MCC/IMS data....
Analysis of Statistical Methods Currently used in Toxicology Journals.
Na, Jihye; Yang, Hyeri; Bae, SeungJin; Lim, Kyung-Min
2014-09-01
Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health.
Integral methods in low-frequency electromagnetics
Solin, Pavel; Karban, Pavel; Ulrych, Bohus
2009-01-01
A modern presentation of integral methods in low-frequency electromagnetics This book provides state-of-the-art knowledge on integral methods in low-frequency electromagnetics. Blending theory with numerous examples, it introduces key aspects of the integral methods used in engineering as a powerful alternative to PDE-based models. Readers will get complete coverage of: The electromagnetic field and its basic characteristics An overview of solution methods Solutions of electromagnetic fields by integral expressions Integral and integrodifferential methods
Brief guidelines for methods and statistics in medical research
Ab Rahman, Jamalludin
2015-01-01
This book serves as a practical guide to methods and statistics in medical research. It includes step-by-step instructions on using SPSS software for statistical analysis, as well as relevant examples to help those readers who are new to research in health and medical fields. Simple texts and diagrams are provided to help explain the concepts covered, and print screens for the statistical steps and the SPSS outputs are provided, together with interpretations and examples of how to report on findings. Brief Guidelines for Methods and Statistics in Medical Research offers a valuable quick reference guide for healthcare students and practitioners conducting research in health related fields, written in an accessible style.
Fundamentals of modern statistical methods substantially improving power and accuracy
Wilcox, Rand R
2001-01-01
Conventional statistical methods have a very serious flaw They routinely miss differences among groups or associations among variables that are detected by more modern techniques - even under very small departures from normality Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable Improved methods have been derived, but they are far from obvious or intuitive based on the training most researchers receive Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods Without assuming any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand The emphasis is on verbal and graphical descriptions of concepts Part II describes modern methods that address the problems covered in Part I Using data from actual studies, many examples are include...
Quantitative EEG Applying the Statistical Recognition Pattern Method
DEFF Research Database (Denmark)
Engedal, Knut; Snaedal, Jon; Hoegh, Peter
2015-01-01
BACKGROUND/AIM: The aim of this study was to examine the discriminatory power of quantitative EEG (qEEG) applying the statistical pattern recognition (SPR) method to separate Alzheimer's disease (AD) patients from elderly individuals without dementia and from other dementia patients. METHODS...
An Overview of Short-term Statistical Forecasting Methods
DEFF Research Database (Denmark)
Elias, Russell J.; Montgomery, Douglas C.; Kulahci, Murat
2006-01-01
An overview of statistical forecasting methodology is given, focusing on techniques appropriate to short- and medium-term forecasts. Topics include basic definitions and terminology, smoothing methods, ARIMA models, regression methods, dynamic regression models, and transfer functions. Techniques...... for evaluating and monitoring forecast performance are also summarized....
Hierarchical modelling for the environmental sciences statistical methods and applications
Clark, James S
2006-01-01
New statistical tools are changing the way in which scientists analyze and interpret data and models. Hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide a consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complicated, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences.
Glushak, P. A.; Markiv, B. B.; Tokarchuk, M. V.
2018-01-01
We present a generalization of Zubarev's nonequilibrium statistical operator method based on the principle of maximum Renyi entropy. In the framework of this approach, we obtain transport equations for the basic set of parameters of the reduced description of nonequilibrium processes in a classical system of interacting particles using Liouville equations with fractional derivatives. For a classical systems of particles in a medium with a fractal structure, we obtain a non-Markovian diffusion equation with fractional spatial derivatives. For a concrete model of the frequency dependence of a memory function, we obtain generalized Kettano-type diffusion equation with the spatial and temporal fractality taken into account. We present a generalization of nonequilibrium thermofield dynamics in Zubarev's nonequilibrium statistical operator method in the framework of Renyi statistics.
Descriptive and inferential statistical methods used in burns research.
Al-Benna, Sammy; Al-Ajam, Yazan; Way, Benjamin; Steinstraesser, Lars
2010-05-01
Burns research articles utilise a variety of descriptive and inferential methods to present and analyse data. The aim of this study was to determine the descriptive methods (e.g. mean, median, SD, range, etc.) and survey the use of inferential methods (statistical tests) used in articles in the journal Burns. This study defined its population as all original articles published in the journal Burns in 2007. Letters to the editor, brief reports, reviews, and case reports were excluded. Study characteristics, use of descriptive statistics and the number and types of statistical methods employed were evaluated. Of the 51 articles analysed, 11(22%) were randomised controlled trials, 18(35%) were cohort studies, 11(22%) were case control studies and 11(22%) were case series. The study design and objectives were defined in all articles. All articles made use of continuous and descriptive data. Inferential statistics were used in 49(96%) articles. Data dispersion was calculated by standard deviation in 30(59%). Standard error of the mean was quoted in 19(37%). The statistical software product was named in 33(65%). Of the 49 articles that used inferential statistics, the tests were named in 47(96%). The 6 most common tests used (Student's t-test (53%), analysis of variance/co-variance (33%), chi(2) test (27%), Wilcoxon & Mann-Whitney tests (22%), Fisher's exact test (12%)) accounted for the majority (72%) of statistical methods employed. A specified significance level was named in 43(88%) and the exact significance levels were reported in 28(57%). Descriptive analysis and basic statistical techniques account for most of the statistical tests reported. This information should prove useful in deciding which tests should be emphasised in educating burn care professionals. These results highlight the need for burn care professionals to have a sound understanding of basic statistics, which is crucial in interpreting and reporting data. Advice should be sought from professionals
Statistical-mechanical entropy by the thin-layer method
International Nuclear Information System (INIS)
Feng, He; Kim, Sung Won
2003-01-01
G. Hooft first studied the statistical-mechanical entropy of a scalar field in a Schwarzschild black hole background by the brick-wall method and hinted that the statistical-mechanical entropy is the statistical origin of the Bekenstein-Hawking entropy of the black hole. However, according to our viewpoint, the statistical-mechanical entropy is only a quantum correction to the Bekenstein-Hawking entropy of the black-hole. The brick-wall method based on thermal equilibrium at a large scale cannot be applied to the cases out of equilibrium such as a nonstationary black hole. The statistical-mechanical entropy of a scalar field in a nonstationary black hole background is calculated by the thin-layer method. The condition of local equilibrium near the horizon of the black hole is used as a working postulate and is maintained for a black hole which evaporates slowly enough and whose mass is far greater than the Planck mass. The statistical-mechanical entropy is also proportional to the area of the black hole horizon. The difference from the stationary black hole is that the result relies on a time-dependent cutoff
Academic Training Lecture: Statistical Methods for Particle Physics
PH Department
2012-01-01
2, 3, 4 and 5 April 2012 Academic Training Lecture Regular Programme from 11:00 to 12:00 - Bldg. 222-R-001 - Filtration Plant Statistical Methods for Particle Physics by Glen Cowan (Royal Holloway) The series of four lectures will introduce some of the important statistical methods used in Particle Physics, and should be particularly relevant to those involved in the analysis of LHC data. The lectures will include an introduction to statistical tests, parameter estimation, and the application of these tools to searches for new phenomena. Both frequentist and Bayesian methods will be described, with particular emphasis on treatment of systematic uncertainties. The lectures will also cover unfolding, that is, estimation of a distribution in binned form where the variable in question is subject to measurement errors.
Methods library of embedded R functions at Statistics Norway
Directory of Open Access Journals (Sweden)
Øyvind Langsrud
2017-11-01
Full Text Available Statistics Norway is modernising the production processes. An important element in this work is a library of functions for statistical computations. In principle, the functions in such a methods library can be programmed in several languages. A modernised production environment demand that these functions can be reused for different statistics products, and that they are embedded within a common IT system. The embedding should be done in such a way that the users of the methods do not need to know the underlying programming language. As a proof of concept, Statistics Norway soon has established a methods library offering a limited number of methods for macro-editing, imputation and confidentiality. This is done within an area of municipal statistics with R as the only programming language. This paper presents the details and experiences from this work. The problem of fitting real word applications to simple and strict standards is discussed and exemplified by the development of solutions to regression imputation and table suppression.
Enterprise Human Resources Integration-Statistical Data Mart (EHRI-SDM) Status Data
Office of Personnel Management — The Enterprise Human Resources Integration-Statistical Data Mart (EHRI-SDM) is a statistically cleansed sub-set of the data contained in the EHRI data warehouse. It...
Enterprise Human Resources Integration-Statistical Data Mart (EHRI-SDM) Dynamics Data
Office of Personnel Management — The Enterprise Human Resources Integration-Statistical Data Mart (EHRI-SDM) is a statistically cleansed sub-set of the data contained in the EHRI data warehouse. It...
Statistical Methods for Particle Physics (4/4)
CERN. Geneva
2012-01-01
The series of four lectures will introduce some of the important statistical methods used in Particle Physics, and should be particularly relevant to those involved in the analysis of LHC data. The lectures will include an introduction to statistical tests, parameter estimation, and the application of these tools to searches for new phenomena. Both frequentist and Bayesian methods will be described, with particular emphasis on treatment of systematic uncertainties. The lectures will also cover unfolding, that is, estimation of a distribution in binned form where the variable in question is subject to measurement errors.
Statistical Methods for Particle Physics (1/4)
CERN. Geneva
2012-01-01
The series of four lectures will introduce some of the important statistical methods used in Particle Physics, and should be particularly relevant to those involved in the analysis of LHC data. The lectures will include an introduction to statistical tests, parameter estimation, and the application of these tools to searches for new phenomena. Both frequentist and Bayesian methods will be described, with particular emphasis on treatment of systematic uncertainties. The lectures will also cover unfolding, that is, estimation of a distribution in binned form where the variable in question is subject to measurement errors.
Statistical Methods for Particle Physics (2/4)
CERN. Geneva
2012-01-01
The series of four lectures will introduce some of the important statistical methods used in Particle Physics, and should be particularly relevant to those involved in the analysis of LHC data. The lectures will include an introduction to statistical tests, parameter estimation, and the application of these tools to searches for new phenomena. Both frequentist and Bayesian methods will be described, with particular emphasis on treatment of systematic uncertainties. The lectures will also cover unfolding, that is, estimation of a distribution in binned form where the variable in question is subject to measurement errors.
Statistical Methods for Particle Physics (3/4)
CERN. Geneva
2012-01-01
The series of four lectures will introduce some of the important statistical methods used in Particle Physics, and should be particularly relevant to those involved in the analysis of LHC data. The lectures will include an introduction to statistical tests, parameter estimation, and the application of these tools to searches for new phenomena. Both frequentist and Bayesian methods will be described, with particular emphasis on treatment of systematic uncertainties. The lectures will also cover unfolding, that is, estimation of a distribution in binned form where the variable in question is subject to measurement errors.
Skinner, Carl G; Patel, Manish M; Thomas, Jerry D; Miller, Michael A
2011-01-01
Statistical methods are pervasive in medical research and general medical literature. Understanding general statistical concepts will enhance our ability to critically appraise the current literature and ultimately improve the delivery of patient care. This article intends to provide an overview of the common statistical methods relevant to medicine.
Methods and statistics for combining motif match scores.
Bailey, T L; Gribskov, M
1998-01-01
Position-specific scoring matrices are useful for representing and searching for protein sequence motifs. A sequence family can often be described by a group of one or more motifs, and an effective search must combine the scores for matching a sequence to each of the motifs in the group. We describe three methods for combining match scores and estimating the statistical significance of the combined scores and evaluate the search quality (classification accuracy) and the accuracy of the estimate of statistical significance of each. The three methods are: 1) sum of scores, 2) sum of reduced variates, 3) product of score p-values. We show that method 3) is superior to the other two methods in both regards, and that combining motif scores indeed gives better search accuracy. The MAST sequence homology search algorithm utilizing the product of p-values scoring method is available for interactive use and downloading at URL http:/(/)www.sdsc.edu/MEME.
Advances in Statistical Methods for Substance Abuse Prevention Research
MacKinnon, David P.; Lockwood, Chondra M.
2010-01-01
The paper describes advances in statistical methods for prevention research with a particular focus on substance abuse prevention. Standard analysis methods are extended to the typical research designs and characteristics of the data collected in prevention research. Prevention research often includes longitudinal measurement, clustering of data in units such as schools or clinics, missing data, and categorical as well as continuous outcome variables. Statistical methods to handle these features of prevention data are outlined. Developments in mediation, moderation, and implementation analysis allow for the extraction of more detailed information from a prevention study. Advancements in the interpretation of prevention research results include more widespread calculation of effect size and statistical power, the use of confidence intervals as well as hypothesis testing, detailed causal analysis of research findings, and meta-analysis. The increased availability of statistical software has contributed greatly to the use of new methods in prevention research. It is likely that the Internet will continue to stimulate the development and application of new methods. PMID:12940467
Statistical methods of parameter estimation for deterministically chaotic time series
Pisarenko, V. F.; Sornette, D.
2004-03-01
We discuss the possibility of applying some standard statistical methods (the least-square method, the maximum likelihood method, and the method of statistical moments for estimation of parameters) to deterministically chaotic low-dimensional dynamic system (the logistic map) containing an observational noise. A “segmentation fitting” maximum likelihood (ML) method is suggested to estimate the structural parameter of the logistic map along with the initial value x1 considered as an additional unknown parameter. The segmentation fitting method, called “piece-wise” ML, is similar in spirit but simpler and has smaller bias than the “multiple shooting” previously proposed. Comparisons with different previously proposed techniques on simulated numerical examples give favorable results (at least, for the investigated combinations of sample size N and noise level). Besides, unlike some suggested techniques, our method does not require the a priori knowledge of the noise variance. We also clarify the nature of the inherent difficulties in the statistical analysis of deterministically chaotic time series and the status of previously proposed Bayesian approaches. We note the trade off between the need of using a large number of data points in the ML analysis to decrease the bias (to guarantee consistency of the estimation) and the unstable nature of dynamical trajectories with exponentially fast loss of memory of the initial condition. The method of statistical moments for the estimation of the parameter of the logistic map is discussed. This method seems to be the unique method whose consistency for deterministically chaotic time series is proved so far theoretically (not only numerically).
RADSS: an integration of GIS, spatial statistics, and network service for regional data mining
Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing
2005-10-01
Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and
Knowledge-Intensive Gathering and Integration of Statistical Information on European Fisheries
Klinkert, M.; Treur, J.; Verwaart, T.; Loganantharaj, R.; Palm, G.; Ali, M.
2000-01-01
Gathering, maintenance, integration and presentation of statistics are major activities of the Dutch Agricultural Economics Research Institute LEI. In this paper we explore how knowledge and agent technology can be exploited to support the information gathering and integration process. In
Landslide Susceptibility Statistical Methods: A Critical and Systematic Literature Review
Mihir, Monika; Malamud, Bruce; Rossi, Mauro; Reichenbach, Paola; Ardizzone, Francesca
2014-05-01
Landslide susceptibility assessment, the subject of this systematic review, is aimed at understanding the spatial probability of slope failures under a set of geomorphological and environmental conditions. It is estimated that about 375 landslides that occur globally each year are fatal, with around 4600 people killed per year. Past studies have brought out the increasing cost of landslide damages which primarily can be attributed to human occupation and increased human activities in the vulnerable environments. Many scientists, to evaluate and reduce landslide risk, have made an effort to efficiently map landslide susceptibility using different statistical methods. In this paper, we do a critical and systematic landslide susceptibility literature review, in terms of the different statistical methods used. For each of a broad set of studies reviewed we note: (i) study geography region and areal extent, (ii) landslide types, (iii) inventory type and temporal period covered, (iv) mapping technique (v) thematic variables used (vi) statistical models, (vii) assessment of model skill, (viii) uncertainty assessment methods, (ix) validation methods. We then pulled out broad trends within our review of landslide susceptibility, particularly regarding the statistical methods. We found that the most common statistical methods used in the study of landslide susceptibility include logistic regression, artificial neural network, discriminant analysis and weight of evidence. Although most of the studies we reviewed assessed the model skill, very few assessed model uncertainty. In terms of geographic extent, the largest number of landslide susceptibility zonations were in Turkey, Korea, Spain, Italy and Malaysia. However, there are also many landslides and fatalities in other localities, particularly India, China, Philippines, Nepal and Indonesia, Guatemala, and Pakistan, where there are much fewer landslide susceptibility studies available in the peer-review literature. This
Colon-Berlingeri, Migdalisel; Burrowes, Patricia A
2011-01-01
Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the undergraduate biology curriculum. The curricular revision included changes in the suggested course sequence, addition of statistics and precalculus as prerequisites to core science courses, and incorporating interdisciplinary (math-biology) learning activities in genetics and zoology courses. In this article, we describe the activities developed for these two courses and the assessment tools used to measure the learning that took place with respect to biology and statistics. We distinguished the effectiveness of these learning opportunities in helping students improve their understanding of the math and statistical concepts addressed and, more importantly, their ability to apply them to solve a biological problem. We also identified areas that need emphasis in both biology and mathematics courses. In light of our observations, we recommend best practices that biology and mathematics academic departments can implement to train undergraduates for the demands of modern biology.
Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics
Abe, Sumiyoshi
2014-11-01
The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.
The application of statistical methods to assess economic assets
Directory of Open Access Journals (Sweden)
D. V. Dianov
2017-01-01
Full Text Available The article is devoted to consideration and evaluation of machinery, equipment and special equipment, methodological aspects of the use of standards for assessment of buildings and structures in current prices, the valuation of residential, specialized houses, office premises, assessment and reassessment of existing and inactive military assets, the application of statistical methods to obtain the relevant cost estimates.The objective of the scientific article is to consider possible application of statistical tools in the valuation of the assets, composing the core group of elements of national wealth – the fixed assets. Firstly, capital tangible assets constitute the basis of material base of a new value creation, products and non-financial services. The gain, accumulated of tangible assets of a capital nature is a part of the gross domestic product, and from its volume and specific weight in the composition of GDP we can judge the scope of reproductive processes in the country.Based on the methodological materials of the state statistics bodies of the Russian Federation, regulations of the theory of statistics, which describe the methods of statistical analysis such as the index, average values, regression, the methodical approach is structured in the application of statistical tools to obtain value estimates of property, plant and equipment with significant accumulated depreciation. Until now, the use of statistical methodology in the practice of economic assessment of assets is only fragmentary. This applies to both Federal Legislation (Federal law № 135 «On valuation activities in the Russian Federation» dated 16.07.1998 in edition 05.07.2016 and the methodological documents and regulations of the estimated activities, in particular, the valuation activities’ standards. A particular problem is the use of a digital database of Rosstat (Federal State Statistics Service, as to the specific fixed assets the comparison should be carried
Experiential Approach to Teaching Statistics and Research Methods ...
African Journals Online (AJOL)
Statistics and research methods are among the more demanding topics for students of education to master at both the undergraduate and postgraduate levels. It is our conviction that teaching these topics should be combined with real practical experiences. We discuss an experiential teaching/ learning approach that ...
Application of statistical methods at copper wire manufacturing
Directory of Open Access Journals (Sweden)
Z. Hajduová
2009-01-01
Full Text Available Six Sigma is a method of management that strives for near perfection. The Six Sigma methodology uses data and rigorous statistical analysis to identify defects in a process or product, reduce variability and achieve as close to zero defects as possible. The paper presents the basic information on this methodology.
Statistical and Machine Learning forecasting methods: Concerns and ways forward.
Makridakis, Spyros; Spiliotis, Evangelos; Assimakopoulos, Vassilios
2018-01-01
Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions.
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
Statistical and Machine Learning forecasting methods: Concerns and ways forward
Makridakis, Spyros; Assimakopoulos, Vassilios
2018-01-01
Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions. PMID:29584784
Illinois' Forests, 2005: Statistics, Methods, and Quality Assurance
Susan J. Crocker; Charles J. Barnett; Mark A. Hatfield
2013-01-01
The first full annual inventory of Illinois' forests was completed in 2005. This report contains 1) descriptive information on methods, statistics, and quality assurance of data collection, 2) a glossary of terms, 3) tables that summarize quality assurance, and 4) a core set of tabular estimates for a variety of forest resources. A detailed analysis of inventory...
Kansas's forests, 2005: statistics, methods, and quality assurance
Patrick D. Miles; W. Keith Moser; Charles J. Barnett
2011-01-01
The first full annual inventory of Kansas's forests was completed in 2005 after 8,868 plots were selected and 468 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of Kansas inventory is presented...
South Dakota's forests, 2005: statistics, methods, and quality assurance
Patrick D. Miles; Ronald J. Piva; Charles J. Barnett
2011-01-01
The first full annual inventory of South Dakota's forests was completed in 2005 after 8,302 plots were selected and 325 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of the South Dakota...
Nebraska's forests, 2005: statistics, methods, and quality assurance
Patrick D. Miles; Dacia M. Meneguzzo; Charles J. Barnett
2011-01-01
The first full annual inventory of Nebraska's forests was completed in 2005 after 8,335 plots were selected and 274 forested plots were visited and measured. This report includes detailed information on forest inventory methods, and data quality estimates. Tables of various important resource statistics are presented. Detailed analysis of the inventory data are...
North Dakota's forests, 2005: statistics, methods, and quality assurance
Patrick D. Miles; David E. Haugen; Charles J. Barnett
2011-01-01
The first full annual inventory of North Dakota's forests was completed in 2005 after 7,622 plots were selected and 164 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of the North Dakota...
Peer-Assisted Learning in Research Methods and Statistics
Stone, Anna; Meade, Claire; Watling, Rosamond
2012-01-01
Feedback from students on a Level 1 Research Methods and Statistics module, studied as a core part of a BSc Psychology programme, highlighted demand for additional tutorials to help them to understand basic concepts. Students in their final year of study commonly request work experience to enhance their employability. All students on the Level 1…
A statistical method for 2D facial landmarking
Dibeklioğlu, H.; Salah, A.A.; Gevers, T.
2012-01-01
Many facial-analysis approaches rely on robust and accurate automatic facial landmarking to correctly function. In this paper, we describe a statistical method for automatic facial-landmark localization. Our landmarking relies on a parsimonious mixture model of Gabor wavelet features, computed in
Investigating salt frost scaling by using statistical methods
DEFF Research Database (Denmark)
Hasholt, Marianne Tange; Clemmensen, Line Katrine Harder
2010-01-01
A large data set comprising data for 118 concrete mixes on mix design, air void structure, and the outcome of freeze/thaw testing according to SS 13 72 44 has been analysed by use of statistical methods. The results show that with regard to mix composition, the most important parameter...
A Bayesian statistical method for particle identification in shower counters
International Nuclear Information System (INIS)
Takashimizu, N.; Kimura, A.; Shibata, A.; Sasaki, T.
2004-01-01
We report an attempt on identifying particles using a Bayesian statistical method. We have developed the mathematical model and software for this purpose. We tried to identify electrons and charged pions in shower counters using this method. We designed an ideal shower counter and studied the efficiency of identification using Monte Carlo simulation based on Geant4. Without having any other information, e.g. charges of particles which are given by tracking detectors, we have achieved 95% identifications of both particles
Quantum statistical Monte Carlo methods and applications to spin systems
International Nuclear Information System (INIS)
Suzuki, M.
1986-01-01
A short review is given concerning the quantum statistical Monte Carlo method based on the equivalence theorem that d-dimensional quantum systems are mapped onto (d+1)-dimensional classical systems. The convergence property of this approximate tansformation is discussed in detail. Some applications of this general appoach to quantum spin systems are reviewed. A new Monte Carlo method, ''thermo field Monte Carlo method,'' is presented, which is an extension of the projection Monte Carlo method at zero temperature to that at finite temperatures
Askerov, Bahram M
2010-01-01
This book deals with theoretical thermodynamics and the statistical physics of electron and particle gases. While treating the laws of thermodynamics from both classical and quantum theoretical viewpoints, it posits that the basis of the statistical theory of macroscopic properties of a system is the microcanonical distribution of isolated systems, from which all canonical distributions stem. To calculate the free energy, the Gibbs method is applied to ideal and non-ideal gases, and also to a crystalline solid. Considerable attention is paid to the Fermi-Dirac and Bose-Einstein quantum statistics and its application to different quantum gases, and electron gas in both metals and semiconductors is considered in a nonequilibrium state. A separate chapter treats the statistical theory of thermodynamic properties of an electron gas in a quantizing magnetic field.
Automatic numerical integration methods for Feynman integrals through 3-loop
International Nuclear Information System (INIS)
De Doncker, E; Olagbemi, O; Yuasa, F; Ishikawa, T; Kato, K
2015-01-01
We give numerical integration results for Feynman loop diagrams through 3-loop such as those covered by Laporta [1]. The methods are based on automatic adaptive integration, using iterated integration and extrapolation with programs from the QUADPACK package, or multivariate techniques from the ParInt package. The Dqags algorithm from QuadPack accommodates boundary singularities of fairly general types. PARINT is a package for multivariate integration layered over MPI (Message Passing Interface), which runs on clusters and incorporates advanced parallel/distributed techniques such as load balancing among processes that may be distributed over a network of nodes. Results are included for 3-loop self-energy diagrams without IR (infra-red) or UV (ultra-violet) singularities. A procedure based on iterated integration and extrapolation yields a novel method of numerical regularization for integrals with UV terms, and is applied to a set of 2-loop self-energy diagrams with UV singularities. (paper)
Application of statistical method for FBR plant transient computation
International Nuclear Information System (INIS)
Kikuchi, Norihiro; Mochizuki, Hiroyasu
2014-01-01
Highlights: • A statistical method with a large trial number up to 10,000 is applied to the plant system analysis. • A turbine trip test conducted at the “Monju” reactor is selected as a plant transient. • A reduction method of trial numbers is discussed. • The result with reduced trial number can express the base regions of the computed distribution. -- Abstract: It is obvious that design tolerances, errors included in operation, and statistical errors in empirical correlations effect on the transient behavior. The purpose of the present study is to apply above mentioned statistical errors to a plant system computation in order to evaluate the statistical distribution contained in the transient evolution. A selected computation case is the turbine trip test conducted at 40% electric power of the prototype fast reactor “Monju”. All of the heat transport systems of “Monju” are modeled with the NETFLOW++ system code which has been validated using the plant transient tests of the experimental fast reactor Joyo, and “Monju”. The effects of parameters on upper plenum temperature are confirmed by sensitivity analyses, and dominant parameters are chosen. The statistical errors are applied to each computation deck by using a pseudorandom number and the Monte-Carlo method. The dSFMT (Double precision SIMD-oriented Fast Mersenne Twister) that is developed version of Mersenne Twister (MT), is adopted as the pseudorandom number generator. In the present study, uniform random numbers are generated by dSFMT, and these random numbers are transformed to the normal distribution by the Box–Muller method. Ten thousands of different computations are performed at once. In every computation case, the steady calculation is performed for 12,000 s, and transient calculation is performed for 4000 s. In the purpose of the present statistical computation, it is important that the base regions of distribution functions should be calculated precisely. A large number of
Statistical methods for assessing agreement between continuous measurements
DEFF Research Database (Denmark)
Sokolowski, Ineta; Hansen, Rikke Pilegaard; Vedsted, Peter
Background: Clinical research often involves study of agreement amongst observers. Agreement can be measured in different ways, and one can obtain quite different values depending on which method one uses. Objective: We review the approaches that have been discussed to assess the agreement between...... continuous measures and discuss their strengths and weaknesses. Different methods are illustrated using actual data from the `Delay in diagnosis of cancer in general practice´ project in Aarhus, Denmark. Subjects and Methods: We use weighted kappa-statistic, intraclass correlation coefficient (ICC......), concordance coefficient, Bland-Altman limits of agreement and percentage of agreement to assess the agreement between patient reported delay and doctor reported delay in diagnosis of cancer in general practice. Key messages: The correct statistical approach is not obvious. Many studies give the product...
Statistical disclosure control for microdata methods and applications in R
Templ, Matthias
2017-01-01
This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data. Introducing readers to the R packages sdcMicro and simPop, the book also features numerous examples and exercises with solutions, as well as case studies with real-world data, accompanied by the underlying R code to allow readers to reproduce all results. The demand for and volume of data from surveys, registers or other sources containing sensible information on persons or enterprises have increased significantly over the last several years. At the same time, privacy protection principles and regulations have imposed restrictions on the access and use of individual data. Proper and secure microdata dissemination calls for the application of statistical disclosure control methods to the data before release. This book is in...
Applied statistical methods in agriculture, health and life sciences
Lawal, Bayo
2014-01-01
This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R. This textbook is developed for undergraduate students in agriculture, nursing, biology and biomedical research. Graduate students will also find it to be a useful way to refresh their statistics skills and to reference software options. The unique combination of examples is approached using MINITAB and R for their individual strengths. Subjects covered include among others data description, probability distributions, experimental design, regression analysis, randomized design and biological assay. Unlike other biostatistics textbooks, this text also includes outliers, influential observations in regression and an introduction to survival analysis. Material is taken from the author's extensive teaching and research in Africa, USA and the UK. Sample problems, references and electronic supplementary material accompany each chapter.
Identification of mine waters by statistical multivariate methods
Energy Technology Data Exchange (ETDEWEB)
Mali, N [IGGG, Ljubljana (Slovenia)
1992-01-01
Three water-bearing aquifers are present in the Velenje lignite mine. The aquifer waters have differing chemical composition; a geochemical water analysis can therefore determine the source of mine water influx. Mine water samples from different locations in the mine were analyzed, the results of chemical content and of electric conductivity of mine water were statistically processed by means of MICROGAS, SPSS-X and IN STATPAC computer programs, which apply three multivariate statistical methods (discriminate, cluster and factor analysis). Reliability of calculated values was determined with the Kolmogorov and Smirnov tests. It is concluded that laboratory analysis of single water samples can produce measurement errors, but statistical processing of water sample data can identify origin and movement of mine water. 15 refs.
Nonequilibrium Statistical Operator Method and Generalized Kinetic Equations
Kuzemsky, A. L.
2018-01-01
We consider some principal problems of nonequilibrium statistical thermodynamics in the framework of the Zubarev nonequilibrium statistical operator approach. We present a brief comparative analysis of some approaches to describing irreversible processes based on the concept of nonequilibrium Gibbs ensembles and their applicability to describing nonequilibrium processes. We discuss the derivation of generalized kinetic equations for a system in a heat bath. We obtain and analyze a damped Schrödinger-type equation for a dynamical system in a heat bath. We study the dynamical behavior of a particle in a medium taking the dissipation effects into account. We consider the scattering problem for neutrons in a nonequilibrium medium and derive a generalized Van Hove formula. We show that the nonequilibrium statistical operator method is an effective, convenient tool for describing irreversible processes in condensed matter.
Integrating Statistical Visualization Research into the Political Science Classroom
Draper, Geoffrey M.; Liu, Baodong; Riesenfeld, Richard F.
2011-01-01
The use of computer software to facilitate learning in political science courses is well established. However, the statistical software packages used in many political science courses can be difficult to use and counter-intuitive. We describe the results of a preliminary user study suggesting that visually-oriented analysis software can help…
Statistical timing for parametric yield prediction of digital integrated circuits
Jess, J.A.G.; Kalafala, K.; Naidu, S.R.; Otten, R.H.J.M.; Visweswariah, C.
2006-01-01
Uncertainty in circuit performance due to manufacturing and environmental variations is increasing with each new generation of technology. It is therefore important to predict the performance of a chip as a probabilistic quantity. This paper proposes three novel path-based algorithms for statistical
Manufacturing Squares: An Integrative Statistical Process Control Exercise
Coy, Steven P.
2016-01-01
In the exercise, students in a junior-level operations management class are asked to manufacture a simple product. Given product specifications, they must design a production process, create roles and design jobs for each team member, and develop a statistical process control plan that efficiently and effectively controls quality during…
Identifying Reflectors in Seismic Images via Statistic and Syntactic Methods
Directory of Open Access Journals (Sweden)
Carlos A. Perez
2010-04-01
Full Text Available In geologic interpretation of seismic reflection data, accurate identification of reflectors is the foremost step to ensure proper subsurface structural definition. Reflector information, along with other data sets, is a key factor to predict the presence of hydrocarbons. In this work, mathematic and pattern recognition theory was adapted to design two statistical and two syntactic algorithms which constitute a tool in semiautomatic reflector identification. The interpretive power of these four schemes was evaluated in terms of prediction accuracy and computational speed. Among these, the semblance method was confirmed to render the greatest accuracy and speed. Syntactic methods offer an interesting alternative due to their inherently structural search method.
Generalized Hamiltonians, functional integration and statistics of continuous fluids and plasmas
International Nuclear Information System (INIS)
Tasso, H.
1985-05-01
Generalized Hamiltonian formalism including generalized Poisson brackets and Lie-Poisson brackets is presented in Section II. Gyroviscous magnetohydrodynamics is treated as a relevant example in Euler and Clebsch variables. Section III is devoted to a short review of functional integration containing the definition and a discussion of ambiguities and methods of evaluation. The main part of the contribution is given in Section IV, where some of the content of the previous sections is applied to Gibbs statistics of continuous fluids and plasmas. In particular, exact fluctuation spectra are calculated for relevant equations in fluids and plasmas. (orig.)
New Graphical Methods and Test Statistics for Testing Composite Normality
Directory of Open Access Journals (Sweden)
Marc S. Paolella
2015-07-01
Full Text Available Several graphical methods for testing univariate composite normality from an i.i.d. sample are presented. They are endowed with correct simultaneous error bounds and yield size-correct tests. As all are based on the empirical CDF, they are also consistent for all alternatives. For one test, called the modified stabilized probability test, or MSP, a highly simplified computational method is derived, which delivers the test statistic and also a highly accurate p-value approximation, essentially instantaneously. The MSP test is demonstrated to have higher power against asymmetric alternatives than the well-known and powerful Jarque-Bera test. A further size-correct test, based on combining two test statistics, is shown to have yet higher power. The methodology employed is fully general and can be applied to any i.i.d. univariate continuous distribution setting.
Statistical learning modeling method for space debris photometric measurement
Sun, Wenjing; Sun, Jinqiu; Zhang, Yanning; Li, Haisen
2016-03-01
Photometric measurement is an important way to identify the space debris, but the present methods of photometric measurement have many constraints on star image and need complex image processing. Aiming at the problems, a statistical learning modeling method for space debris photometric measurement is proposed based on the global consistency of the star image, and the statistical information of star images is used to eliminate the measurement noises. First, the known stars on the star image are divided into training stars and testing stars. Then, the training stars are selected as the least squares fitting parameters to construct the photometric measurement model, and the testing stars are used to calculate the measurement accuracy of the photometric measurement model. Experimental results show that, the accuracy of the proposed photometric measurement model is about 0.1 magnitudes.
Statistic method of research reactors maximum permissible power calculation
International Nuclear Information System (INIS)
Grosheva, N.A.; Kirsanov, G.A.; Konoplev, K.A.; Chmshkyan, D.V.
1998-01-01
The technique for calculating maximum permissible power of a research reactor at which the probability of the thermal-process accident does not exceed the specified value, is presented. The statistical method is used for the calculations. It is regarded that the determining function related to the reactor safety is the known function of the reactor power and many statistically independent values which list includes the reactor process parameters, geometrical characteristics of the reactor core and fuel elements, as well as random factors connected with the reactor specific features. Heat flux density or temperature is taken as a limiting factor. The program realization of the method discussed is briefly described. The results of calculating the PIK reactor margin coefficients for different probabilities of the thermal-process accident are considered as an example. It is shown that the probability of an accident with fuel element melting in hot zone is lower than 10 -8 1 per year for the reactor rated power [ru
Multivariate methods and forecasting with IBM SPSS statistics
Aljandali, Abdulkader
2017-01-01
This is the second of a two-part guide to quantitative analysis using the IBM SPSS Statistics software package; this volume focuses on multivariate statistical methods and advanced forecasting techniques. More often than not, regression models involve more than one independent variable. For example, forecasting methods are commonly applied to aggregates such as inflation rates, unemployment, exchange rates, etc., that have complex relationships with determining variables. This book introduces multivariate regression models and provides examples to help understand theory underpinning the model. The book presents the fundamentals of multivariate regression and then moves on to examine several related techniques that have application in business-orientated fields such as logistic and multinomial regression. Forecasting tools such as the Box-Jenkins approach to time series modeling are introduced, as well as exponential smoothing and naïve techniques. This part also covers hot topics such as Factor Analysis, Dis...
Mathematical and Statistical Methods for Actuarial Sciences and Finance
Legros, Florence; Perna, Cira; Sibillo, Marilena
2017-01-01
This volume gathers selected peer-reviewed papers presented at the international conference "MAF 2016 – Mathematical and Statistical Methods for Actuarial Sciences and Finance”, held in Paris (France) at the Université Paris-Dauphine from March 30 to April 1, 2016. The contributions highlight new ideas on mathematical and statistical methods in actuarial sciences and finance. The cooperation between mathematicians and statisticians working in insurance and finance is a very fruitful field, one that yields unique theoretical models and practical applications, as well as new insights in the discussion of problems of national and international interest. This volume is addressed to academicians, researchers, Ph.D. students and professionals.
Statistical methods for longitudinal data with agricultural applications
DEFF Research Database (Denmark)
Anantharama Ankinakatte, Smitha
The PhD study focuses on modeling two kings of longitudinal data arising in agricultural applications: continuous time series data and discrete longitudinal data. Firstly, two statistical methods, neural networks and generalized additive models, are applied to predict masistis using multivariate...... algorithm. This was found to compare favourably with the algorithm implemented in the well-known Beagle software. Finally, an R package to apply APFA models developed as part of the PhD project is described...
Statistical methods in nuclear material accountancy: Past, present and future
International Nuclear Information System (INIS)
Pike, D.J.; Woods, A.J.
1983-01-01
The analysis of nuclear material inventory data is motivated by the desire to detect any loss or diversion of nuclear material, insofar as such detection may be feasible by statistical analysis of repeated inventory and throughput measurements. The early regulations, which laid down the specifications for the analysis of inventory data, were framed without acknowledging the essentially sequential nature of the data. It is the broad aim of this paper to discuss the historical nature of statistical analysis of inventory data including an evaluation of why statistical methods should be required at all. If it is accepted that statistical techniques are required, then two main areas require extensive discussion. First, it is important to assess the extent to which stated safeguards aims can be met in practice. Second, there is a vital need for reassessment of the statistical techniques which have been proposed for use in nuclear material accountancy. Part of this reassessment must involve a reconciliation of the apparent differences in philosophy shown by statisticians; but, in addition, the techniques themselves need comparative study to see to what extent they are capable of meeting realistic safeguards aims. This paper contains a brief review of techniques with an attempt to compare and contrast the approaches. It will be suggested that much current research is following closely similar lines, and that national and international bodies should encourage collaborative research and practical in-plant implementations. The techniques proposed require credibility and power; but at this point in time statisticians require credibility and a greater level of unanimity in their approach. A way ahead is proposed based on a clear specification of realistic safeguards aims, and a development of a unified statistical approach with encouragement for the performance of joint research. (author)
State analysis of BOP using statistical and heuristic methods
International Nuclear Information System (INIS)
Heo, Gyun Young; Chang, Soon Heung
2003-01-01
Under the deregulation environment, the performance enhancement of BOP in nuclear power plants is being highlighted. To analyze performance level of BOP, we use the performance test procedures provided from an authorized institution such as ASME. However, through plant investigation, it was proved that the requirements of the performance test procedures about the reliability and quantity of sensors was difficult to be satisfied. As a solution of this, state analysis method that are the expanded concept of signal validation, was proposed on the basis of the statistical and heuristic approaches. Authors recommended the statistical linear regression model by analyzing correlation among BOP parameters as a reference state analysis method. Its advantage is that its derivation is not heuristic, it is possible to calculate model uncertainty, and it is easy to apply to an actual plant. The error of the statistical linear regression model is below 3% under normal as well as abnormal system states. Additionally a neural network model was recommended since the statistical model is impossible to apply to the validation of all of the sensors and is sensitive to the outlier that is the signal located out of a statistical distribution. Because there are a lot of sensors need to be validated in BOP, wavelet analysis (WA) were applied as a pre-processor for the reduction of input dimension and for the enhancement of training accuracy. The outlier localization capability of WA enhanced the robustness of the neural network. The trained neural network restored the degraded signals to the values within ±3% of the true signals
Subdomain Precise Integration Method for Periodic Structures
Directory of Open Access Journals (Sweden)
F. Wu
2014-01-01
Full Text Available A subdomain precise integration method is developed for the dynamical responses of periodic structures comprising many identical structural cells. The proposed method is based on the precise integration method, the subdomain scheme, and the repeatability of the periodic structures. In the proposed method, each structural cell is seen as a super element that is solved using the precise integration method, considering the repeatability of the structural cells. The computational efforts and the memory size of the proposed method are reduced, while high computational accuracy is achieved. Therefore, the proposed method is particularly suitable to solve the dynamical responses of periodic structures. Two numerical examples are presented to demonstrate the accuracy and efficiency of the proposed method through comparison with the Newmark and Runge-Kutta methods.
Statistical benchmarking in utility regulation: Role, standards and methods
International Nuclear Information System (INIS)
Newton Lowry, Mark; Getachew, Lullit
2009-01-01
Statistical benchmarking is being used with increasing frequency around the world in utility rate regulation. We discuss how and where benchmarking is in use for this purpose and the pros and cons of regulatory benchmarking. We then discuss alternative performance standards and benchmarking methods in regulatory applications. We use these to propose guidelines for the appropriate use of benchmarking in the rate setting process. The standards, which we term the competitive market and frontier paradigms, have a bearing on method selection. These along with regulatory experience suggest that benchmarking can either be used for prudence review in regulation or to establish rates or rate setting mechanisms directly
Statistical methods of spin assignment in compound nuclear reactions
International Nuclear Information System (INIS)
Mach, H.; Johns, M.W.
1984-01-01
Spin assignment to nuclear levels can be obtained from standard in-beam gamma-ray spectroscopy techniques and in the case of compound nuclear reactions can be complemented by statistical methods. These are based on a correlation pattern between level spin and gamma-ray intensities feeding low-lying levels. Three types of intensity and level spin correlations are found suitable for spin assignment: shapes of the excitation functions, ratio of intensity at two beam energies or populated in two different reactions, and feeding distributions. Various empirical attempts are examined and the range of applicability of these methods as well as the limitations associated with them are given. 12 references
Statistical methods of spin assignment in compound nuclear reactions
International Nuclear Information System (INIS)
Mach, H.; Johns, M.W.
1985-01-01
Spin assignment to nuclear levels can be obtained from standard in-beam gamma-ray spectroscopy techniques and in the case of compound nuclear reactions can be complemented by statistical methods. These are based on a correlation pattern between level spin and gamma-ray intensities feeding low-lying levels. Three types of intensity and level spin correlations are found suitable for spin assignment: shapes of the excitation functions, ratio of intensity at two beam energies or populated in two different reactions, and feeding distributions. Various empirical attempts are examined and the range of applicability of these methods as well as the limitations associated with them are given
On second quantization methods applied to classical statistical mechanics
International Nuclear Information System (INIS)
Matos Neto, A.; Vianna, J.D.M.
1984-01-01
A method of expressing statistical classical results in terms of mathematical entities usually associated to quantum field theoretical treatment of many particle systems (Fock space, commutators, field operators, state vector) is discussed. It is developed a linear response theory using the 'second quantized' Liouville equation introduced by Schonberg. The relationship of this method to that of Prigogine et al. is briefly analyzed. The chain of equations and the spectral representations for the new classical Green's functions are presented. Generalized operators defined on Fock space are discussed. It is shown that the correlation functions can be obtained from Green's functions defined with generalized operators. (Author) [pt
Methods for estimating low-flow statistics for Massachusetts streams
Ries, Kernell G.; Friesz, Paul J.
2000-01-01
Methods and computer software are described in this report for determining flow duration, low-flow frequency statistics, and August median flows. These low-flow statistics can be estimated for unregulated streams in Massachusetts using different methods depending on whether the location of interest is at a streamgaging station, a low-flow partial-record station, or an ungaged site where no data are available. Low-flow statistics for streamgaging stations can be estimated using standard U.S. Geological Survey methods described in the report. The MOVE.1 mathematical method and a graphical correlation method can be used to estimate low-flow statistics for low-flow partial-record stations. The MOVE.1 method is recommended when the relation between measured flows at a partial-record station and daily mean flows at a nearby, hydrologically similar streamgaging station is linear, and the graphical method is recommended when the relation is curved. Equations are presented for computing the variance and equivalent years of record for estimates of low-flow statistics for low-flow partial-record stations when either a single or multiple index stations are used to determine the estimates. The drainage-area ratio method or regression equations can be used to estimate low-flow statistics for ungaged sites where no data are available. The drainage-area ratio method is generally as accurate as or more accurate than regression estimates when the drainage-area ratio for an ungaged site is between 0.3 and 1.5 times the drainage area of the index data-collection site. Regression equations were developed to estimate the natural, long-term 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent duration flows; the 7-day, 2-year and the 7-day, 10-year low flows; and the August median flow for ungaged sites in Massachusetts. Streamflow statistics and basin characteristics for 87 to 133 streamgaging stations and low-flow partial-record stations were used to develop the equations. The
Literature in Focus: Statistical Methods in Experimental Physics
2007-01-01
Frederick James was a high-energy physicist who became the CERN "expert" on statistics and is now well-known around the world, in part for this famous text. The first edition of Statistical Methods in Experimental Physics was originally co-written with four other authors and was published in 1971 by North Holland (now an imprint of Elsevier). It became such an important text that demand for it has continued for more than 30 years. Fred has updated it and it was released in a second edition by World Scientific in 2006. It is still a top seller and there is no exaggeration in calling it «the» reference on the subject. A full review of the title appeared in the October CERN Courier.Come and meet the author to hear more about how this book has flourished during its 35-year lifetime. Frederick James Statistical Methods in Experimental Physics Monday, 26th of November, 4 p.m. Council Chamber (Bldg. 503-1-001) The author will be introduced...
Fuel rod design by statistical methods for MOX fuel
International Nuclear Information System (INIS)
Heins, L.; Landskron, H.
2000-01-01
Statistical methods in fuel rod design have received more and more attention during the last years. One of different possible ways to use statistical methods in fuel rod design can be described as follows: Monte Carlo calculations are performed using the fuel rod code CARO. For each run with CARO, the set of input data is modified: parameters describing the design of the fuel rod (geometrical data, density etc.) and modeling parameters are randomly selected according to their individual distributions. Power histories are varied systematically in a way that each power history of the relevant core management calculation is represented in the Monte Carlo calculations with equal frequency. The frequency distributions of the results as rod internal pressure and cladding strain which are generated by the Monte Carlo calculation are evaluated and compared with the design criteria. Up to now, this methodology has been applied to licensing calculations for PWRs and BWRs, UO 2 and MOX fuel, in 3 countries. Especially for the insertion of MOX fuel resulting in power histories with relatively high linear heat generation rates at higher burnup, the statistical methodology is an appropriate approach to demonstrate the compliance of licensing requirements. (author)
Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical Methods
Directory of Open Access Journals (Sweden)
H. Molladavoodi
2018-01-01
Full Text Available Rock as a natural material is heterogeneous. Rock material consists of minerals, crystals, cement, grains, and microcracks. Each component of rock has a different mechanical behavior under applied loading condition. Therefore, rock component distribution has an important effect on rock mechanical behavior, especially in the postpeak region. In this paper, the rock sample was studied by digital image processing (DIP, micromechanics, and statistical methods. Using image processing, volume fractions of the rock minerals composing the rock sample were evaluated precisely. The mechanical properties of the rock matrix were determined based on upscaling micromechanics. In order to consider the rock heterogeneities effect on mechanical behavior, the heterogeneity index was calculated in a framework of statistical method. A Weibull distribution function was fitted to the Young modulus distribution of minerals. Finally, statistical and Mohr–Coulomb strain-softening models were used simultaneously as a constitutive model in DEM code. The acoustic emission, strain energy release, and the effect of rock heterogeneities on the postpeak behavior process were investigated. The numerical results are in good agreement with experimental data.
THE FLUORBOARD A STATISTICALLY BASED DASHBOARD METHOD FOR IMPROVING SAFETY
International Nuclear Information System (INIS)
PREVETTE, S.S.
2005-01-01
The FluorBoard is a statistically based dashboard method for improving safety. Fluor Hanford has achieved significant safety improvements--including more than a 80% reduction in OSHA cases per 200,000 hours, during its work at the US Department of Energy's Hanford Site in Washington state. The massive project on the former nuclear materials production site is considered one of the largest environmental cleanup projects in the world. Fluor Hanford's safety improvements were achieved by a committed partnering of workers, managers, and statistical methodology. Safety achievements at the site have been due to a systematic approach to safety. This includes excellent cooperation between the field workers, the safety professionals, and management through OSHA Voluntary Protection Program principles. Fluor corporate values are centered around safety, and safety excellence is important for every manager in every project. In addition, Fluor Hanford has utilized a rigorous approach to using its safety statistics, based upon Dr. Shewhart's control charts, and Dr. Deming's management and quality methods
A new quantum statistical evaluation method for time correlation functions
International Nuclear Information System (INIS)
Loss, D.; Schoeller, H.
1989-01-01
Considering a system of N identical interacting particles, which obey Fermi-Dirac or Bose-Einstein statistics, the authors derive new formulas for correlation functions of the type C(t) = i= 1 N A i (t) Σ j=1 N B j > (where B j is diagonal in the free-particle states) in the thermodynamic limit. Thereby they apply and extend a superoperator formalism, recently developed for the derivation of long-time tails in semiclassical systems. As an illustrative application, the Boltzmann equation value of the time-integrated correlation function C(t) is derived in a straight-forward manner. Due to exchange effects, the obtained t-matrix and the resulting scattering cross section, which occurs in the Boltzmann collision operator, are now functionals of the Fermi-Dirac or Bose-Einstein distribution
A numerical method for resonance integral calculations
International Nuclear Information System (INIS)
Tanbay, Tayfun; Ozgener, Bilge
2013-01-01
A numerical method has been proposed for resonance integral calculations and a cubic fit based on least squares approximation to compute the optimum Bell factor is given. The numerical method is based on the discretization of the neutron slowing down equation. The scattering integral is approximated by taking into account the location of the upper limit in energy domain. The accuracy of the method has been tested by performing computations of resonance integrals for uranium dioxide isolated rods and comparing the results with empirical values. (orig.)
Statistical physics and computational methods for evolutionary game theory
Javarone, Marco Alberto
2018-01-01
This book presents an introduction to Evolutionary Game Theory (EGT) which is an emerging field in the area of complex systems attracting the attention of researchers from disparate scientific communities. EGT allows one to represent and study several complex phenomena, such as the emergence of cooperation in social systems, the role of conformity in shaping the equilibrium of a population, and the dynamics in biological and ecological systems. Since EGT models belong to the area of complex systems, statistical physics constitutes a fundamental ingredient for investigating their behavior. At the same time, the complexity of some EGT models, such as those realized by means of agent-based methods, often require the implementation of numerical simulations. Therefore, beyond providing an introduction to EGT, this book gives a brief overview of the main statistical physics tools (such as phase transitions and the Ising model) and computational strategies for simulating evolutionary games (such as Monte Carlo algor...
Huffman and linear scanning methods with statistical language models.
Roark, Brian; Fried-Oken, Melanie; Gibbons, Chris
2015-03-01
Current scanning access methods for text generation in AAC devices are limited to relatively few options, most notably row/column variations within a matrix. We present Huffman scanning, a new method for applying statistical language models to binary-switch, static-grid typing AAC interfaces, and compare it to other scanning options under a variety of conditions. We present results for 16 adults without disabilities and one 36-year-old man with locked-in syndrome who presents with complex communication needs and uses AAC scanning devices for writing. Huffman scanning with a statistical language model yielded significant typing speedups for the 16 participants without disabilities versus any of the other methods tested, including two row/column scanning methods. A similar pattern of results was found with the individual with locked-in syndrome. Interestingly, faster typing speeds were obtained with Huffman scanning using a more leisurely scan rate than relatively fast individually calibrated scan rates. Overall, the results reported here demonstrate great promise for the usability of Huffman scanning as a faster alternative to row/column scanning.
Statistical Method to Overcome Overfitting Issue in Rational Function Models
Alizadeh Moghaddam, S. H.; Mokhtarzade, M.; Alizadeh Naeini, A.; Alizadeh Moghaddam, S. A.
2017-09-01
Rational function models (RFMs) are known as one of the most appealing models which are extensively applied in geometric correction of satellite images and map production. Overfitting is a common issue, in the case of terrain dependent RFMs, that degrades the accuracy of RFMs-derived geospatial products. This issue, resulting from the high number of RFMs' parameters, leads to ill-posedness of the RFMs. To tackle this problem, in this study, a fast and robust statistical approach is proposed and compared to Tikhonov regularization (TR) method, as a frequently-used solution to RFMs' overfitting. In the proposed method, a statistical test, namely, significance test is applied to search for the RFMs' parameters that are resistant against overfitting issue. The performance of the proposed method was evaluated for two real data sets of Cartosat-1 satellite images. The obtained results demonstrate the efficiency of the proposed method in term of the achievable level of accuracy. This technique, indeed, shows an improvement of 50-80% over the TR.
Radiological decontamination, survey, and statistical release method for vehicles
International Nuclear Information System (INIS)
Goodwill, M.E.; Lively, J.W.; Morris, R.L.
1996-06-01
Earth-moving vehicles (e.g., dump trucks, belly dumps) commonly haul radiologically contaminated materials from a site being remediated to a disposal site. Traditionally, each vehicle must be surveyed before being released. The logistical difficulties of implementing the traditional approach on a large scale demand that an alternative be devised. A statistical method for assessing product quality from a continuous process was adapted to the vehicle decontamination process. This method produced a sampling scheme that automatically compensates and accommodates fluctuating batch sizes and changing conditions without the need to modify or rectify the sampling scheme in the field. Vehicles are randomly selected (sampled) upon completion of the decontamination process to be surveyed for residual radioactive surface contamination. The frequency of sampling is based on the expected number of vehicles passing through the decontamination process in a given period and the confidence level desired. This process has been successfully used for 1 year at the former uranium millsite in Monticello, Utah (a cleanup site regulated under the Comprehensive Environmental Response, Compensation, and Liability Act). The method forces improvement in the quality of the decontamination process and results in a lower likelihood that vehicles exceeding the surface contamination standards are offered for survey. Implementation of this statistical sampling method on Monticello projects has resulted in more efficient processing of vehicles through decontamination and radiological release, saved hundreds of hours of processing time, provided a high level of confidence that release limits are met, and improved the radiological cleanliness of vehicles leaving the controlled site
Hayslett, H T
1991-01-01
Statistics covers the basic principles of Statistics. The book starts by tackling the importance and the two kinds of statistics; the presentation of sample data; the definition, illustration and explanation of several measures of location; and the measures of variation. The text then discusses elementary probability, the normal distribution and the normal approximation to the binomial. Testing of statistical hypotheses and tests of hypotheses about the theoretical proportion of successes in a binomial population and about the theoretical mean of a normal population are explained. The text the
Efficient orbit integration by manifold correction methods.
Fukushima, Toshio
2005-12-01
Triggered by a desire to investigate, numerically, the planetary precession through a long-term numerical integration of the solar system, we developed a new formulation of numerical integration of orbital motion named manifold correct on methods. The main trick is to rigorously retain the consistency of physical relations, such as the orbital energy, the orbital angular momentum, or the Laplace integral, of a binary subsystem. This maintenance is done by applying a correction to the integrated variables at each integration step. Typical methods of correction are certain geometric transformations, such as spatial scaling and spatial rotation, which are commonly used in the comparison of reference frames, or mathematically reasonable operations, such as modularization of angle variables into the standard domain [-pi, pi). The form of the manifold correction methods finally evolved are the orbital longitude methods, which enable us to conduct an extremely precise integration of orbital motions. In unperturbed orbits, the integration errors are suppressed at the machine epsilon level for an indefinitely long period. In perturbed cases, on the other hand, the errors initially grow in proportion to the square root of time and then increase more rapidly, the onset of which depends on the type and magnitude of the perturbations. This feature is also realized for highly eccentric orbits by applying the same idea as used in KS-regularization. In particular, the introduction of time elements greatly enhances the performance of numerical integration of KS-regularized orbits, whether the scaling is applied or not.
Directory of Open Access Journals (Sweden)
Abul Kalam Azad
2014-05-01
Full Text Available The best Weibull distribution methods for the assessment of wind energy potential at different altitudes in desired locations are statistically diagnosed in this study. Seven different methods, namely graphical method (GM, method of moments (MOM, standard deviation method (STDM, maximum likelihood method (MLM, power density method (PDM, modified maximum likelihood method (MMLM and equivalent energy method (EEM were used to estimate the Weibull parameters and six statistical tools, namely relative percentage of error, root mean square error (RMSE, mean percentage of error, mean absolute percentage of error, chi-square error and analysis of variance were used to precisely rank the methods. The statistical fittings of the measured and calculated wind speed data are assessed for justifying the performance of the methods. The capacity factor and total energy generated by a small model wind turbine is calculated by numerical integration using Trapezoidal sums and Simpson’s rules. The results show that MOM and MLM are the most efficient methods for determining the value of k and c to fit Weibull distribution curves.
Yucel, Abdulkadir C.
2015-05-05
An efficient method for statistically characterizing multiconductor transmission line (MTL) networks subject to a large number of manufacturing uncertainties is presented. The proposed method achieves its efficiency by leveraging a high-dimensional model representation (HDMR) technique that approximates observables (quantities of interest in MTL networks, such as voltages/currents on mission-critical circuits) in terms of iteratively constructed component functions of only the most significant random variables (parameters that characterize the uncertainties in MTL networks, such as conductor locations and widths, and lumped element values). The efficiency of the proposed scheme is further increased using a multielement probabilistic collocation (ME-PC) method to compute the component functions of the HDMR. The ME-PC method makes use of generalized polynomial chaos (gPC) expansions to approximate the component functions, where the expansion coefficients are expressed in terms of integrals of the observable over the random domain. These integrals are numerically evaluated and the observable values at the quadrature/collocation points are computed using a fast deterministic simulator. The proposed method is capable of producing accurate statistical information pertinent to an observable that is rapidly varying across a high-dimensional random domain at a computational cost that is significantly lower than that of gPC or Monte Carlo methods. The applicability, efficiency, and accuracy of the method are demonstrated via statistical characterization of frequency-domain voltages in parallel wire, interconnect, and antenna corporate feed networks.
Mathematical and statistical methods for actuarial sciences and finance
Sibillo, Marilena
2014-01-01
The interaction between mathematicians and statisticians working in the actuarial and financial fields is producing numerous meaningful scientific results. This volume, comprising a series of four-page papers, gathers new ideas relating to mathematical and statistical methods in the actuarial sciences and finance. The book covers a variety of topics of interest from both theoretical and applied perspectives, including: actuarial models; alternative testing approaches; behavioral finance; clustering techniques; coherent and non-coherent risk measures; credit-scoring approaches; data envelopment analysis; dynamic stochastic programming; financial contagion models; financial ratios; intelligent financial trading systems; mixture normality approaches; Monte Carlo-based methodologies; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; r...
Evolutionary Computation Methods and their applications in Statistics
Directory of Open Access Journals (Sweden)
Francesco Battaglia
2013-05-01
Full Text Available A brief discussion of the genesis of evolutionary computation methods, their relationship to artificial intelligence, and the contribution of genetics and Darwin’s theory of natural evolution is provided. Then, the main evolutionary computation methods are illustrated: evolution strategies, genetic algorithms, estimation of distribution algorithms, differential evolution, and a brief description of some evolutionary behavior methods such as ant colony and particle swarm optimization. We also discuss the role of the genetic algorithm for multivariate probability distribution random generation, rather than as a function optimizer. Finally, some relevant applications of genetic algorithm to statistical problems are reviewed: selection of variables in regression, time series model building, outlier identification, cluster analysis, design of experiments.
Classification of Specialized Farms Applying Multivariate Statistical Methods
Directory of Open Access Journals (Sweden)
Zuzana Hloušková
2017-01-01
Full Text Available Classification of specialized farms applying multivariate statistical methods The paper is aimed at application of advanced multivariate statistical methods when classifying cattle breeding farming enterprises by their economic size. Advantage of the model is its ability to use a few selected indicators compared to the complex methodology of current classification model that requires knowledge of detailed structure of the herd turnover and structure of cultivated crops. Output of the paper is intended to be applied within farm structure research focused on future development of Czech agriculture. As data source, the farming enterprises database for 2014 has been used, from the FADN CZ system. The predictive model proposed exploits knowledge of actual size classes of the farms tested. Outcomes of the linear discriminatory analysis multifactor classification method have supported the chance of filing farming enterprises in the group of Small farms (98 % filed correctly, and the Large and Very Large enterprises (100 % filed correctly. The Medium Size farms have been correctly filed at 58.11 % only. Partial shortages of the process presented have been found when discriminating Medium and Small farms.
Application of mathematical statistics methods to study fluorite deposits
International Nuclear Information System (INIS)
Chermeninov, V.B.
1980-01-01
Considered are the applicability of mathematical-statistical methods for the increase of reliability of sampling and geological tasks (study of regularities of ore formation). Compared is the reliability of core sampling (regarding the selective abrasion of fluorite) and neutron activation logging for fluorine. The core sampling data are characterized by higher dispersion than neutron activation logging results (mean value of variation coefficients are 75% and 56% respectively). However the hypothesis of the equality of average two sampling is confirmed; this fact testifies to the absence of considerable variability of ore bodies
Algebraic methods in statistical mechanics and quantum field theory
Emch, Dr Gérard G
2009-01-01
This systematic algebraic approach concerns problems involving a large number of degrees of freedom. It extends the traditional formalism of quantum mechanics, and it eliminates conceptual and mathematical difficulties common to the development of statistical mechanics and quantum field theory. Further, the approach is linked to research in applied and pure mathematics, offering a reflection of the interplay between formulation of physical motivations and self-contained descriptions of the mathematical methods.The four-part treatment begins with a survey of algebraic approaches to certain phys
Statistical methods for determining the effect of mammography screening
DEFF Research Database (Denmark)
Lophaven, Søren
2016-01-01
In an overview of five randomised controlled trials from Sweden, a reduction of 29% was found in breast cancer mortality in women aged 50-69 at randomisation after a follow up of 5-13 years. Organised, population based, mammography service screening was introduced on the basis of these resultsin...... in 2007-2008. Women aged 50-69 were invited to screening every second year. Taking advantage of the registers of population and health, we present statistical methods for evaluating the effect of mammography screening on breast cancer mortality (Olsen et al. 2005, Njor et al. 2015 and Weedon-Fekjær etal...
A method for statistical steady state thermal analysis of reactor cores
International Nuclear Information System (INIS)
Whetton, P.A.
1981-01-01
In a previous publication the author presented a method for undertaking statistical steady state thermal analyses of reactor cores. The present paper extends the technique to an assessment of confidence limits for the resulting probability functions which define the probability that a given thermal response value will be exceeded in a reactor core. Establishing such confidence limits is considered an integral part of any statistical thermal analysis and essential if such analysis are to be considered in any regulatory process. In certain applications the use of a best estimate probability function may be justifiable but it is recognised that a demonstrably conservative probability function is required for any regulatory considerations. (orig.)
Oliveira, Sérgio C.; Zêzere, José L.; Lajas, Sara; Melo, Raquel
2017-07-01
Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km2) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.
A method for statistically comparing spatial distribution maps
Directory of Open Access Journals (Sweden)
Reynolds Mary G
2009-01-01
Full Text Available Abstract Background Ecological niche modeling is a method for estimation of species distributions based on certain ecological parameters. Thus far, empirical determination of significant differences between independently generated distribution maps for a single species (maps which are created through equivalent processes, but with different ecological input parameters, has been challenging. Results We describe a method for comparing model outcomes, which allows a statistical evaluation of whether the strength of prediction and breadth of predicted areas is measurably different between projected distributions. To create ecological niche models for statistical comparison, we utilized GARP (Genetic Algorithm for Rule-Set Production software to generate ecological niche models of human monkeypox in Africa. We created several models, keeping constant the case location input records for each model but varying the ecological input data. In order to assess the relative importance of each ecological parameter included in the development of the individual predicted distributions, we performed pixel-to-pixel comparisons between model outcomes and calculated the mean difference in pixel scores. We used a two sample Student's t-test, (assuming as null hypothesis that both maps were identical to each other regardless of which input parameters were used to examine whether the mean difference in corresponding pixel scores from one map to another was greater than would be expected by chance alone. We also utilized weighted kappa statistics, frequency distributions, and percent difference to look at the disparities in pixel scores. Multiple independent statistical tests indicated precipitation as the single most important independent ecological parameter in the niche model for human monkeypox disease. Conclusion In addition to improving our understanding of the natural factors influencing the distribution of human monkeypox disease, such pixel-to-pixel comparison
Statistical methods in the mechanical design of fuel assemblies
Energy Technology Data Exchange (ETDEWEB)
Radsak, C.; Streit, D.; Muench, C.J. [AREVA NP GmbH, Erlangen (Germany)
2013-07-01
The mechanical design of a fuel assembly is still being mainly performed in a de terministic way. This conservative approach is however not suitable to provide a realistic quantification of the design margins with respect to licensing criter ia for more and more demanding operating conditions (power upgrades, burnup increase,..). This quantification can be provided by statistical methods utilizing all available information (e.g. from manufacturing, experience feedback etc.) of the topic under consideration. During optimization e.g. of the holddown system certain objectives in the mechanical design of a fuel assembly (FA) can contradict each other, such as sufficient holddown forces enough to prevent fuel assembly lift-off and reducing the holddown forces to minimize axial loads on the fuel assembly structure to ensure no negative effect on the control rod movement.By u sing a statistical method the fuel assembly design can be optimized much better with respect to these objectives than it would be possible based on a deterministic approach. This leads to a more realistic assessment and safer way of operating fuel assemblies. Statistical models are defined on the one hand by the quanti le that has to be maintained concerning the design limit requirements (e.g. one FA quantile) and on the other hand by the confidence level which has to be met. Using the above example of the holddown force, a feasible quantile can be define d based on the requirement that less than one fuel assembly (quantile > 192/19 3 [%] = 99.5 %) in the core violates the holddown force limit w ith a confidence of 95%. (orig.)
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
A novel statistical method for classifying habitat generalists and specialists
DEFF Research Database (Denmark)
Chazdon, Robin L; Chao, Anne; Colwell, Robert K
2011-01-01
in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher......: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance...... fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest...
Statistically Consistent k-mer Methods for Phylogenetic Tree Reconstruction.
Allman, Elizabeth S; Rhodes, John A; Sullivant, Seth
2017-02-01
Frequencies of k-mers in sequences are sometimes used as a basis for inferring phylogenetic trees without first obtaining a multiple sequence alignment. We show that a standard approach of using the squared Euclidean distance between k-mer vectors to approximate a tree metric can be statistically inconsistent. To remedy this, we derive model-based distance corrections for orthologous sequences without gaps, which lead to consistent tree inference. The identifiability of model parameters from k-mer frequencies is also studied. Finally, we report simulations showing that the corrected distance outperforms many other k-mer methods, even when sequences are generated with an insertion and deletion process. These results have implications for multiple sequence alignment as well since k-mer methods are usually the first step in constructing a guide tree for such algorithms.
Response statistics of rotating shaft with non-linear elastic restoring forces by path integration
Gaidai, Oleg; Naess, Arvid; Dimentberg, Michael
2017-07-01
Extreme statistics of random vibrations is studied for a Jeffcott rotor under uniaxial white noise excitation. Restoring force is modelled as elastic non-linear; comparison is done with linearized restoring force to see the force non-linearity effect on the response statistics. While for the linear model analytical solutions and stability conditions are available, it is not generally the case for non-linear system except for some special cases. The statistics of non-linear case is studied by applying path integration (PI) method, which is based on the Markov property of the coupled dynamic system. The Jeffcott rotor response statistics can be obtained by solving the Fokker-Planck (FP) equation of the 4D dynamic system. An efficient implementation of PI algorithm is applied, namely fast Fourier transform (FFT) is used to simulate dynamic system additive noise. The latter allows significantly reduce computational time, compared to the classical PI. Excitation is modelled as Gaussian white noise, however any kind distributed white noise can be implemented with the same PI technique. Also multidirectional Markov noise can be modelled with PI in the same way as unidirectional. PI is accelerated by using Monte Carlo (MC) estimated joint probability density function (PDF) as initial input. Symmetry of dynamic system was utilized to afford higher mesh resolution. Both internal (rotating) and external damping are included in mechanical model of the rotor. The main advantage of using PI rather than MC is that PI offers high accuracy in the probability distribution tail. The latter is of critical importance for e.g. extreme value statistics, system reliability, and first passage probability.
Safety bey statistics? A critical view on statistical methods applied in health physics
International Nuclear Information System (INIS)
Kraut, W.
2016-01-01
The only proper way to describe uncertainties in health physics is by statistical means. But statistics never can replace Your personal evaluation of effect, nor can statistics transmute randomness into certainty like an ''uncertainty laundry''. The paper discusses these problems in routine practical work.
A Statistic-Based Calibration Method for TIADC System
Directory of Open Access Journals (Sweden)
Kuojun Yang
2015-01-01
Full Text Available Time-interleaved technique is widely used to increase the sampling rate of analog-to-digital converter (ADC. However, the channel mismatches degrade the performance of time-interleaved ADC (TIADC. Therefore, a statistic-based calibration method for TIADC is proposed in this paper. The average value of sampling points is utilized to calculate offset error, and the summation of sampling points is used to calculate gain error. After offset and gain error are obtained, they are calibrated by offset and gain adjustment elements in ADC. Timing skew is calibrated by an iterative method. The product of sampling points of two adjacent subchannels is used as a metric for calibration. The proposed method is employed to calibrate mismatches in a four-channel 5 GS/s TIADC system. Simulation results show that the proposed method can estimate mismatches accurately in a wide frequency range. It is also proved that an accurate estimation can be obtained even if the signal noise ratio (SNR of input signal is 20 dB. Furthermore, the results obtained from a real four-channel 5 GS/s TIADC system demonstrate the effectiveness of the proposed method. We can see that the spectra spurs due to mismatches have been effectively eliminated after calibration.
International Nuclear Information System (INIS)
Romero, Vicente J.; Burkardt, John V.; Gunzburger, Max D.; Peterson, Janet S.
2006-01-01
A recently developed centroidal Voronoi tessellation (CVT) sampling method is investigated here to assess its suitability for use in statistical sampling applications. CVT efficiently generates a highly uniform distribution of sample points over arbitrarily shaped M-dimensional parameter spaces. On several 2-D test problems CVT has recently been found to provide exceedingly effective and efficient point distributions for response surface generation. Additionally, for statistical function integration and estimation of response statistics associated with uniformly distributed random-variable inputs (uncorrelated), CVT has been found in initial investigations to provide superior points sets when compared against latin-hypercube and simple-random Monte Carlo methods and Halton and Hammersley quasi-random sequence methods. In this paper, the performance of all these sampling methods and a new variant ('Latinized' CVT) are further compared for non-uniform input distributions. Specifically, given uncorrelated normal inputs in a 2-D test problem, statistical sampling efficiencies are compared for resolving various statistics of response: mean, variance, and exceedence probabilities
An overview of recent developments in genomics and associated statistical methods.
Bickel, Peter J; Brown, James B; Huang, Haiyan; Li, Qunhua
2009-11-13
The landscape of genomics has changed drastically in the last two decades. Increasingly inexpensive sequencing has shifted the primary focus from the acquisition of biological sequences to the study of biological function. Assays have been developed to study many intricacies of biological systems, and publicly available databases have given rise to integrative analyses that combine information from many sources to draw complex conclusions. Such research was the focus of the recent workshop at the Isaac Newton Institute, 'High dimensional statistics in biology'. Many computational methods from modern genomics and related disciplines were presented and discussed. Using, as much as possible, the material from these talks, we give an overview of modern genomics: from the essential assays that make data-generation possible, to the statistical methods that yield meaningful inference. We point to current analytical challenges, where novel methods, or novel applications of extant methods, are presently needed.
Integrated Data Collection Analysis (IDCA) Program - Statistical Analysis of RDX Standard Data Sets
Energy Technology Data Exchange (ETDEWEB)
Sandstrom, Mary M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Brown, Geoffrey W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Preston, Daniel N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Pollard, Colin J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Warner, Kirstin F. [Naval Surface Warfare Center (NSWC), Indian Head, MD (United States). Indian Head Division; Sorensen, Daniel N. [Naval Surface Warfare Center (NSWC), Indian Head, MD (United States). Indian Head Division; Remmers, Daniel L. [Naval Surface Warfare Center (NSWC), Indian Head, MD (United States). Indian Head Division; Phillips, Jason J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shelley, Timothy J. [Air Force Research Lab. (AFRL), Tyndall AFB, FL (United States); Reyes, Jose A. [Applied Research Associates, Tyndall AFB, FL (United States); Hsu, Peter C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Reynolds, John G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-10-30
The Integrated Data Collection Analysis (IDCA) program is conducting a Proficiency Test for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are statistical analyses of the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of the RDX Type II Class 5 standard. The material was tested as a well-characterized standard several times during the proficiency study to assess differences among participants and the range of results that may arise for well-behaved explosive materials. The analyses show that there are detectable differences among the results from IDCA participants. While these differences are statistically significant, most of them can be disregarded for comparison purposes to assess potential variability when laboratories attempt to measure identical samples using methods assumed to be nominally the same. The results presented in this report include the average sensitivity results for the IDCA participants and the ranges of values obtained. The ranges represent variation about the mean values of the tests of between 26% and 42%. The magnitude of this variation is attributed to differences in operator, method, and environment as well as the use of different instruments that are also of varying age. The results appear to be a good representation of the broader safety testing community based on the range of methods, instruments, and environments included in the IDCA Proficiency Test.
Directory of Open Access Journals (Sweden)
Jose H. Guardiola
2010-01-01
Full Text Available This paper compares the academic performance of students in three similar elementary statistics courses taught by the same instructor, but with the lab component differing among the three. One course is traditionally taught without a lab component; the second with a lab component using scenarios and an extensive use of technology, but without explicit coordination between lab and lecture; and the third using a lab component with an extensive use of technology that carefully coordinates the lab with the lecture. Extensive use of technology means, in this context, using Minitab software in the lab section, doing homework and quizzes using MyMathlab ©, and emphasizing interpretation of computer output during lectures. Initially, an online instrument based on Gardner’s multiple intelligences theory, is given to students to try to identify students’ learning styles and intelligence types as covariates. An analysis of covariance is performed in order to compare differences in achievement. In this study there is no attempt to measure difference in student performance across the different treatments. The purpose of this study is to find indications of associations among variables that support the claim that statistics labs could be associated with superior academic achievement in one of these three instructional environments. Also, this study tries to identify individual student characteristics that could be associated with superior academic performance. This study did not find evidence of any individual student characteristics that could be associated with superior achievement. The response variable was computed as percentage of correct answers for the three exams during the semester added together. The results of this study indicate a significant difference across these three different instructional methods, showing significantly higher mean scores for the response variable on students taking the lab component that was carefully coordinated with
The extraction and integration framework: a two-process account of statistical learning.
Thiessen, Erik D; Kronstein, Alexandra T; Hufnagle, Daniel G
2013-07-01
The term statistical learning in infancy research originally referred to sensitivity to transitional probabilities. Subsequent research has demonstrated that statistical learning contributes to infant development in a wide array of domains. The range of statistical learning phenomena necessitates a broader view of the processes underlying statistical learning. Learners are sensitive to a much wider range of statistical information than the conditional relations indexed by transitional probabilities, including distributional and cue-based statistics. We propose a novel framework that unifies learning about all of these kinds of statistical structure. From our perspective, learning about conditional relations outputs discrete representations (such as words). Integration across these discrete representations yields sensitivity to cues and distributional information. To achieve sensitivity to all of these kinds of statistical structure, our framework combines processes that extract segments of the input with processes that compare across these extracted items. In this framework, the items extracted from the input serve as exemplars in long-term memory. The similarity structure of those exemplars in long-term memory leads to the discovery of cues and categorical structure, which guides subsequent extraction. The extraction and integration framework provides a way to explain sensitivity to both conditional statistical structure (such as transitional probabilities) and distributional statistical structure (such as item frequency and variability), and also a framework for thinking about how these different aspects of statistical learning influence each other. 2013 APA, all rights reserved
International Nuclear Information System (INIS)
2005-01-01
For the years 2004 and 2005 the figures shown in the tables of Energy Review are partly preliminary. The annual statistics published in Energy Review are presented in more detail in a publication called Energy Statistics that comes out yearly. Energy Statistics also includes historical time-series over a longer period of time (see e.g. Energy Statistics, Statistics Finland, Helsinki 2004.) The applied energy units and conversion coefficients are shown in the back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes, precautionary stock fees and oil pollution fees
Statistical methods for mechanistic model validation: Salt Repository Project
International Nuclear Information System (INIS)
Eggett, D.L.
1988-07-01
As part of the Department of Energy's Salt Repository Program, Pacific Northwest Laboratory (PNL) is studying the emplacement of nuclear waste containers in a salt repository. One objective of the SRP program is to develop an overall waste package component model which adequately describes such phenomena as container corrosion, waste form leaching, spent fuel degradation, etc., which are possible in the salt repository environment. The form of this model will be proposed, based on scientific principles and relevant salt repository conditions with supporting data. The model will be used to predict the future characteristics of the near field environment. This involves several different submodels such as the amount of time it takes a brine solution to contact a canister in the repository, how long it takes a canister to corrode and expose its contents to the brine, the leach rate of the contents of the canister, etc. These submodels are often tested in a laboratory and should be statistically validated (in this context, validate means to demonstrate that the model adequately describes the data) before they can be incorporated into the waste package component model. This report describes statistical methods for validating these models. 13 refs., 1 fig., 3 tabs
Statistical methods of evaluating and comparing imaging techniques
International Nuclear Information System (INIS)
Freedman, L.S.
1987-01-01
Over the past 20 years several new methods of generating images of internal organs and the anatomy of the body have been developed and used to enhance the accuracy of diagnosis and treatment. These include ultrasonic scanning, radioisotope scanning, computerised X-ray tomography (CT) and magnetic resonance imaging (MRI). The new techniques have made a considerable impact on radiological practice in hospital departments, not least on the investigational process for patients suspected or known to have malignant disease. As a consequence of the increased range of imaging techniques now available, there has developed a need to evaluate and compare their usefulness. Over the past 10 years formal studies of the application of imaging technology have been conducted and many reports have appeared in the literature. These studies cover a range of clinical situations. Likewise, the methodologies employed for evaluating and comparing the techniques in question have differed widely. While not attempting an exhaustive review of the clinical studies which have been reported, this paper aims to examine the statistical designs and analyses which have been used. First a brief review of the different types of study is given. Examples of each type are then chosen to illustrate statistical issues related to their design and analysis. In the final sections it is argued that a form of classification for these different types of study might be helpful in clarifying relationships between them and bringing a perspective to the field. A classification based upon a limited analogy with clinical trials is suggested
Integral Methods in Science and Engineering
Constanda, Christian
2011-01-01
An enormous array of problems encountered by scientists and engineers are based on the design of mathematical models using many different types of ordinary differential, partial differential, integral, and integro-differential equations. Accordingly, the solutions of these equations are of great interest to practitioners and to science in general. Presenting a wealth of cutting-edge research by a diverse group of experts in the field, Integral Methods in Science and Engineering: Computational and Analytic Aspects gives a vivid picture of both the development of theoretical integral techniques
Method of manufacturing Josephson junction integrated circuits
International Nuclear Information System (INIS)
Jillie, D.W. Jr.; Smith, L.N.
1985-01-01
Josephson junction integrated circuits of the current injection type and magnetically controlled type utilize a superconductive layer that forms both Josephson junction electrode for the Josephson junction devices on the integrated circuit as well as a ground plane for the integrated circuit. Large area Josephson junctions are utilized for effecting contact to lower superconductive layers and islands are formed in superconductive layers to provide isolation between the groudplane function and the Josephson junction electrode function as well as to effect crossovers. A superconductor-barrier-superconductor trilayer patterned by local anodization is also utilized with additional layers formed thereover. Methods of manufacturing the embodiments of the invention are disclosed
Development and testing of improved statistical wind power forecasting methods.
Energy Technology Data Exchange (ETDEWEB)
Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)
2011-12-06
(with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.
Data and statistical methods for analysis of trends and patterns
International Nuclear Information System (INIS)
Atwood, C.L.; Gentillon, C.D.; Wilson, G.E.
1992-11-01
This report summarizes topics considered at a working meeting on data and statistical methods for analysis of trends and patterns in US commercial nuclear power plants. This meeting was sponsored by the Office of Analysis and Evaluation of Operational Data (AEOD) of the Nuclear Regulatory Commission (NRC). Three data sets are briefly described: Nuclear Plant Reliability Data System (NPRDS), Licensee Event Report (LER) data, and Performance Indicator data. Two types of study are emphasized: screening studies, to see if any trends or patterns appear to be present; and detailed studies, which are more concerned with checking the analysis assumptions, modeling any patterns that are present, and searching for causes. A prescription is given for a screening study, and ideas are suggested for a detailed study, when the data take of any of three forms: counts of events per time, counts of events per demand, and non-event data
International Nuclear Information System (INIS)
2001-01-01
For the year 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g. Energiatilastot 1999, Statistics Finland, Helsinki 2000, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions from the use of fossil fuels, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in 2000, Energy exports by recipient country in 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
International Nuclear Information System (INIS)
2000-01-01
For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g., Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-March 2000, Energy exports by recipient country in January-March 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
International Nuclear Information System (INIS)
1999-01-01
For the year 1998 and the year 1999, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g. Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-June 1999, Energy exports by recipient country in January-June 1999, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
Implementation of statistical analysis methods for medical physics data
International Nuclear Information System (INIS)
Teixeira, Marilia S.; Pinto, Nivia G.P.; Barroso, Regina C.; Oliveira, Luis F.
2009-01-01
The objective of biomedical research with different radiation natures is to contribute for the understanding of the basic physics and biochemistry of the biological systems, the disease diagnostic and the development of the therapeutic techniques. The main benefits are: the cure of tumors through the therapy, the anticipated detection of diseases through the diagnostic, the using as prophylactic mean for blood transfusion, etc. Therefore, for the better understanding of the biological interactions occurring after exposure to radiation, it is necessary for the optimization of therapeutic procedures and strategies for reduction of radioinduced effects. The group pf applied physics of the Physics Institute of UERJ have been working in the characterization of biological samples (human tissues, teeth, saliva, soil, plants, sediments, air, water, organic matrixes, ceramics, fossil material, among others) using X-rays diffraction and X-ray fluorescence. The application of these techniques for measurement, analysis and interpretation of the biological tissues characteristics are experimenting considerable interest in the Medical and Environmental Physics. All quantitative data analysis must be initiated with descriptive statistic calculation (means and standard deviations) in order to obtain a previous notion on what the analysis will reveal. It is well known que o high values of standard deviation found in experimental measurements of biologicals samples can be attributed to biological factors, due to the specific characteristics of each individual (age, gender, environment, alimentary habits, etc). This work has the main objective the development of a program for the use of specific statistic methods for the optimization of experimental data an analysis. The specialized programs for this analysis are proprietary, another objective of this work is the implementation of a code which is free and can be shared by the other research groups. As the program developed since the
Statistically qualified neuro-analytic failure detection method and system
Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.
2002-03-02
An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.
Improved Statistical Method For Hydrographic Climatic Records Quality Control
Gourrion, J.; Szekely, T.
2016-02-01
Climate research benefits from the continuous development of global in-situ hydrographic networks in the last decades. Apart from the increasing volume of observations available on a large range of temporal and spatial scales, a critical aspect concerns the ability to constantly improve the quality of the datasets. In the context of the Coriolis Dataset for ReAnalysis (CORA) version 4.2, a new quality control method based on a local comparison to historical extreme values ever observed is developed, implemented and validated. Temperature, salinity and potential density validity intervals are directly estimated from minimum and maximum values from an historical reference dataset, rather than from traditional mean and standard deviation estimates. Such an approach avoids strong statistical assumptions on the data distributions such as unimodality, absence of skewness and spatially homogeneous kurtosis. As a new feature, it also allows addressing simultaneously the two main objectives of a quality control strategy, i.e. maximizing the number of good detections while minimizing the number of false alarms. The reference dataset is presently built from the fusion of 1) all ARGO profiles up to early 2014, 2) 3 historical CTD datasets and 3) the Sea Mammals CTD profiles from the MEOP database. All datasets are extensively and manually quality controlled. In this communication, the latest method validation results are also presented. The method has been implemented in the latest version of the CORA dataset and will benefit to the next version of the Copernicus CMEMS dataset.
Variational method for integrating radial gradient field
Legarda-Saenz, Ricardo; Brito-Loeza, Carlos; Rivera, Mariano; Espinosa-Romero, Arturo
2014-12-01
We propose a variational method for integrating information obtained from circular fringe pattern. The proposed method is a suitable choice for objects with radial symmetry. First, we analyze the information contained in the fringe pattern captured by the experimental setup and then move to formulate the problem of recovering the wavefront using techniques from calculus of variations. The performance of the method is demonstrated by numerical experiments with both synthetic and real data.
De Spiegelaere, Ward; Malatinkova, Eva; Lynch, Lindsay; Van Nieuwerburgh, Filip; Messiaen, Peter; O'Doherty, Una; Vandekerckhove, Linos
2014-06-01
Quantification of integrated proviral HIV DNA by repetitive-sampling Alu-HIV PCR is a candidate virological tool to monitor the HIV reservoir in patients. However, the experimental procedures and data analysis of the assay are complex and hinder its widespread use. Here, we provide an improved and simplified data analysis method by adopting binomial and Poisson statistics. A modified analysis method on the basis of Poisson statistics was used to analyze the binomial data of positive and negative reactions from a 42-replicate Alu-HIV PCR by use of dilutions of an integration standard and on samples of 57 HIV-infected patients. Results were compared with the quantitative output of the previously described Alu-HIV PCR method. Poisson-based quantification of the Alu-HIV PCR was linearly correlated with the standard dilution series, indicating that absolute quantification with the Poisson method is a valid alternative for data analysis of repetitive-sampling Alu-HIV PCR data. Quantitative outputs of patient samples assessed by the Poisson method correlated with the previously described Alu-HIV PCR analysis, indicating that this method is a valid alternative for quantifying integrated HIV DNA. Poisson-based analysis of the Alu-HIV PCR data enables absolute quantification without the need of a standard dilution curve. Implementation of the CI estimation permits improved qualitative analysis of the data and provides a statistical basis for the required minimal number of technical replicates. © 2014 The American Association for Clinical Chemistry.
A new method to determine the number of experimental data using statistical modeling methods
Energy Technology Data Exchange (ETDEWEB)
Jung, Jung-Ho; Kang, Young-Jin; Lim, O-Kaung; Noh, Yoojeong [Pusan National University, Busan (Korea, Republic of)
2017-06-15
For analyzing the statistical performance of physical systems, statistical characteristics of physical parameters such as material properties need to be estimated by collecting experimental data. For accurate statistical modeling, many such experiments may be required, but data are usually quite limited owing to the cost and time constraints of experiments. In this study, a new method for determining a rea- sonable number of experimental data is proposed using an area metric, after obtaining statistical models using the information on the underlying distribution, the Sequential statistical modeling (SSM) approach, and the Kernel density estimation (KDE) approach. The area metric is used as a convergence criterion to determine the necessary and sufficient number of experimental data to be acquired. The pro- posed method is validated in simulations, using different statistical modeling methods, different true models, and different convergence criteria. An example data set with 29 data describing the fatigue strength coefficient of SAE 950X is used for demonstrating the performance of the obtained statistical models that use a pre-determined number of experimental data in predicting the probability of failure for a target fatigue life.
Assessment Methods in Statistical Education An International Perspective
Bidgood, Penelope; Jolliffe, Flavia
2010-01-01
This book is a collaboration from leading figures in statistical education and is designed primarily for academic audiences involved in teaching statistics and mathematics. The book is divided in four sections: (1) Assessment using real-world problems, (2) Assessment statistical thinking, (3) Individual assessment (4) Successful assessment strategies.
Elementary methods for statistical systems, mean field, large-n, and duality
International Nuclear Information System (INIS)
Itzykson, C.
1983-01-01
Renormalizable field theories are singled out by such precise restraints that regularization schemes must be used to break these invariances. Statistical methods can be adapted to these problems where asymptotically free models fail. This lecture surveys approximation schemes developed in the context of statistical mechanics. The confluence point of statistical mechanics and field theory is the use of discretized path integrals, where continuous space time has been replaced by a regular lattice. Dynamic variables, a Boltzman weight factor, and boundary conditions are the ingredients. Mean field approximations --field equations, Random field transform, and gauge invariant systems--are surveyed. Under Large-N limits vector models are found to simplify tremendously. The reasons why matrix models drawn from SU (n) gauge theories do not simplify are discussed. In the epilogue, random curves versus random surfaces are offered as an example where global and local symmetries are not alike
Statistical methods for quality assurance basics, measurement, control, capability, and improvement
Vardeman, Stephen B
2016-01-01
This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the...
Tuuli, Methodius G; Odibo, Anthony O
2011-08-01
The objective of this article is to discuss the rationale for common statistical tests used for the analysis and interpretation of prenatal diagnostic imaging studies. Examples from the literature are used to illustrate descriptive and inferential statistics. The uses and limitations of linear and logistic regression analyses are discussed in detail.
Verhoeven, P.S.
2009-01-01
Although Statistics is not a very popular course according to most students, a majority of students still take it, as it is mandatory at most Social Science departments. Therefore it takes special teacher’s skills to teach statistics. In order to do so it is essential for teachers to know what
Mining method selection by integrated AHP and PROMETHEE method.
Bogdanovic, Dejan; Nikolic, Djordje; Ilic, Ivana
2012-03-01
Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteria to evaluate them. Criteria are accurately chosen in order to cover the most important parameters that impact on the mining method selection, such as geological and geotechnical properties, economic parameters and geographical factors. The AHP is used to analyze the structure of the mining method selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain the final ranking and to make a sensitivity analysis by changing the weights. The results have shown that the proposed integrated method can be successfully used in solving mining engineering problems.
International Nuclear Information System (INIS)
2003-01-01
For the year 2002, part of the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot 2001, Statistics Finland, Helsinki 2002). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supply and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees on energy products
International Nuclear Information System (INIS)
2004-01-01
For the year 2003 and 2004, the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot, Statistics Finland, Helsinki 2003, ISSN 0785-3165). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-March 2004, Energy exports by recipient country in January-March 2004, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees
International Nuclear Information System (INIS)
2000-01-01
For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy also includes historical time series over a longer period (see e.g., Energiatilastot 1999, Statistics Finland, Helsinki 2000, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-June 2000, Energy exports by recipient country in January-June 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
Statistical method to compare massive parallel sequencing pipelines.
Elsensohn, M H; Leblay, N; Dimassi, S; Campan-Fournier, A; Labalme, A; Roucher-Boulez, F; Sanlaville, D; Lesca, G; Bardel, C; Roy, P
2017-03-01
Today, sequencing is frequently carried out by Massive Parallel Sequencing (MPS) that cuts drastically sequencing time and expenses. Nevertheless, Sanger sequencing remains the main validation method to confirm the presence of variants. The analysis of MPS data involves the development of several bioinformatic tools, academic or commercial. We present here a statistical method to compare MPS pipelines and test it in a comparison between an academic (BWA-GATK) and a commercial pipeline (TMAP-NextGENe®), with and without reference to a gold standard (here, Sanger sequencing), on a panel of 41 genes in 43 epileptic patients. This method used the number of variants to fit log-linear models for pairwise agreements between pipelines. To assess the heterogeneity of the margins and the odds ratios of agreement, four log-linear models were used: a full model, a homogeneous-margin model, a model with single odds ratio for all patients, and a model with single intercept. Then a log-linear mixed model was fitted considering the biological variability as a random effect. Among the 390,339 base-pairs sequenced, TMAP-NextGENe® and BWA-GATK found, on average, 2253.49 and 1857.14 variants (single nucleotide variants and indels), respectively. Against the gold standard, the pipelines had similar sensitivities (63.47% vs. 63.42%) and close but significantly different specificities (99.57% vs. 99.65%; p < 0.001). Same-trend results were obtained when only single nucleotide variants were considered (99.98% specificity and 76.81% sensitivity for both pipelines). The method allows thus pipeline comparison and selection. It is generalizable to all types of MPS data and all pipelines.
Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods
Werner, Arelia T.; Cannon, Alex J.
2016-04-01
Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e. correlation tests) and distributional properties (i.e. tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), the climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3-day peak flow and 7-day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational data sets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational data set. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7-day low-flow events, regardless of reanalysis or observational data set. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event
National Research Council Canada - National Science Library
Willsky, Alan
2004-01-01
.... Our research blends methods from several fields-statistics and probability, signal and image processing, mathematical physics, scientific computing, statistical learning theory, and differential...
Improved statistical method for temperature and salinity quality control
Gourrion, Jérôme; Szekely, Tanguy
2017-04-01
Climate research and Ocean monitoring benefit from the continuous development of global in-situ hydrographic networks in the last decades. Apart from the increasing volume of observations available on a large range of temporal and spatial scales, a critical aspect concerns the ability to constantly improve the quality of the datasets. In the context of the Coriolis Dataset for ReAnalysis (CORA) version 4.2, a new quality control method based on a local comparison to historical extreme values ever observed is developed, implemented and validated. Temperature, salinity and potential density validity intervals are directly estimated from minimum and maximum values from an historical reference dataset, rather than from traditional mean and standard deviation estimates. Such an approach avoids strong statistical assumptions on the data distributions such as unimodality, absence of skewness and spatially homogeneous kurtosis. As a new feature, it also allows addressing simultaneously the two main objectives of an automatic quality control strategy, i.e. maximizing the number of good detections while minimizing the number of false alarms. The reference dataset is presently built from the fusion of 1) all ARGO profiles up to late 2015, 2) 3 historical CTD datasets and 3) the Sea Mammals CTD profiles from the MEOP database. All datasets are extensively and manually quality controlled. In this communication, the latest method validation results are also presented. The method has already been implemented in the latest version of the delayed-time CMEMS in-situ dataset and will be deployed soon in the equivalent near-real time products.
Nonlinear structural analysis using integrated force method
Indian Academy of Sciences (India)
A new formulation termed the Integrated Force Method (IFM) was proposed by Patnaik ... nated ``Structure (nY m)'' where (nY m) are the force and displacement degrees of ..... Patnaik S N, Yadagiri S 1976 Frequency analysis of structures.
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)
An adaptive multi-element probabilistic collocation method for statistical EMC/EMI characterization
Yücel, Abdulkadir C.
2013-12-01
An adaptive multi-element probabilistic collocation (ME-PC) method for quantifying uncertainties in electromagnetic compatibility and interference phenomena involving electrically large, multi-scale, and complex platforms is presented. The method permits the efficient and accurate statistical characterization of observables (i.e., quantities of interest such as coupled voltages) that potentially vary rapidly and/or are discontinuous in the random variables (i.e., parameters that characterize uncertainty in a system\\'s geometry, configuration, or excitation). The method achieves its efficiency and accuracy by recursively and adaptively dividing the domain of the random variables into subdomains using as a guide the decay rate of relative error in a polynomial chaos expansion of the observables. While constructing local polynomial expansions on each subdomain, a fast integral-equation-based deterministic field-cable-circuit simulator is used to compute the observable values at the collocation/integration points determined by the adaptive ME-PC scheme. The adaptive ME-PC scheme requires far fewer (computationally costly) deterministic simulations than traditional polynomial chaos collocation and Monte Carlo methods for computing averages, standard deviations, and probability density functions of rapidly varying observables. The efficiency and accuracy of the method are demonstrated via its applications to the statistical characterization of voltages in shielded/unshielded microwave amplifiers and magnetic fields induced on car tire pressure sensors. © 2013 IEEE.
A statistical method for draft tube pressure pulsation analysis
International Nuclear Information System (INIS)
Doerfler, P K; Ruchonnet, N
2012-01-01
Draft tube pressure pulsation (DTPP) in Francis turbines is composed of various components originating from different physical phenomena. These components may be separated because they differ by their spatial relationships and by their propagation mechanism. The first step for such an analysis was to distinguish between so-called synchronous and asynchronous pulsations; only approximately periodic phenomena could be described in this manner. However, less regular pulsations are always present, and these become important when turbines have to operate in the far off-design range, in particular at very low load. The statistical method described here permits to separate the stochastic (random) component from the two traditional 'regular' components. It works in connection with the standard technique of model testing with several pressure signals measured in draft tube cone. The difference between the individual signals and the averaged pressure signal, together with the coherence between the individual pressure signals is used for analysis. An example reveals that a generalized, non-periodic version of the asynchronous pulsation is important at low load.
GREY STATISTICS METHOD OF TECHNOLOGY SELECTION FOR ADVANCED PUBLIC TRANSPORTATION SYSTEMS
Directory of Open Access Journals (Sweden)
Chien Hung WEI
2003-01-01
Full Text Available Taiwan is involved in intelligent transportation systems planning, and is now selecting its prior focus areas for investment and development. The high social and economic impact associated with which intelligent transportation systems technology are chosen explains the efforts of various electronics and transportation corporations for developing intelligent transportation systems technology to expand their business opportunities. However, there has been no detailed research conducted with regard to selecting technology for advanced public transportation systems in Taiwan. Thus, the present paper demonstrates a grey statistics method integrated with a scenario method for solving the problem of selecting advanced public transportation systems technology for Taiwan. A comprehensive questionnaire survey was conducted to demonstrate the effectiveness of the grey statistics method. The proposed approach indicated that contactless smart card technology is the appropriate technology for Taiwan to develop in the near future. The significance of our research results implies that the grey statistics method is an effective method for selecting advanced public transportation systems technologies. We feel our information will be beneficial to the private sector for developing an appropriate intelligent transportation systems technology strategy.
Indirect methods for wake potential integration
International Nuclear Information System (INIS)
Zagorodnov, I.
2006-05-01
The development of the modern accelerator and free-electron laser projects requires to consider wake fields of very short bunches in arbitrary three dimensional structures. To obtain the wake numerically by direct integration is difficult, since it takes a long time for the scattered fields to catch up to the bunch. On the other hand no general algorithm for indirect wake field integration is available in the literature so far. In this paper we review the know indirect methods to compute wake potentials in rotationally symmetric and cavity-like three dimensional structures. For arbitrary three dimensional geometries we introduce several new techniques and test them numerically. (Orig.)
Numerical methods for engine-airframe integration
International Nuclear Information System (INIS)
Murthy, S.N.B.; Paynter, G.C.
1986-01-01
Various papers on numerical methods for engine-airframe integration are presented. The individual topics considered include: scientific computing environment for the 1980s, overview of prediction of complex turbulent flows, numerical solutions of the compressible Navier-Stokes equations, elements of computational engine/airframe integrations, computational requirements for efficient engine installation, application of CAE and CFD techniques to complete tactical missile design, CFD applications to engine/airframe integration, and application of a second-generation low-order panel methods to powerplant installation studies. Also addressed are: three-dimensional flow analysis of turboprop inlet and nacelle configurations, application of computational methods to the design of large turbofan engine nacelles, comparison of full potential and Euler solution algorithms for aeropropulsive flow field computations, subsonic/transonic, supersonic nozzle flows and nozzle integration, subsonic/transonic prediction capabilities for nozzle/afterbody configurations, three-dimensional viscous design methodology of supersonic inlet systems for advanced technology aircraft, and a user's technology assessment
Statistical methods for decision making in mine action
DEFF Research Database (Denmark)
Larsen, Jan
The lecture discusses the basics of statistical decision making in connection with humanitarian mine action. There is special focus on: 1) requirements for mine detection; 2) design and evaluation of mine equipment; 3) performance improvement by statistical learning and information fusion; 4...
Integrating functional data to prioritize causal variants in statistical fine-mapping studies.
Directory of Open Access Journals (Sweden)
Gleb Kichaev
2014-10-01
Full Text Available Standard statistical approaches for prioritization of variants for functional testing in fine-mapping studies either use marginal association statistics or estimate posterior probabilities for variants to be causal under simplifying assumptions. Here, we present a probabilistic framework that integrates association strength with functional genomic annotation data to improve accuracy in selecting plausible causal variants for functional validation. A key feature of our approach is that it empirically estimates the contribution of each functional annotation to the trait of interest directly from summary association statistics while allowing for multiple causal variants at any risk locus. We devise efficient algorithms that estimate the parameters of our model across all risk loci to further increase performance. Using simulations starting from the 1000 Genomes data, we find that our framework consistently outperforms the current state-of-the-art fine-mapping methods, reducing the number of variants that need to be selected to capture 90% of the causal variants from an average of 13.3 to 10.4 SNPs per locus (as compared to the next-best performing strategy. Furthermore, we introduce a cost-to-benefit optimization framework for determining the number of variants to be followed up in functional assays and assess its performance using real and simulation data. We validate our findings using a large scale meta-analysis of four blood lipids traits and find that the relative probability for causality is increased for variants in exons and transcription start sites and decreased in repressed genomic regions at the risk loci of these traits. Using these highly predictive, trait-specific functional annotations, we estimate causality probabilities across all traits and variants, reducing the size of the 90% confidence set from an average of 17.5 to 13.5 variants per locus in this data.
International Nuclear Information System (INIS)
Clerc, F; Njiki-Menga, G-H; Witschger, O
2013-01-01
Most of the measurement strategies that are suggested at the international level to assess workplace exposure to nanomaterials rely on devices measuring, in real time, airborne particles concentrations (according different metrics). Since none of the instruments to measure aerosols can distinguish a particle of interest to the background aerosol, the statistical analysis of time resolved data requires special attention. So far, very few approaches have been used for statistical analysis in the literature. This ranges from simple qualitative analysis of graphs to the implementation of more complex statistical models. To date, there is still no consensus on a particular approach and the current period is always looking for an appropriate and robust method. In this context, this exploratory study investigates a statistical method to analyse time resolved data based on a Bayesian probabilistic approach. To investigate and illustrate the use of the this statistical method, particle number concentration data from a workplace study that investigated the potential for exposure via inhalation from cleanout operations by sandpapering of a reactor producing nanocomposite thin films have been used. In this workplace study, the background issue has been addressed through the near-field and far-field approaches and several size integrated and time resolved devices have been used. The analysis of the results presented here focuses only on data obtained with two handheld condensation particle counters. While one was measuring at the source of the released particles, the other one was measuring in parallel far-field. The Bayesian probabilistic approach allows a probabilistic modelling of data series, and the observed task is modelled in the form of probability distributions. The probability distributions issuing from time resolved data obtained at the source can be compared with the probability distributions issuing from the time resolved data obtained far-field, leading in a
Statistics a guide to the use of statistical methods in the physical sciences
Barlow, Roger J
1989-01-01
The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition F. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars Second Edition A.C. Phillips Computing for Scienti
On the estimation of multiple random integrals and U-statistics
Major, Péter
2013-01-01
This work starts with the study of those limit theorems in probability theory for which classical methods do not work. In many cases some form of linearization can help to solve the problem, because the linearized version is simpler. But in order to apply such a method we have to show that the linearization causes a negligible error. The estimation of this error leads to some important large deviation type problems, and the main subject of this work is their investigation. We provide sharp estimates of the tail distribution of multiple integrals with respect to a normalized empirical measure and so-called degenerate U-statistics and also of the supremum of appropriate classes of such quantities. The proofs apply a number of useful techniques of modern probability that enable us to investigate the non-linear functionals of independent random variables. This lecture note yields insights into these methods, and may also be useful for those who only want some new tools to help them prove limit theorems when stand...
Refining developmental coordination disorder subtyping with multivariate statistical methods
Directory of Open Access Journals (Sweden)
Lalanne Christophe
2012-07-01
Full Text Available Abstract Background With a large number of potentially relevant clinical indicators penalization and ensemble learning methods are thought to provide better predictive performance than usual linear predictors. However, little is known about how they perform in clinical studies where few cases are available. We used Random Forests and Partial Least Squares Discriminant Analysis to select the most salient impairments in Developmental Coordination Disorder (DCD and assess patients similarity. Methods We considered a wide-range testing battery for various neuropsychological and visuo-motor impairments which aimed at characterizing subtypes of DCD in a sample of 63 children. Classifiers were optimized on a training sample, and they were used subsequently to rank the 49 items according to a permuted measure of variable importance. In addition, subtyping consistency was assessed with cluster analysis on the training sample. Clustering fitness and predictive accuracy were evaluated on the validation sample. Results Both classifiers yielded a relevant subset of items impairments that altogether accounted for a sharp discrimination between three DCD subtypes: ideomotor, visual-spatial and constructional, and mixt dyspraxia. The main impairments that were found to characterize the three subtypes were: digital perception, imitations of gestures, digital praxia, lego blocks, visual spatial structuration, visual motor integration, coordination between upper and lower limbs. Classification accuracy was above 90% for all classifiers, and clustering fitness was found to be satisfactory. Conclusions Random Forests and Partial Least Squares Discriminant Analysis are useful tools to extract salient features from a large pool of correlated binary predictors, but also provide a way to assess individuals proximities in a reduced factor space. Less than 15 neuro-visual, neuro-psychomotor and neuro-psychological tests might be required to provide a sensitive and
Analysis Method for Integrating Components of Product
Energy Technology Data Exchange (ETDEWEB)
Choi, Jun Ho [Inzest Co. Ltd, Seoul (Korea, Republic of); Lee, Kun Sang [Kookmin Univ., Seoul (Korea, Republic of)
2017-04-15
This paper presents some of the methods used to incorporate the parts constituting a product. A new relation function concept and its structure are introduced to analyze the relationships of component parts. This relation function has three types of information, which can be used to establish a relation function structure. The relation function structure of the analysis criteria was established to analyze and present the data. The priority components determined by the analysis criteria can be integrated. The analysis criteria were divided based on their number and orientation, as well as their direct or indirect characteristic feature. This paper presents a design algorithm for component integration. This algorithm was applied to actual products, and the components inside the product were integrated. Therefore, the proposed algorithm was used to conduct research to improve the brake discs for bicycles. As a result, an improved product similar to the related function structure was actually created.
Analysis Method for Integrating Components of Product
International Nuclear Information System (INIS)
Choi, Jun Ho; Lee, Kun Sang
2017-01-01
This paper presents some of the methods used to incorporate the parts constituting a product. A new relation function concept and its structure are introduced to analyze the relationships of component parts. This relation function has three types of information, which can be used to establish a relation function structure. The relation function structure of the analysis criteria was established to analyze and present the data. The priority components determined by the analysis criteria can be integrated. The analysis criteria were divided based on their number and orientation, as well as their direct or indirect characteristic feature. This paper presents a design algorithm for component integration. This algorithm was applied to actual products, and the components inside the product were integrated. Therefore, the proposed algorithm was used to conduct research to improve the brake discs for bicycles. As a result, an improved product similar to the related function structure was actually created.
First integral method for an oscillator system
Directory of Open Access Journals (Sweden)
Xiaoqian Gong
2013-04-01
Full Text Available In this article, we consider the nonlinear Duffing-van der Pol-type oscillator system by means of the first integral method. This system has physical relevance as a model in certain flow-induced structural vibration problems, which includes the van der Pol oscillator and the damped Duffing oscillator etc as particular cases. Firstly, we apply the Division Theorem for two variables in the complex domain, which is based on the ring theory of commutative algebra, to explore a quasi-polynomial first integral to an equivalent autonomous system. Then, through solving an algebraic system we derive the first integral of the Duffing-van der Pol-type oscillator system under certain parametric condition.
Robust Control Methods for On-Line Statistical Learning
Directory of Open Access Journals (Sweden)
Capobianco Enrico
2001-01-01
Full Text Available The issue of controlling that data processing in an experiment results not affected by the presence of outliers is relevant for statistical control and learning studies. Learning schemes should thus be tested for their capacity of handling outliers in the observed training set so to achieve reliable estimates with respect to the crucial bias and variance aspects. We describe possible ways of endowing neural networks with statistically robust properties by defining feasible error criteria. It is convenient to cast neural nets in state space representations and apply both Kalman filter and stochastic approximation procedures in order to suggest statistically robustified solutions for on-line learning.
Statistics and scientific method: an introduction for students and researchers
National Research Council Canada - National Science Library
Diggle, Peter; Chetwynd, Amanda
2011-01-01
"Most introductory statistics text-books are written either in a highly mathematical style for an intended readership of mathematics undergraduate students, or in a recipe-book style for an intended...
Using Statistical Process Control Methods to Classify Pilot Mental Workloads
National Research Council Canada - National Science Library
Kudo, Terence
2001-01-01
.... These include cardiac, ocular, respiratory, and brain activity measures. The focus of this effort is to apply statistical process control methodology on different psychophysiological features in an attempt to classify pilot mental workload...
Sensory evaluation of food: statistical methods and procedures
National Research Council Canada - National Science Library
O'Mahony, Michael
1986-01-01
The aim of this book is to provide basic knowledge of the logic and computation of statistics for the sensory evaluation of food, or for other forms of sensory measurement encountered in, say, psychophysics...
Highly Robust Statistical Methods in Medical Image Analysis
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2012-01-01
Roč. 32, č. 2 (2012), s. 3-16 ISSN 0208-5216 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust statistics * classification * faces * robust image analysis * forensic science Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.208, year: 2012 http://www.ibib.waw.pl/bbe/bbefulltext/BBE_32_2_003_FT.pdf
THE INTEGRATED SHORT-TERM STATISTICAL SURVEYS: EXPERIENCE OF NBS IN MOLDOVA
Directory of Open Access Journals (Sweden)
Oleg CARA
2012-07-01
Full Text Available The users’ rising need for relevant, reliable, coherent, timely data for the early diagnosis of the economic vulnerability and of the turning points in the business cycles, especially during a financial and economic crisis, asks for a prompt answer, coordinated by statistical institutions. High quality short term statistics are of special interest for the emerging market economies, such as the Moldavian one, being extremely vulnerable when facing economic recession. Answering to the challenges of producing a coherent and adequate image of the economic activity, by using the system of indicators and definitions efficiently applied at the level of the European Union, the National Bureau of Statistics (NBS of the Republic of Moldova has launched the development process of an integrated system of short term statistics (STS based on the advanced international experience.Thus, in 2011, BNS implemented the integrated statistical survey on STS based on consistent concepts, harmonized with the EU standards. The integration of the production processes, which were previously separated, is based on a common technical infrastructure, standardized procedures and techniques for data production. The achievement of this complex survey with holistic approach has allowed the consolidation of the statistical data quality, comparable at European level and the signifi cant reduction of information burden on business units, especially of small size.The reformation of STS based on the integrated survey has been possible thanks to the consistent methodological and practical support given to NBS by the National Institute of Statistics (INS of Romania, for which we would like to thank to our Romanian colleagues.
Directory of Open Access Journals (Sweden)
Zhang Xiaohua
2003-11-01
Full Text Available Abstract In the search for genetic determinants of complex disease, two approaches to association analysis are most often employed, testing single loci or testing a small group of loci jointly via haplotypes for their relationship to disease status. It is still debatable which of these approaches is more favourable, and under what conditions. The former has the advantage of simplicity but suffers severely when alleles at the tested loci are not in linkage disequilibrium (LD with liability alleles; the latter should capture more of the signal encoded in LD, but is far from simple. The complexity of haplotype analysis could be especially troublesome for association scans over large genomic regions, which, in fact, is becoming the standard design. For these reasons, the authors have been evaluating statistical methods that bridge the gap between single-locus and haplotype-based tests. In this article, they present one such method, which uses non-parametric regression techniques embodied by Bayesian adaptive regression splines (BARS. For a set of markers falling within a common genomic region and a corresponding set of single-locus association statistics, the BARS procedure integrates these results into a single test by examining the class of smooth curves consistent with the data. The non-parametric BARS procedure generally finds no signal when no liability allele exists in the tested region (ie it achieves the specified size of the test and it is sensitive enough to pick up signals when a liability allele is present. The BARS procedure provides a robust and potentially powerful alternative to classical tests of association, diminishes the multiple testing problem inherent in those tests and can be applied to a wide range of data types, including genotype frequencies estimated from pooled samples.
Colon-Berlingeri, Migdalisel; Burrowes, Patricia A.
2011-01-01
Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the…
Multistep Methods for Integrating the Solar System
1988-07-01
Technical Report 1055 [Multistep Methods for Integrating the Solar System 0 Panayotis A. Skordos’ MIT Artificial Intelligence Laboratory DTIC S D g8...RMA ELEENT. PROECT. TASK Artific ial Inteligence Laboratory ARE1A G WORK UNIT NUMBERS 545 Technology Square Cambridge, MA 02139 IL. CONTROLLING...describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology, supported by the Advanced Research Projects
International Nuclear Information System (INIS)
Letang, Jean-Michel
1993-01-01
This PhD thesis deals with the detection of moving objects in monocular image sequences. The first section presents the inherent problems of motion analysis in real applications. We propose a method robust to perturbations frequently encountered during acquisition of outdoor scenes. It appears three main directions for investigations, all of them pointing out the importance of the temporal axis, which is a specific dimension for motion analysis. In the first part, the image sequence is considered as a set of temporal signals. The temporal multi-scale decomposition enables the characterization of various dynamical behaviors of the objects being in the scene at a given instant. A second module integrates motion information. This elementary trajectography of moving objects provides a temporal prediction map, giving a confidence level of motion presence. Interactions between both sets of data are expressed within a statistical regularization. Markov random field models supply a formal framework to convey a priori knowledge of the primitives to be evaluated. A calibration method with qualitative boxes is presented to estimate model parameters. Our approach requires only simple computations and leads to a rather fast algorithm, that we evaluate in the last section over various typical sequences. (author) [fr
Yang, Su
2005-02-01
A new descriptor for symbol recognition is proposed. 1) A histogram is constructed for every pixel to figure out the distribution of the constraints among the other pixels. 2) All the histograms are statistically integrated to form a feature vector with fixed dimension. The robustness and invariance were experimentally confirmed.
Integrating source-language context into phrase-based statistical machine translation
Haque, R.; Kumar Naskar, S.; Bosch, A.P.J. van den; Way, A.
2011-01-01
The translation features typically used in Phrase-Based Statistical Machine Translation (PB-SMT) model dependencies between the source and target phrases, but not among the phrases in the source language themselves. A swathe of research has demonstrated that integrating source context modelling
Hassan, Mahamood M.; Schwartz, Bill N.
2014-01-01
This paper discusses a student research project that is part of an advanced cost accounting class. The project emphasizes active learning, integrates cost accounting with macroeconomics and statistics by "learning by doing" using real world data. Students analyze sales data for a publicly listed company by focusing on the company's…
Ing, Alex; Schwarzbauer, Christian
2014-01-01
Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.
Statistical methods and applications from a historical perspective selected issues
Mignani, Stefania
2014-01-01
The book showcases a selection of peer-reviewed papers, the preliminary versions of which were presented at a conference held 11-13 June 2011 in Bologna and organized jointly by the Italian Statistical Society (SIS), the National Institute of Statistics (ISTAT) and the Bank of Italy. The theme of the conference was "Statistics in the 150 years of the Unification of Italy." The celebration of the anniversary of Italian unification provided the opportunity to examine and discuss the methodological aspects and applications from a historical perspective and both from a national and international point of view. The critical discussion on the issues of the past has made it possible to focus on recent advances, considering the studies of socio-economic and demographic changes in European countries.
Statistical methods to evaluate thermoluminescence ionizing radiation dosimetry data
International Nuclear Information System (INIS)
Segre, Nadia; Matoso, Erika; Fagundes, Rosane Correa
2011-01-01
Ionizing radiation levels, evaluated through the exposure of CaF 2 :Dy thermoluminescence dosimeters (TLD- 200), have been monitored at Centro Experimental Aramar (CEA), located at Ipero in Sao Paulo state, Brazil, since 1991 resulting in a large amount of measurements until 2009 (more than 2,000). The data amount associated with measurements dispersion, since every process has deviation, reinforces the utilization of statistical tools to evaluate the results, procedure also imposed by the Brazilian Standard CNEN-NN-3.01/PR- 3.01-008 which regulates the radiometric environmental monitoring. Thermoluminescence ionizing radiation dosimetry data are statistically compared in order to evaluate potential CEA's activities environmental impact. The statistical tools discussed in this work are box plots, control charts and analysis of variance. (author)
Statistical methods for quantitative mass spectrometry proteomic experiments with labeling
Directory of Open Access Journals (Sweden)
Oberg Ann L
2012-11-01
Full Text Available Abstract Mass Spectrometry utilizing labeling allows multiple specimens to be subjected to mass spectrometry simultaneously. As a result, between-experiment variability is reduced. Here we describe use of fundamental concepts of statistical experimental design in the labeling framework in order to minimize variability and avoid biases. We demonstrate how to export data in the format that is most efficient for statistical analysis. We demonstrate how to assess the need for normalization, perform normalization, and check whether it worked. We describe how to build a model explaining the observed values and test for differential protein abundance along with descriptive statistics and measures of reliability of the findings. Concepts are illustrated through the use of three case studies utilizing the iTRAQ 4-plex labeling protocol.
Statistical methods for quantitative mass spectrometry proteomic experiments with labeling.
Oberg, Ann L; Mahoney, Douglas W
2012-01-01
Mass Spectrometry utilizing labeling allows multiple specimens to be subjected to mass spectrometry simultaneously. As a result, between-experiment variability is reduced. Here we describe use of fundamental concepts of statistical experimental design in the labeling framework in order to minimize variability and avoid biases. We demonstrate how to export data in the format that is most efficient for statistical analysis. We demonstrate how to assess the need for normalization, perform normalization, and check whether it worked. We describe how to build a model explaining the observed values and test for differential protein abundance along with descriptive statistics and measures of reliability of the findings. Concepts are illustrated through the use of three case studies utilizing the iTRAQ 4-plex labeling protocol.
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.
Wegner, Franz
2016-01-01
This text presents the mathematical concepts of Grassmann variables and the method of supersymmetry to a broad audience of physicists interested in applying these tools to disordered and critical systems, as well as related topics in statistical physics. Based on many courses and seminars held by the author, one of the pioneers in this field, the reader is given a systematic and tutorial introduction to the subject matter. The algebra and analysis of Grassmann variables is presented in part I. The mathematics of these variables is applied to a random matrix model, path integrals for fermions, dimer models and the Ising model in two dimensions. Supermathematics - the use of commuting and anticommuting variables on an equal footing - is the subject of part II. The properties of supervectors and supermatrices, which contain both commuting and Grassmann components, are treated in great detail, including the derivation of integral theorems. In part III, supersymmetric physical models are considered. While supersym...
Directory of Open Access Journals (Sweden)
Christos Chalkias
2016-03-01
Full Text Available In this paper, an integration landslide susceptibility model by combining expert-based and bivariate statistical analysis (Landslide Susceptibility Index—LSI approaches is presented. Factors related with the occurrence of landslides—such as elevation, slope angle, slope aspect, lithology, land cover, Mean Annual Precipitation (MAP and Peak Ground Acceleration (PGA—were analyzed within a GIS environment. This integrated model produced a landslide susceptibility map which categorized the study area according to the probability level of landslide occurrence. The accuracy of the final map was evaluated by Receiver Operating Characteristics (ROC analysis depending on an independent (validation dataset of landslide events. The prediction ability was found to be 76% revealing that the integration of statistical analysis with human expertise can provide an acceptable landslide susceptibility assessment at regional scale.
Hayen, Andrew; Macaskill, Petra; Irwig, Les; Bossuyt, Patrick
2010-01-01
To explain which measures of accuracy and which statistical methods should be used in studies to assess the value of a new binary test as a replacement test, an add-on test, or a triage test. Selection and explanation of statistical methods, illustrated with examples. Statistical methods for
Barron, Kenneth E.; Apple, Kevin J.
2014-01-01
Coursework in statistics and research methods is a core requirement in most undergraduate psychology programs. However, is there an optimal way to structure and sequence methodology courses to facilitate student learning? For example, should statistics be required before research methods, should research methods be required before statistics, or…
Fuzzy comprehensive evaluation method of F statistics weighting in ...
African Journals Online (AJOL)
In order to rapidly identify the source of water inrush in coal mine, and provide the theoretical basis for mine water damage prevention and control, fuzzy comprehensive evaluation model was established. The F statistics of water samples was normalized as the weight of fuzzy comprehensive evaluation for determining the ...
Statistical methods for decision making in mine action
DEFF Research Database (Denmark)
Larsen, Jan
The design and evaluation of mine clearance equipment – the problem of reliability * Detection probability – tossing a coin * Requirements in mine action * Detection probability and confidence in MA * Using statistics in area reduction Improving performance by information fusion and combination...
Statistical methods of combining information: Applications to sensor data fusion
Energy Technology Data Exchange (ETDEWEB)
Burr, T.
1996-12-31
This paper reviews some statistical approaches to combining information from multiple sources. Promising new approaches will be described, and potential applications to combining not-so-different data sources such as sensor data will be discussed. Experiences with one real data set are described.
An Introduction to Modern Statistical Methods in HCI
Robertson, Judy; Kaptein, Maurits; Robertson, J; Kaptein, M
2016-01-01
This chapter explains why we think statistical methodology matters so much to the HCI community and why we should attempt to improve it. It introduces some flaws in the well-accepted methodology of Null Hypothesis Significance Testing and briefly introduces some alternatives. Throughout the book we
An introduction to modern statistical methods in HCI
Robertson, J.; Kaptein, M.C.; Robertson, J.; Kaptein, M.C.
2016-01-01
This chapter explains why we think statistical methodology matters so much to the HCI community and why we should attempt to improve it. It introduces some flaws in the well-accepted methodology of Null Hypothesis Significance Testing and briefly introduces some alternatives. Throughout the book we
Effective viscosity of dispersions approached by a statistical continuum method
Mellema, J.; Willemse, M.W.M.
1983-01-01
The problem of the determination of the effective viscosity of disperse systems (emulsions, suspensions) is considered. On the basis of the formal solution of the equations governing creeping flow in a statistically homogeneous dispersion, the effective viscosity is expressed in a series expansion
Critical Realism and Statistical Methods--A Response to Nash
Scott, David
2007-01-01
This article offers a defence of critical realism in the face of objections Nash (2005) makes to it in a recent edition of this journal. It is argued that critical and scientific realisms are closely related and that both are opposed to statistical positivism. However, the suggestion is made that scientific realism retains (from statistical…
Kalaian, Sema A.; Kasim, Rafa M.
2014-01-01
This meta-analytic study focused on the quantitative integration and synthesis of the accumulated pedagogical research in undergraduate statistics education literature. These accumulated research studies compared the academic achievement of students who had been instructed using one of the various forms of small-group learning methods to those who…
Statistical methods for data analysis in particle physics
Lista, Luca
2017-01-01
This concise set of course-based notes provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data, in particular in the field of high-energy physics (HEP). First, the book provides an introduction to probability theory and basic statistics, mainly intended as a refresher from readers’ advanced undergraduate studies, but also to help them clearly distinguish between the Frequentist and Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on both discoveries and upper limits, as many applications in HEP concern hypothesis testing, where the main goal is often to provide better and better limits so as to eventually be able to distinguish between competing hypotheses, or to rule out some of them altogether. Many worked-out examples will help newcomers to the field and graduate students alike understand the pitfalls involved in applying theoretical co...
Reactor noise analysis by statistical pattern recognition methods
International Nuclear Information System (INIS)
Howington, L.C.; Gonzalez, R.C.
1976-01-01
A multivariate statistical pattern recognition system for reactor noise analysis is presented. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, updating, and data compacting capabilities. System design emphasizes control of the false-alarm rate. Its abilities to learn normal patterns, to recognize deviations from these patterns, and to reduce the dimensionality of data with minimum error were evaluated by experiments at the Oak Ridge National Laboratory (ORNL) High-Flux Isotope Reactor. Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the pattern recognition system
Statistical methods for data analysis in particle physics
AUTHOR|(CDS)2070643
2015-01-01
This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data
METHODOLOGICAL PRINCIPLES AND METHODS OF TERMS OF TRADE STATISTICAL EVALUATION
Directory of Open Access Journals (Sweden)
N. Kovtun
2014-09-01
Full Text Available The paper studies the methodological principles and guidance of the statistical evaluation of terms of trade for the United Nations classification model – Harmonized Commodity Description and Coding System (HS. The practical implementation of the proposed three-stage model of index analysis and estimation of terms of trade for Ukraine's commodity-members for the period of 2011-2012 are realized.
Statistical modeling of an integrated boiler for coal fired thermal power plant
Directory of Open Access Journals (Sweden)
Sreepradha Chandrasekharan
2017-06-01
Full Text Available The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R2 analysis and ANOVA (Analysis of Variance. The dependability of the process variable (temperature on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM supported by DOE (design of experiments are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant. Keywords: Chemical engineering, Applied mathematics
Statistical modeling of an integrated boiler for coal fired thermal power plant.
Chandrasekharan, Sreepradha; Panda, Rames Chandra; Swaminathan, Bhuvaneswari Natrajan
2017-06-01
The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R 2 analysis and ANOVA (Analysis of Variance). The dependability of the process variable (temperature) on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM) supported by DOE (design of experiments) are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant.
Joyce, Brendan; Lee, Danny; Rubio, Alex; Ogurtsov, Aleksey; Alves, Gelio; Yu, Yi-Kuo
2018-03-15
RAId is a software package that has been actively developed for the past 10 years for computationally and visually analyzing MS/MS data. Founded on rigorous statistical methods, RAId's core program computes accurate E-values for peptides and proteins identified during database searches. Making this robust tool readily accessible for the proteomics community by developing a graphical user interface (GUI) is our main goal here. We have constructed a graphical user interface to facilitate the use of RAId on users' local machines. Written in Java, RAId_GUI not only makes easy executions of RAId but also provides tools for data/spectra visualization, MS-product analysis, molecular isotopic distribution analysis, and graphing the retrieval versus the proportion of false discoveries. The results viewer displays and allows the users to download the analyses results. Both the knowledge-integrated organismal databases and the code package (containing source code, the graphical user interface, and a user manual) are available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads/raid.html .
Continual integration method in the polaron model
International Nuclear Information System (INIS)
Kochetov, E.A.; Kuleshov, S.P.; Smondyrev, M.A.
1981-01-01
The article is devoted to the investigation of a polaron system on the base of a variational approach formulated on the language of continuum integration. The variational method generalizing the Feynman one for the case of the system pulse different from zero has been formulated. The polaron state has been investigated at zero temperature. A problem of the bound state of two polarons exchanging quanta of a scalar field as well as a problem of polaron scattering with an external field in the Born approximation have been considered. Thermodynamics of the polaron system has been investigated, namely, high-temperature expansions for mean energy and effective polaron mass have been studied [ru
Improvements of the integral transport theory method
International Nuclear Information System (INIS)
Kavenoky, A.; Lam-Hime, M.; Stankovski, Z.
1979-01-01
The integral transport theory is widely used in practical reactor design calculations however it is computer time consuming for two dimensional calculations of large media. In the first part of this report a new treatment is presented; it is based on the Galerkin method: inside each region the total flux is expanded over a three component basis. Numerical comparison shows that this method can considerably reduce the computing time. The second part of the this report is devoted to homogeneization theory: a straightforward calculation of the fundamental mode for an heterogeneous cell is presented. At first general presentation of the problem is given, then it is simplified to plane geometry and numerical results are presented
Spatial Analysis Along Networks Statistical and Computational Methods
Okabe, Atsuyuki
2012-01-01
In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Process
Statistical methods for segmentation and classification of images
DEFF Research Database (Denmark)
Rosholm, Anders
1997-01-01
The central matter of the present thesis is Bayesian statistical inference applied to classification of images. An initial review of Markov Random Fields relates to the modeling aspect of the indicated main subject. In that connection, emphasis is put on the relatively unknown sub-class of Pickard...... with a Pickard Random Field modeling of a considered (categorical) image phenomemon. An extension of the fast PRF based classification technique is presented. The modification introduces auto-correlation into the model of an involved noise process, which previously has been assumed independent. The suitability...... of the extended model is documented by tests on controlled image data containing auto-correlated noise....
Method of statistical estimation of temperature minimums in binary systems
International Nuclear Information System (INIS)
Mireev, V.A.; Safonov, V.V.
1985-01-01
On the basis of statistical processing of literature data the technique for evaluation of temperature minima on liquidus curves in binary systems with common ion chloride systems being taken as an example, is developed. The systems are formed by 48 chlorides of 45 chemical elements including alkali, alkaline earth, rare earth and transition metals as well as Cd, In, Th. It is shown that calculation error in determining minimum melting points depends on topology of the phase diagram. The comparison of calculated and experimental data for several previously nonstudied systems is given
An integrated model of statistical process control and maintenance based on the delayed monitoring
International Nuclear Information System (INIS)
Yin, Hui; Zhang, Guojun; Zhu, Haiping; Deng, Yuhao; He, Fei
2015-01-01
This paper develops an integrated model of statistical process control and maintenance decision. The proposal of delayed monitoring policy postpones the sampling process till a scheduled time and contributes to ten-scenarios of the production process, where equipment failure may occur besides quality shift. The equipment failure and the control chart alert trigger the corrective maintenance and the predictive maintenance, respectively. The occurrence probability, the cycle time and the cycle cost of each scenario are obtained by integral calculation; therefore, a mathematical model is established to minimize the expected cost by using the genetic algorithm. A Monte Carlo simulation experiment is conducted and compared with the integral calculation in order to ensure the analysis of the ten-scenario model. Another ordinary integrated model without delayed monitoring is also established as comparison. The results of a numerical example indicate satisfactory economic performance of the proposed model. Finally, a sensitivity analysis is performed to investigate the effect of model parameters. - Highlights: • We develop an integrated model of statistical process control and maintenance. • We propose delayed monitoring policy and derive an economic model with 10 scenarios. • We consider two deterioration mechanisms, quality shift and equipment failure. • The delayed monitoring policy will help reduce the expected cost
Collaborative teaching of an integrated methods course
Directory of Open Access Journals (Sweden)
George Zhou
2011-03-01
Full Text Available With an increasing diversity in American schools, teachers need to be able to collaborate in teaching. University courses are widely considered as a stage to demonstrate or model the ways of collaboration. To respond to this call, three authors team taught an integrated methods course at an urban public university in the city of New York. Following a qualitative research design, this study explored both instructors‟ and pre-service teachers‟ experiences with this course. Study findings indicate that collaborative teaching of an integrated methods course is feasible and beneficial to both instructors and pre-service teachers. For instructors, this collaborative teaching was a reciprocal learning process where they were engaged in thinking about teaching in a broader and innovative way. For pre-service teachers, this collaborative course not only helped them understand how three different subjects could be related to each other, but also provided opportunities for them to actually see how collaboration could take place in teaching. Their understanding of collaborative teaching was enhanced after the course.
Han, Kyunghwa; Jung, Inkyung
2018-05-01
This review article presents an assessment of trends in statistical methods and an evaluation of their appropriateness in articles published in the Archives of Plastic Surgery (APS) from 2012 to 2017. We reviewed 388 original articles published in APS between 2012 and 2017. We categorized the articles that used statistical methods according to the type of statistical method, the number of statistical methods, and the type of statistical software used. We checked whether there were errors in the description of statistical methods and results. A total of 230 articles (59.3%) published in APS between 2012 and 2017 used one or more statistical method. Within these articles, there were 261 applications of statistical methods with continuous or ordinal outcomes, and 139 applications of statistical methods with categorical outcome. The Pearson chi-square test (17.4%) and the Mann-Whitney U test (14.4%) were the most frequently used methods. Errors in describing statistical methods and results were found in 133 of the 230 articles (57.8%). Inadequate description of P-values was the most common error (39.1%). Among the 230 articles that used statistical methods, 71.7% provided details about the statistical software programs used for the analyses. SPSS was predominantly used in the articles that presented statistical analyses. We found that the use of statistical methods in APS has increased over the last 6 years. It seems that researchers have been paying more attention to the proper use of statistics in recent years. It is expected that these positive trends will continue in APS.
Directory of Open Access Journals (Sweden)
Zaira M Alieva
2016-01-01
Full Text Available The article analyzes the application of mathematical and statistical methods in the analysis of socio-humanistic texts. The essence of mathematical and statistical methods, presents examples of their use in the study of Humanities and social phenomena. Considers the key issues faced by the expert in the application of mathematical-statistical methods in socio-humanitarian sphere, including the availability of sustainable contrasting socio-humanitarian Sciences and mathematics; the complexity of the allocation of the object that is the bearer of the problem; having the use of a probabilistic approach. The conclusion according to the results of the study.
A statistical comparison of accelerated concrete testing methods
Denny Meyer
1997-01-01
Accelerated curing results, obtained after only 24 hours, are used to predict the 28 day strength of concrete. Various accelerated curing methods are available. Two of these methods are compared in relation to the accuracy of their predictions and the stability of the relationship between their 24 hour and 28 day concrete strength. The results suggest that Warm Water accelerated curing is preferable to Hot Water accelerated curing of concrete. In addition, some other methods for improving the...
Evaluation of local corrosion life by statistical method
International Nuclear Information System (INIS)
Kato, Shunji; Kurosawa, Tatsuo; Takaku, Hiroshi; Kusanagi, Hideo; Hirano, Hideo; Kimura, Hideo; Hide, Koichiro; Kawasaki, Masayuki
1987-01-01
In this paper, for the purpose of achievement of life extension of light water reactor, we examined the evaluation of local corrosion by satistical method and its application of nuclear power plant components. There are many evaluation examples of maximum cracking depth of local corrosion by dowbly exponential distribution. This evaluation method has been established. But, it has not been established that we evaluate service lifes of construction materials by satistical method. In order to establish of service life evaluation by satistical method, we must strive to collect local corrosion dates and its analytical researchs. (author)
Chang, Lun-Ching; Lin, Hui-Min; Sibille, Etienne; Tseng, George C
2013-12-21
As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS(A): DE genes with non-zero effect sizes in all studies, (2) HS(B): DE genes with non-zero effect sizes in one or more studies and (3) HS(r): DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS(A), HS(B), and HS(r)). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author's publication website.
Statistical methods for analysing responses of wildlife to human disturbance.
Haiganoush K. Preisler; Alan A. Ager; Michael J. Wisdom
2006-01-01
1. Off-road recreation is increasing rapidly in many areas of the world, and effects on wildlife can be highly detrimental. Consequently, we have developed methods for studying wildlife responses to off-road recreation with the use of new technologies that allow frequent and accurate monitoring of human-wildlife interactions. To illustrate these methods, we studied the...
Introducing Students to the Application of Statistics and Investigative Methods in Political Science
Wells, Dominic D.; Nemire, Nathan A.
2017-01-01
This exercise introduces students to the application of statistics and its investigative methods in political science. It helps students gain a better understanding and a greater appreciation of statistics through a real world application.
Use of Mathematical Methods of Statistics for Analyzing Engine Characteristics
Directory of Open Access Journals (Sweden)
Aivaras Jasilionis
2012-11-01
Full Text Available For the development of new models, automobile manufacturers are trying to come up with optimal software for engine control in all movement modes. However, in this case, a vehicle cannot reach outstanding characteristics in none of them. This is the main reason why modifications in engine control software used for adapting the vehicle for driver’s needs are becoming more and more popular. The article presents a short analysis of development trends towards engine control software. Also, models of mathematical statistics for engine power and torque growth are created. The introduced models give an opportunity to predict the probabilities of engine power or torque growth after individual reprogramming of engine control software.
Statistical Methods and Tools for Hanford Staged Feed Tank Sampling
Energy Technology Data Exchange (ETDEWEB)
Fountain, Matthew S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Brigantic, Robert T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Peterson, Reid A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2013-10-01
This report summarizes work conducted by Pacific Northwest National Laboratory to technically evaluate the current approach to staged feed sampling of high-level waste (HLW) sludge to meet waste acceptance criteria (WAC) for transfer from tank farms to the Hanford Waste Treatment and Immobilization Plant (WTP). The current sampling and analysis approach is detailed in the document titled Initial Data Quality Objectives for WTP Feed Acceptance Criteria, 24590-WTP-RPT-MGT-11-014, Revision 0 (Arakali et al. 2011). The goal of this current work is to evaluate and provide recommendations to support a defensible, technical and statistical basis for the staged feed sampling approach that meets WAC data quality objectives (DQOs).
Directory of Open Access Journals (Sweden)
Yin Yanshu
2017-12-01
Full Text Available In this paper, a location-based multiple point statistics method is developed to model a non-stationary reservoir. The proposed method characterizes the relationship between the sedimentary pattern and the deposit location using the relative central position distance function, which alleviates the requirement that the training image and the simulated grids have the same dimension. The weights in every direction of the distance function can be changed to characterize the reservoir heterogeneity in various directions. The local integral replacements of data events, structured random path, distance tolerance and multi-grid strategy are applied to reproduce the sedimentary patterns and obtain a more realistic result. This method is compared with the traditional Snesim method using a synthesized 3-D training image of Poyang Lake and a reservoir model of Shengli Oilfield in China. The results indicate that the new method can reproduce the non-stationary characteristics better than the traditional method and is more suitable for simulation of delta-front deposits. These results show that the new method is a powerful tool for modelling a reservoir with non-stationary characteristics.
Statistical Bayesian method for reliability evaluation based on ADT data
Lu, Dawei; Wang, Lizhi; Sun, Yusheng; Wang, Xiaohong
2018-05-01
Accelerated degradation testing (ADT) is frequently conducted in the laboratory to predict the products’ reliability under normal operating conditions. Two kinds of methods, degradation path models and stochastic process models, are utilized to analyze degradation data and the latter one is the most popular method. However, some limitations like imprecise solution process and estimation result of degradation ratio still exist, which may affect the accuracy of the acceleration model and the extrapolation value. Moreover, the conducted solution of this problem, Bayesian method, lose key information when unifying the degradation data. In this paper, a new data processing and parameter inference method based on Bayesian method is proposed to handle degradation data and solve the problems above. First, Wiener process and acceleration model is chosen; Second, the initial values of degradation model and parameters of prior and posterior distribution under each level is calculated with updating and iteration of estimation values; Third, the lifetime and reliability values are estimated on the basis of the estimation parameters; Finally, a case study is provided to demonstrate the validity of the proposed method. The results illustrate that the proposed method is quite effective and accuracy in estimating the lifetime and reliability of a product.
Yu, Pei; Li, Zi-Yuan; Xu, Hong-Ya; Huang, Liang; Dietz, Barbara; Grebogi, Celso; Lai, Ying-Cheng
2016-12-01
A crucial result in quantum chaos, which has been established for a long time, is that the spectral properties of classically integrable systems generically are described by Poisson statistics, whereas those of time-reversal symmetric, classically chaotic systems coincide with those of random matrices from the Gaussian orthogonal ensemble (GOE). Does this result hold for two-dimensional Dirac material systems? To address this fundamental question, we investigate the spectral properties in a representative class of graphene billiards with shapes of classically integrable circular-sector billiards. Naively one may expect to observe Poisson statistics, which is indeed true for energies close to the band edges where the quasiparticle obeys the Schrödinger equation. However, for energies near the Dirac point, where the quasiparticles behave like massless Dirac fermions, Poisson statistics is extremely rare in the sense that it emerges only under quite strict symmetry constraints on the straight boundary parts of the sector. An arbitrarily small amount of imperfection of the boundary results in GOE statistics. This implies that, for circular-sector confinements with arbitrary angle, the spectral properties will generically be GOE. These results are corroborated by extensive numerical computation. Furthermore, we provide a physical understanding for our results.
Yu, Pei; Li, Zi-Yuan; Xu, Hong-Ya; Huang, Liang; Dietz, Barbara; Grebogi, Celso; Lai, Ying-Cheng
2016-12-01
A crucial result in quantum chaos, which has been established for a long time, is that the spectral properties of classically integrable systems generically are described by Poisson statistics, whereas those of time-reversal symmetric, classically chaotic systems coincide with those of random matrices from the Gaussian orthogonal ensemble (GOE). Does this result hold for two-dimensional Dirac material systems? To address this fundamental question, we investigate the spectral properties in a representative class of graphene billiards with shapes of classically integrable circular-sector billiards. Naively one may expect to observe Poisson statistics, which is indeed true for energies close to the band edges where the quasiparticle obeys the Schrödinger equation. However, for energies near the Dirac point, where the quasiparticles behave like massless Dirac fermions, Poisson statistics is extremely rare in the sense that it emerges only under quite strict symmetry constraints on the straight boundary parts of the sector. An arbitrarily small amount of imperfection of the boundary results in GOE statistics. This implies that, for circular-sector confinements with arbitrary angle, the spectral properties will generically be GOE. These results are corroborated by extensive numerical computation. Furthermore, we provide a physical understanding for our results.
[Flavouring estimation of quality of grape wines with use of methods of mathematical statistics].
Yakuba, Yu F; Khalaphyan, A A; Temerdashev, Z A; Bessonov, V V; Malinkin, A D
2016-01-01
The questions of forming of wine's flavour integral estimation during the tasting are discussed, the advantages and disadvantages of the procedures are declared. As investigating materials we used the natural white and red wines of Russian manufactures, which were made with the traditional technologies from Vitis Vinifera, straight hybrids, blending and experimental wines (more than 300 different samples). The aim of the research was to set the correlation between the content of wine's nonvolatile matter and wine's tasting quality rating by mathematical statistics methods. The content of organic acids, amino acids and cations in wines were considered as the main factors influencing on the flavor. Basically, they define the beverage's quality. The determination of those components in wine's samples was done by the electrophoretic method «CAPEL». Together with the analytical checking of wine's samples quality the representative group of specialists simultaneously carried out wine's tasting estimation using 100 scores system. The possibility of statistical modelling of correlation of wine's tasting estimation based on analytical data of amino acids and cations determination reasonably describing the wine's flavour was examined. The statistical modelling of correlation between the wine's tasting estimation and the content of major cations (ammonium, potassium, sodium, magnesium, calcium), free amino acids (proline, threonine, arginine) and the taking into account the level of influence on flavour and analytical valuation within fixed limits of quality accordance were done with Statistica. Adequate statistical models which are able to predict tasting estimation that is to determine the wine's quality using the content of components forming the flavour properties have been constructed. It is emphasized that along with aromatic (volatile) substances the nonvolatile matter - mineral substances and organic substances - amino acids such as proline, threonine, arginine
A simple statistical method for catch comparison studies
DEFF Research Database (Denmark)
Holst, René; Revill, Andrew
2009-01-01
For analysing catch comparison data, we propose a simple method based on Generalised Linear Mixed Models (GLMM) and use polynomial approximations to fit the proportions caught in the test codend. The method provides comparisons of fish catch at length by the two gears through a continuous curve...... with a realistic confidence band. We demonstrate the versatility of this method, on field data obtained from the first known testing in European waters of the Rhode Island (USA) 'Eliminator' trawl. These data are interesting as they include a range of species with different selective patterns. Crown Copyright (C...
A statistical comparison of accelerated concrete testing methods
Directory of Open Access Journals (Sweden)
Denny Meyer
1997-01-01
Full Text Available Accelerated curing results, obtained after only 24 hours, are used to predict the 28 day strength of concrete. Various accelerated curing methods are available. Two of these methods are compared in relation to the accuracy of their predictions and the stability of the relationship between their 24 hour and 28 day concrete strength. The results suggest that Warm Water accelerated curing is preferable to Hot Water accelerated curing of concrete. In addition, some other methods for improving the accuracy of predictions of 28 day strengths are suggested. In particular the frequency at which it is necessary to recalibrate the prediction equation is considered.
Rationalizing method of replacement intervals by using Bayesian statistics
International Nuclear Information System (INIS)
Kasai, Masao; Notoya, Junichi; Kusakari, Yoshiyuki
2007-01-01
This study represents the formulations for rationalizing the replacement intervals of equipments and/or parts taking into account the probability density functions (PDF) of the parameters of failure distribution functions (FDF) and compares the optimized intervals by our formulations with those by conventional formulations which uses only representative values of the parameters of FDF instead of using these PDFs. The failure data are generated by Monte Carlo simulations since the real failure data can not be available for us. The PDF of PDF parameters are obtained by Bayesian method and the representative values are obtained by likelihood estimation and Bayesian method. We found that the method using PDF by Bayesian method brings longer replacement intervals than one using the representative of the parameters. (author)
Comparative Analysis of Kernel Methods for Statistical Shape Learning
National Research Council Canada - National Science Library
Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen
2006-01-01
.... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...
Statistical Genetics Methods for Localizing Multiple Breast Cancer Genes
National Research Council Canada - National Science Library
Ott, Jurg
1998-01-01
.... For a number of variables measured on a trait, a method, principal components of heritability, was developed that combines these variables in such a way that the resulting linear combination has highest heritability...
Statistics in science the foundations of statistical methods in biology, physics and economics
Costantini, Domenico
1990-01-01
An inference may be defined as a passage of thought according to some method. In the theory of knowledge it is customary to distinguish deductive and non-deductive inferences. Deductive inferences are truth preserving, that is, the truth of the premises is preserved in the con clusion. As a result, the conclusion of a deductive inference is already 'contained' in the premises, although we may not know this fact until the inference is performed. Standard examples of deductive inferences are taken from logic and mathematics. Non-deductive inferences need not preserve truth, that is, 'thought may pass' from true premises to false conclusions. Such inferences can be expansive, or, ampliative in the sense that the performances of such inferences actually increases our putative knowledge. Standard non-deductive inferences do not really exist, but one may think of elementary inductive inferences in which conclusions regarding the future are drawn from knowledge of the past. Since the body of scientific knowledge i...
Parallel Jacobi EVD Methods on Integrated Circuits
Directory of Open Access Journals (Sweden)
Chi-Chia Sun
2014-01-01
Full Text Available Design strategies for parallel iterative algorithms are presented. In order to further study different tradeoff strategies in design criteria for integrated circuits, A 10 × 10 Jacobi Brent-Luk-EVD array with the simplified μ-CORDIC processor is used as an example. The experimental results show that using the μ-CORDIC processor is beneficial for the design criteria as it yields a smaller area, faster overall computation time, and less energy consumption than the regular CORDIC processor. It is worth to notice that the proposed parallel EVD method can be applied to real-time and low-power array signal processing algorithms performing beamforming or DOA estimation.
Directory of Open Access Journals (Sweden)
Stefania Stevenazzi
2017-06-01
Full Text Available Groundwater is among the most important freshwater resources. Worldwide, aquifers are experiencing an increasing threat of pollution from urbanization, industrial development, agricultural activities and mining enterprise. Thus, practical actions, strategies and solutions to protect groundwater from these anthropogenic sources are widely required. The most efficient tool, which helps supporting land use planning, while protecting groundwater from contamination, is represented by groundwater vulnerability assessment. Over the years, several methods assessing groundwater vulnerability have been developed: overlay and index methods, statistical and process-based methods. All methods are means to synthesize complex hydrogeological information into a unique document, which is a groundwater vulnerability map, useable by planners, decision and policy makers, geoscientists and the public. Although it is not possible to identify an approach which could be the best one for all situations, the final product should always be scientific defensible, meaningful and reliable. Nevertheless, various methods may produce very different results at any given site. Thus, reasons for similarities and differences need to be deeply investigated. This study demonstrates the reliability and flexibility of a spatial statistical method to assess groundwater vulnerability to contamination at a regional scale. The Lombardy Plain case study is particularly interesting for its long history of groundwater monitoring (quality and quantity, availability of hydrogeological data, and combined presence of various anthropogenic sources of contamination. Recent updates of the regional water protection plan have raised the necessity of realizing more flexible, reliable and accurate groundwater vulnerability maps. A comparison of groundwater vulnerability maps obtained through different approaches and developed in a time span of several years has demonstrated the relevance of the
Instrumental and statistical methods for the comparison of class evidence
Liszewski, Elisa Anne
Trace evidence is a major field within forensic science. Association of trace evidence samples can be problematic due to sample heterogeneity and a lack of quantitative criteria for comparing spectra or chromatograms. The aim of this study is to evaluate different types of instrumentation for their ability to discriminate among samples of various types of trace evidence. Chemometric analysis, including techniques such as Agglomerative Hierarchical Clustering, Principal Components Analysis, and Discriminant Analysis, was employed to evaluate instrumental data. First, automotive clear coats were analyzed by using microspectrophotometry to collect UV absorption data. In total, 71 samples were analyzed with classification accuracy of 91.61%. An external validation was performed, resulting in a prediction accuracy of 81.11%. Next, fiber dyes were analyzed using UV-Visible microspectrophotometry. While several physical characteristics of cotton fiber can be identified and compared, fiber color is considered to be an excellent source of variation, and thus was examined in this study. Twelve dyes were employed, some being visually indistinguishable. Several different analyses and comparisons were done, including an inter-laboratory comparison and external validations. Lastly, common plastic samples and other polymers were analyzed using pyrolysis-gas chromatography/mass spectrometry, and their pyrolysis products were then analyzed using multivariate statistics. The classification accuracy varied dependent upon the number of classes chosen, but the plastics were grouped based on composition. The polymers were used as an external validation and misclassifications occurred with chlorinated samples all being placed into the category containing PVC.
Non-Statistical Methods of Analysing of Bankruptcy Risk
Directory of Open Access Journals (Sweden)
Pisula Tomasz
2015-06-01
Full Text Available The article focuses on assessing the effectiveness of a non-statistical approach to bankruptcy modelling in enterprises operating in the logistics sector. In order to describe the issue more comprehensively, the aforementioned prediction of the possible negative results of business operations was carried out for companies functioning in the Polish region of Podkarpacie, and in Slovakia. The bankruptcy predictors selected for the assessment of companies operating in the logistics sector included 28 financial indicators characterizing these enterprises in terms of their financial standing and management effectiveness. The purpose of the study was to identify factors (models describing the bankruptcy risk in enterprises in the context of their forecasting effectiveness in a one-year and two-year time horizon. In order to assess their practical applicability the models were carefully analysed and validated. The usefulness of the models was assessed in terms of their classification properties, and the capacity to accurately identify enterprises at risk of bankruptcy and healthy companies as well as proper calibration of the models to the data from training sample sets.
Comparison of Statistical Methods for Detector Testing Programs
Energy Technology Data Exchange (ETDEWEB)
Rennie, John Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Abhold, Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-10-14
A typical goal for any detector testing program is to ascertain not only the performance of the detector systems under test, but also the confidence that systems accepted using that testing program’s acceptance criteria will exceed a minimum acceptable performance (which is usually expressed as the minimum acceptable success probability, p). A similar problem often arises in statistics, where we would like to ascertain the fraction, p, of a population of items that possess a property that may take one of two possible values. Typically, the problem is approached by drawing a fixed sample of size n, with the number of items out of n that possess the desired property, x, being termed successes. The sample mean gives an estimate of the population mean p ≈ x/n, although usually it is desirable to accompany such an estimate with a statement concerning the range within which p may fall and the confidence associated with that range. Procedures for establishing such ranges and confidence limits are described in detail by Clopper, Brown, and Agresti for two-sided symmetric confidence intervals.
Data Analysis & Statistical Methods for Command File Errors
Meshkat, Leila; Waggoner, Bruce; Bryant, Larry
2014-01-01
This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.
Statistically Efficient Methods for Pitch and DOA Estimation
DEFF Research Database (Denmark)
Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Jensen, Søren Holdt
2013-01-01
, it was recently considered to estimate the DOA and pitch jointly. In this paper, we propose two novel methods for DOA and pitch estimation. They both yield maximum-likelihood estimates in white Gaussian noise scenar- ios, where the SNR may be different across channels, as opposed to state-of-the-art methods......Traditionally, direction-of-arrival (DOA) and pitch estimation of multichannel, periodic sources have been considered as two separate problems. Separate estimation may render the task of resolving sources with similar DOA or pitch impossible, and it may decrease the estimation accuracy. Therefore...
Statistical methods for mass spectrometry-based clinical proteomics
Kakourou, A.
2018-01-01
The work presented in this thesis focuses on methods for the construction of diagnostic rules based on clinical mass spectrometry proteomic data. Mass spectrometry has become one of the key technologies for jointly measuring the expression of thousands of proteins in biological samples.
Statistical comparison of excystation methods in Cryptosporidium parvum oocysts
Czech Academy of Sciences Publication Activity Database
Pecková, R.; Stuart, P. D.; Sak, Bohumil; Květoňová, Dana; Kváč, Martin; Foitová, I.
2016-01-01
Roč. 230, OCT 30 (2016), s. 1-5 ISSN 0304-4017 R&D Projects: GA ČR(CZ) GAP505/11/1163 Institutional support: RVO:60077344 Keywords : Cryptosporidium parvum * excystation methods * in vitro cultivation * sodium hypochlorite * tlypsin Subject RIV: EG - Zoology Impact factor: 2.356, year: 2016
Application of few-body methods to statistical mechanics
International Nuclear Information System (INIS)
Bolle, D.
1981-01-01
This paper reviews some of the methods to study the thermodynamic properties of a macroscopic system in terms of the scattering processes between the constituent particles in the system. In particular, we discuss the time delay approach to the virial expansion and the use of the arrangement channel quantum mechanics formulation in kinetic theory. (orig.)
Oxygen Abundance Methods in SDSS: View from Modern Statistics ...
Indian Academy of Sciences (India)
6Occam's razor is a principle attributed to the 14th century English logician and .... knowledge of a galaxy's metallicity in order to locate it on the appropriate branch of ..... These methods try to balance the log likelihood term (lack of fit) with a.
CAPABILITY ASSESSMENT OF MEASURING EQUIPMENT USING STATISTIC METHOD
Directory of Open Access Journals (Sweden)
Pavel POLÁK
2014-10-01
Full Text Available Capability assessment of the measurement device is one of the methods of process quality control. Only in case the measurement device is capable, the capability of the measurement and consequently production process can be assessed. This paper deals with assessment of the capability of the measuring device using indices Cg and Cgk.
Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A.; van t Veld, Aart A.
2012-01-01
PURPOSE: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator
CSIR Research Space (South Africa)
Debba, Pravesh
2010-11-01
Full Text Available This paper reports on the results from ordinary least squares and ridge regression as statistical methods, and is compared to numerical optimization methods such as the stochastic method for global optimization, simulated annealing, particle swarm...
Hoffman, F. M.; Kumar, J.; Hargrove, W. W.
2013-12-01
Vegetated ecosystems typically exhibit unique phenological behavior over the course of a year, suggesting that remotely sensed land surface phenology may be useful for characterizing land cover and ecoregions. However, phenology is also strongly influenced by temperature and water stress; insect, fire, and storm disturbances; and climate change over seasonal, interannual, decadal and longer time scales. Normalized difference vegetation index (NDVI), a remotely sensed measure of greenness, provides a useful proxy for land surface phenology. We used NDVI for the conterminous United States (CONUS) derived from the Moderate Resolution Spectroradiometer (MODIS) at 250 m resolution to develop phenological signatures of emergent ecological regimes called phenoregions. By applying a unsupervised, quantitative data mining technique to NDVI measurements for every eight days over the entire MODIS record, annual maps of phenoregions were developed. This technique produces a prescribed number of prototypical phenological states to which every location belongs in any year. To reduce the impact of short-term disturbances, we derived a single map of the mode of annual phenological states for the CONUS, assigning each map cell to the state with the largest integrated NDVI in cases where multiple states tie for the highest frequency. Since the data mining technique is unsupervised, individual phenoregions are not associated with an ecologically understandable label. To add automated supervision to the process, we applied the method of Mapcurves, developed by Hargrove and Hoffman, to associate individual phenoregions with labeled polygons in expert-derived maps of biomes, land cover, and ecoregions. Utilizing spatial overlays with multiple expert-derived maps, this "label-stealing"' technique exploits the knowledge contained in a collection of maps to identify biome characteristics of our statistically derived phenoregions. Generalized land cover maps were produced by combining
Numerov iteration method for second order integral-differential equation
International Nuclear Information System (INIS)
Zeng Fanan; Zhang Jiaju; Zhao Xuan
1987-01-01
In this paper, Numerov iterative method for second order integral-differential equation and system of equations are constructed. Numerical examples show that this method is better than direct method (Gauss elimination method) in CPU time and memoy requireing. Therefore, this method is an efficient method for solving integral-differential equation in nuclear physics
An Integrated Method for Airfoil Optimization
Okrent, Joshua B.
Design exploration and optimization is a large part of the initial engineering and design process. To evaluate the aerodynamic performance of a design, viscous Navier-Stokes solvers can be used. However this method can prove to be overwhelmingly time consuming when performing an initial design sweep. Therefore, another evaluation method is needed to provide accurate results at a faster pace. To accomplish this goal, a coupled viscous-inviscid method is used. This thesis proposes an integrated method for analyzing, evaluating, and optimizing an airfoil using a coupled viscous-inviscid solver along with a genetic algorithm to find the optimal candidate. The method proposed is different from prior optimization efforts in that it greatly broadens the design space, while allowing the optimization to search for the best candidate that will meet multiple objectives over a characteristic mission profile rather than over a single condition and single optimization parameter. The increased design space is due to the use of multiple parametric airfoil families, namely the NACA 4 series, CST family, and the PARSEC family. Almost all possible airfoil shapes can be created with these three families allowing for all possible configurations to be included. This inclusion of multiple airfoil families addresses a possible criticism of prior optimization attempts since by only focusing on one airfoil family, they were inherently limiting the number of possible airfoil configurations. By using multiple parametric airfoils, it can be assumed that all reasonable airfoil configurations are included in the analysis and optimization and that a global and not local maximum is found. Additionally, the method used is amenable to customization to suit any specific needs as well as including the effects of other physical phenomena or design criteria and/or constraints. This thesis found that an airfoil configuration that met multiple objectives could be found for a given set of nominal
Statistical Analysis Methods for the fMRI Data
Directory of Open Access Journals (Sweden)
Huseyin Boyaci
2011-08-01
Full Text Available Functional magnetic resonance imaging (fMRI is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. The technique has become a ubiquitous tool in basic, clinical and cognitive neuroscience. This method can measure little metabolism changes that occur in active part of the brain. We process the fMRI data to be able to find the parts of brain that are involve in a mechanism, or to determine the changes that occur in brain activities due to a brain lesion. In this study we will have an overview over the methods that are used for the analysis of fMRI data.
Neumann, David L.; Neumann, Michelle M.; Hood, Michelle
2011-01-01
The discipline of statistics seems well suited to the integration of technology in a lecture as a means to enhance student learning and engagement. Technology can be used to simulate statistical concepts, create interactive learning exercises, and illustrate real world applications of statistics. The present study aimed to better understand the…
de Savigny, Don; Riley, Ian; Chandramohan, Daniel; Odhiambo, Frank; Nichols, Erin; Notzon, Sam; AbouZahr, Carla; Mitra, Raj; Cobos Muñoz, Daniel; Firth, Sonja; Maire, Nicolas; Sankoh, Osman; Bronson, Gay; Setel, Philip; Byass, Peter; Jakob, Robert; Boerma, Ties; Lopez, Alan D.
2017-01-01
ABSTRACT Background: Reliable and representative cause of death (COD) statistics are essential to inform public health policy, respond to emerging health needs, and document progress towards Sustainable Development Goals. However, less than one-third of deaths worldwide are assigned a cause. Civil registration and vital statistics (CRVS) systems in low- and lower-middle-income countries are failing to provide timely, complete and accurate vital statistics, and it will still be some time before they can provide physician-certified COD for every death. Proposals: Verbal autopsy (VA) is a method to ascertain the probable COD and, although imperfect, it is the best alternative in the absence of medical certification. There is extensive experience with VA in research settings but only a few examples of its use on a large scale. Data collection using electronic questionnaires on mobile devices and computer algorithms to analyse responses and estimate probable COD have increased the potential for VA to be routinely applied in CRVS systems. However, a number of CRVS and health system integration issues should be considered in planning, piloting and implementing a system-wide intervention such as VA. These include addressing the multiplicity of stakeholders and sub-systems involved, integration with existing CRVS work processes and information flows, linking VA results to civil registration records, information technology requirements and data quality assurance. Conclusions: Integrating VA within CRVS systems is not simply a technical undertaking. It will have profound system-wide effects that should be carefully considered when planning for an effective implementation. This paper identifies and discusses the major system-level issues and emerging practices, provides a planning checklist of system-level considerations and proposes an overview for how VA can be integrated into routine CRVS systems. PMID:28137194
Overview of statistical methods, models and analysis for predicting equipment end of life
Energy Technology Data Exchange (ETDEWEB)
NONE
2009-07-01
Utility equipment can be operated and maintained for many years following installation. However, as the equipment ages, utility operators must decide whether to extend the service life or replace the equipment. Condition assessment modelling is used by many utilities to determine the condition of equipment and to prioritize the maintenance or repair. Several factors are weighted and combined in assessment modelling, which gives a single index number to rate the equipment. There is speculation that this index alone may not be adequate for a business case to rework or replace an asset because it only ranks an asset into a particular category. For that reason, a new methodology was developed to determine the economic end of life of an asset. This paper described the different statistical methods available and their use in determining the remaining service life of electrical equipment. A newly developed Excel-based demonstration computer tool is also an integral part of the deliverables of this project.
Swofford, H J; Koertner, A J; Zemp, F; Ausdemore, M; Liu, A; Salyards, M J
2018-04-03
The forensic fingerprint community has faced increasing amounts of criticism by scientific and legal commentators, challenging the validity and reliability of fingerprint evidence due to the lack of an empirically demonstrable basis to evaluate and report the strength of the evidence in a given case. This paper presents a method, developed as a stand-alone software application, FRStat, which provides a statistical assessment of the strength of fingerprint evidence. The performance was evaluated using a variety of mated and non-mated datasets. The results show strong performance characteristics, often with values supporting specificity rates greater than 99%. This method provides fingerprint experts the capability to demonstrate the validity and reliability of fingerprint evidence in a given case and report the findings in a more transparent and standardized fashion with clearly defined criteria for conclusions and known error rate information thereby responding to concerns raised by the scientific and legal communities. Published by Elsevier B.V.
METHODS OF INTEGRATED OPTIMIZATION MAGLEV TRANSPORT SYSTEMS
Directory of Open Access Journals (Sweden)
A. Lasher
2013-09-01
example, this research proved the sustainability of the proposed integrated optimization parameters of transport systems. This approach could be applied not only for MTS, but also for other transport systems. Originality. The bases of the complex optimization of transport presented are the new system of universal scientific methods and approaches that ensure high accuracy and authenticity of calculations with the simulation of transport systems and transport networks taking into account the dynamics of their development. Practical value. The development of the theoretical and technological bases of conducting the complex optimization of transport makes it possible to create the scientific tool, which ensures the fulfillment of the automated simulation and calculating of technical and economic structure and technology of the work of different objects of transport, including its infrastructure.
Statistics of electron multiplication in multiplier phototube: iterative method
International Nuclear Information System (INIS)
Grau Malonda, A.; Ortiz Sanchez, J.F.
1985-01-01
An iterative method is applied to study the variation of dynode response in the multiplier phototube. Three different situations are considered that correspond to the following ways of electronic incidence on the first dynode: incidence of exactly one electron, incidence of exactly r electrons and incidence of an average anti-r electrons. The responses are given for a number of steps between 1 and 5, and for values of the multiplication factor of 2.1, 2.5, 3 and 5. We study also the variance, the skewness and the excess of jurtosis for different multiplication factors. (author)
Statistics of electron multiplication in a multiplier phototube; Iterative method
International Nuclear Information System (INIS)
Ortiz, J. F.; Grau, A.
1985-01-01
In the present paper an iterative method is applied to study the variation of dynode response in the multiplier phototube. Three different situation are considered that correspond to the following ways of electronic incidence on the first dynode: incidence of exactly one electron, incidence of exactly r electrons and incidence of an average r electrons. The responses are given for a number of steps between 1 and 5, and for values of the multiplication factor of 2.1, 2.5, 3 and 5. We study also the variance, the skewness and the excess of jurtosis for different multiplication factors. (Author) 11 refs
Statistical inference methods for two crossing survival curves: a comparison of methods.
Li, Huimin; Han, Dong; Hou, Yawen; Chen, Huilin; Chen, Zheng
2015-01-01
A common problem that is encountered in medical applications is the overall homogeneity of survival distributions when two survival curves cross each other. A survey demonstrated that under this condition, which was an obvious violation of the assumption of proportional hazard rates, the log-rank test was still used in 70% of studies. Several statistical methods have been proposed to solve this problem. However, in many applications, it is difficult to specify the types of survival differences and choose an appropriate method prior to analysis. Thus, we conducted an extensive series of Monte Carlo simulations to investigate the power and type I error rate of these procedures under various patterns of crossing survival curves with different censoring rates and distribution parameters. Our objective was to evaluate the strengths and weaknesses of tests in different situations and for various censoring rates and to recommend an appropriate test that will not fail for a wide range of applications. Simulation studies demonstrated that adaptive Neyman's smooth tests and the two-stage procedure offer higher power and greater stability than other methods when the survival distributions cross at early, middle or late times. Even for proportional hazards, both methods maintain acceptable power compared with the log-rank test. In terms of the type I error rate, Renyi and Cramér-von Mises tests are relatively conservative, whereas the statistics of the Lin-Xu test exhibit apparent inflation as the censoring rate increases. Other tests produce results close to the nominal 0.05 level. In conclusion, adaptive Neyman's smooth tests and the two-stage procedure are found to be the most stable and feasible approaches for a variety of situations and censoring rates. Therefore, they are applicable to a wider spectrum of alternatives compared with other tests.
A reductionist perspective on quantum statistical mechanics: Coarse-graining of path integrals.
Sinitskiy, Anton V; Voth, Gregory A
2015-09-07
Computational modeling of the condensed phase based on classical statistical mechanics has been rapidly developing over the last few decades and has yielded important information on various systems containing up to millions of atoms. However, if a system of interest contains important quantum effects, well-developed classical techniques cannot be used. One way of treating finite temperature quantum systems at equilibrium has been based on Feynman's imaginary time path integral approach and the ensuing quantum-classical isomorphism. This isomorphism is exact only in the limit of infinitely many classical quasiparticles representing each physical quantum particle. In this work, we present a reductionist perspective on this problem based on the emerging methodology of coarse-graining. This perspective allows for the representations of one quantum particle with only two classical-like quasiparticles and their conjugate momenta. One of these coupled quasiparticles is the centroid particle of the quantum path integral quasiparticle distribution. Only this quasiparticle feels the potential energy function. The other quasiparticle directly provides the observable averages of quantum mechanical operators. The theory offers a simplified perspective on quantum statistical mechanics, revealing its most reductionist connection to classical statistical physics. By doing so, it can facilitate a simpler representation of certain quantum effects in complex molecular environments.
A reductionist perspective on quantum statistical mechanics: Coarse-graining of path integrals
International Nuclear Information System (INIS)
Sinitskiy, Anton V.; Voth, Gregory A.
2015-01-01
Computational modeling of the condensed phase based on classical statistical mechanics has been rapidly developing over the last few decades and has yielded important information on various systems containing up to millions of atoms. However, if a system of interest contains important quantum effects, well-developed classical techniques cannot be used. One way of treating finite temperature quantum systems at equilibrium has been based on Feynman’s imaginary time path integral approach and the ensuing quantum-classical isomorphism. This isomorphism is exact only in the limit of infinitely many classical quasiparticles representing each physical quantum particle. In this work, we present a reductionist perspective on this problem based on the emerging methodology of coarse-graining. This perspective allows for the representations of one quantum particle with only two classical-like quasiparticles and their conjugate momenta. One of these coupled quasiparticles is the centroid particle of the quantum path integral quasiparticle distribution. Only this quasiparticle feels the potential energy function. The other quasiparticle directly provides the observable averages of quantum mechanical operators. The theory offers a simplified perspective on quantum statistical mechanics, revealing its most reductionist connection to classical statistical physics. By doing so, it can facilitate a simpler representation of certain quantum effects in complex molecular environments
Directory of Open Access Journals (Sweden)
Jess Hartcher-O'Brien
Full Text Available Often multisensory information is integrated in a statistically optimal fashion where each sensory source is weighted according to its precision. This integration scheme isstatistically optimal because it theoretically results in unbiased perceptual estimates with the highest precisionpossible.There is a current lack of consensus about how the nervous system processes multiple sensory cues to elapsed time.In order to shed light upon this, we adopt a computational approach to pinpoint the integration strategy underlying duration estimationof audio/visual stimuli. One of the assumptions of our computational approach is that the multisensory signals redundantly specify the same stimulus property. Our results clearly show that despite claims to the contrary, perceived duration is the result of an optimal weighting process, similar to that adopted for estimates of space. That is, participants weight the audio and visual information to arrive at the most precise, single duration estimate possible. The work also disentangles how different integration strategies - i.e. consideringthe time of onset/offset ofsignals - might alter the final estimate. As such we provide the first concrete evidence of an optimal integration strategy in human duration estimates.
Students' Attitudes toward Statistics across the Disciplines: A Mixed-Methods Approach
Griffith, James D.; Adams, Lea T.; Gu, Lucy L.; Hart, Christian L.; Nichols-Whitehead, Penney
2012-01-01
Students' attitudes toward statistics were investigated using a mixed-methods approach including a discovery-oriented qualitative methodology among 684 undergraduate students across business, criminal justice, and psychology majors where at least one course in statistics was required. Students were asked about their attitudes toward statistics and…
Chamberlain, John Martyn; Hillier, John; Signoretta, Paola
2015-01-01
This article reports the results of research concerned with students' statistical anxiety and confidence to both complete and learn to complete statistical tasks. Data were collected at the beginning and end of a quantitative method statistics module. Students recognised the value of numeracy skills but felt they were not necessarily relevant for…
Multivariate statistical methods and data mining in particle physics (4/4)
CERN. Geneva
2008-01-01
The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.
Multivariate statistical methods and data mining in particle physics (2/4)
CERN. Geneva
2008-01-01
The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.
Multivariate statistical methods and data mining in particle physics (1/4)
CERN. Geneva
2008-01-01
The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.
Lu, Qiongshi; Hu, Yiming; Sun, Jiehuan; Cheng, Yuwei; Cheung, Kei-Hoi; Zhao, Hongyu
2015-05-27
Identifying functional regions in the human genome is a major goal in human genetics. Great efforts have been made to functionally annotate the human genome either through computational predictions, such as genomic conservation, or high-throughput experiments, such as the ENCODE project. These efforts have resulted in a rich collection of functional annotation data of diverse types that need to be jointly analyzed for integrated interpretation and annotation. Here we present GenoCanyon, a whole-genome annotation method that performs unsupervised statistical learning using 22 computational and experimental annotations thereby inferring the functional potential of each position in the human genome. With GenoCanyon, we are able to predict many of the known functional regions. The ability of predicting functional regions as well as its generalizable statistical framework makes GenoCanyon a unique and powerful tool for whole-genome annotation. The GenoCanyon web server is available at http://genocanyon.med.yale.edu.
Directory of Open Access Journals (Sweden)
Yongze Song
2017-12-01
Full Text Available The integration of building information modelling (BIM and geographic information system (GIS in construction management is a new and fast developing trend in recent years, from research to industrial practice. BIM has advantages on rich geometric and semantic information through the building life cycle, while GIS is a broad field covering geovisualization-based decision making and geospatial modelling. However, most current studies of BIM-GIS integration focus on the integration techniques but lack theories and methods for further data analysis and mathematic modelling. This paper reviews the applications and discusses future trends of BIM-GIS integration in the architecture, engineering and construction (AEC industry based on the studies of 96 high-quality research articles from a spatio-temporal statistical perspective. The analysis of these applications helps reveal the evolution progress of BIM-GIS integration. Results show that the utilization of BIM-GIS integration in the AEC industry requires systematic theories beyond integration technologies and deep applications of mathematical modeling methods, including spatio-temporal statistical modeling in GIS and 4D/nD BIM simulation and management. Opportunities of BIM-GIS integration are outlined as three hypotheses in the AEC industry for future research on the in-depth integration of BIM and GIS. BIM-GIS integration hypotheses enable more comprehensive applications through the life cycle of AEC projects.
Energy demand forecasting method based on international statistical data
International Nuclear Information System (INIS)
Glanc, Z.; Kerner, A.
1997-01-01
Poland is in a transition phase from a centrally planned to a market economy; data collected under former economic conditions do not reflect a market economy. Final energy demand forecasts are based on the assumption that the economic transformation in Poland will gradually lead the Polish economy, technologies and modes of energy use, to the same conditions as mature market economy countries. The starting point has a significant influence on the future energy demand and supply structure: final energy consumption per capita in 1992 was almost half the average of OECD countries; energy intensity, based on Purchasing Power Parities (PPP) and referred to GDP, is more than 3 times higher in Poland. A method of final energy demand forecasting based on regression analysis is described in this paper. The input data are: output of macroeconomic and population growth forecast; time series 1970-1992 of OECD countries concerning both macroeconomic characteristics and energy consumption; and energy balance of Poland for the base year of the forecast horizon. (author). 1 ref., 19 figs, 4 tabs
Energy demand forecasting method based on international statistical data
Energy Technology Data Exchange (ETDEWEB)
Glanc, Z; Kerner, A [Energy Information Centre, Warsaw (Poland)
1997-09-01
Poland is in a transition phase from a centrally planned to a market economy; data collected under former economic conditions do not reflect a market economy. Final energy demand forecasts are based on the assumption that the economic transformation in Poland will gradually lead the Polish economy, technologies and modes of energy use, to the same conditions as mature market economy countries. The starting point has a significant influence on the future energy demand and supply structure: final energy consumption per capita in 1992 was almost half the average of OECD countries; energy intensity, based on Purchasing Power Parities (PPP) and referred to GDP, is more than 3 times higher in Poland. A method of final energy demand forecasting based on regression analysis is described in this paper. The input data are: output of macroeconomic and population growth forecast; time series 1970-1992 of OECD countries concerning both macroeconomic characteristics and energy consumption; and energy balance of Poland for the base year of the forecast horizon. (author). 1 ref., 19 figs, 4 tabs.
Statistical methods for the forensic analysis of striated tool marks
Energy Technology Data Exchange (ETDEWEB)
Hoeksema, Amy Beth [Iowa State Univ., Ames, IA (United States)
2013-01-01
In forensics, fingerprints can be used to uniquely identify suspects in a crime. Similarly, a tool mark left at a crime scene can be used to identify the tool that was used. However, the current practice of identifying matching tool marks involves visual inspection of marks by forensic experts which can be a very subjective process. As a result, declared matches are often successfully challenged in court, so law enforcement agencies are particularly interested in encouraging research in more objective approaches. Our analysis is based on comparisons of profilometry data, essentially depth contours of a tool mark surface taken along a linear path. In current practice, for stronger support of a match or non-match, multiple marks are made in the lab under the same conditions by the suspect tool. We propose the use of a likelihood ratio test to analyze the difference between a sample of comparisons of lab tool marks to a field tool mark, against a sample of comparisons of two lab tool marks. Chumbley et al. (2010) point out that the angle of incidence between the tool and the marked surface can have a substantial impact on the tool mark and on the effectiveness of both manual and algorithmic matching procedures. To better address this problem, we describe how the analysis can be enhanced to model the effect of tool angle and allow for angle estimation for a tool mark left at a crime scene. With sufficient development, such methods may lead to more defensible forensic analyses.
Path integral molecular dynamics for exact quantum statistics of multi-electronic-state systems.
Liu, Xinzijian; Liu, Jian
2018-03-14
An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD), Liu et al. [J. Chem. Phys. 145, 024103 (2016)] and Zhang et al. [J. Chem. Phys. 147, 034109 (2017)], for quantum statistical mechanics when a single potential energy surface is involved. We first define an effective potential function that is numerically favorable for MES-PIMD and then derive corresponding estimators in MES-PIMD for evaluating various physical properties. Its application to several representative one-dimensional and multi-dimensional models demonstrates that MES-PIMD in principle offers a practical tool in either of the diabatic and adiabatic representations for studying exact quantum statistics of complex/large MES systems when the Born-Oppenheimer approximation, Condon approximation, and harmonic bath approximation are broken.
Pavlacky, David C; Lukacs, Paul M; Blakesley, Jennifer A; Skorkowsky, Robert C; Klute, David S; Hahn, Beth A; Dreitz, Victoria J; George, T Luke; Hanni, David J
2017-01-01
Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer's sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical
Directory of Open Access Journals (Sweden)
David C Pavlacky
Full Text Available Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1 coordination across organizations and regions, 2 meaningful management and conservation objectives, and 3 rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17. We provide two examples for the Brewer's sparrow (Spizella breweri in BCR 17 demonstrating the ability of the design to 1 determine hierarchical population responses to landscape change and 2 estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous
Boundary integral methods for unsaturated flow
International Nuclear Information System (INIS)
Martinez, M.J.; McTigue, D.F.
1990-01-01
Many large simulations may be required to assess the performance of Yucca Mountain as a possible site for the nations first high level nuclear waste repository. A boundary integral equation method (BIEM) is described for numerical analysis of quasilinear steady unsaturated flow in homogeneous material. The applicability of the exponential model for the dependence of hydraulic conductivity on pressure head is discussed briefly. This constitutive assumption is at the heart of the quasilinear transformation. Materials which display a wide distribution in pore-size are described reasonably well by the exponential. For materials with a narrow range in pore-size, the exponential is suitable over more limited ranges in pressure head. The numerical implementation of the BIEM is used to investigate the infiltration from a strip source to a water table. The net infiltration of moisture into a finite-depth layer is well-described by results for a semi-infinite layer if αD > 4, where α is the sorptive number and D is the depth to the water table. the distribution of moisture exhibits a similar dependence on αD. 11 refs., 4 figs.,
Hayat, Matthew J; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L
2017-01-01
Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals.
Statistical method for resolving the photon-photoelectron-counting inversion problem
International Nuclear Information System (INIS)
Wu Jinlong; Li Tiejun; Peng, Xiang; Guo Hong
2011-01-01
A statistical inversion method is proposed for the photon-photoelectron-counting statistics in quantum key distribution experiment. With the statistical viewpoint, this problem is equivalent to the parameter estimation for an infinite binomial mixture model. The coarse-graining idea and Bayesian methods are applied to deal with this ill-posed problem, which is a good simple example to show the successful application of the statistical methods to the inverse problem. Numerical results show the applicability of the proposed strategy. The coarse-graining idea for the infinite mixture models should be general to be used in the future.
DYNAMIC STABILITY OF THE SOLAR SYSTEM: STATISTICALLY INCONCLUSIVE RESULTS FROM ENSEMBLE INTEGRATIONS
Energy Technology Data Exchange (ETDEWEB)
Zeebe, Richard E., E-mail: zeebe@soest.hawaii.edu [School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, 1000 Pope Road, MSB 629, Honolulu, HI 96822 (United States)
2015-01-01
Due to the chaotic nature of the solar system, the question of its long-term stability can only be answered in a statistical sense, for instance, based on numerical ensemble integrations of nearby orbits. Destabilization of the inner planets, leading to close encounters and/or collisions can be initiated through a large increase in Mercury's eccentricity, with a currently assumed likelihood of ∼1%. However, little is known at present about the robustness of this number. Here I report ensemble integrations of the full equations of motion of the eight planets and Pluto over 5 Gyr, including contributions from general relativity. The results show that different numerical algorithms lead to statistically different results for the evolution of Mercury's eccentricity (e{sub M}). For instance, starting at present initial conditions (e{sub M}≃0.21), Mercury's maximum eccentricity achieved over 5 Gyr is, on average, significantly higher in symplectic ensemble integrations using heliocentric rather than Jacobi coordinates and stricter error control. In contrast, starting at a possible future configuration (e{sub M}≃0.53), Mercury's maximum eccentricity achieved over the subsequent 500 Myr is, on average, significantly lower using heliocentric rather than Jacobi coordinates. For example, the probability for e{sub M} to increase beyond 0.53 over 500 Myr is >90% (Jacobi) versus only 40%-55% (heliocentric). This poses a dilemma because the physical evolution of the real system—and its probabilistic behavior—cannot depend on the coordinate system or the numerical algorithm chosen to describe it. Some tests of the numerical algorithms suggest that symplectic integrators using heliocentric coordinates underestimate the odds for destabilization of Mercury's orbit at high initial e{sub M}.
Integral Equation Methods for Electromagnetic and Elastic Waves
Chew, Weng; Hu, Bin
2008-01-01
Integral Equation Methods for Electromagnetic and Elastic Waves is an outgrowth of several years of work. There have been no recent books on integral equation methods. There are books written on integral equations, but either they have been around for a while, or they were written by mathematicians. Much of the knowledge in integral equation methods still resides in journal papers. With this book, important relevant knowledge for integral equations are consolidated in one place and researchers need only read the pertinent chapters in this book to gain important knowledge needed for integral eq
Analytic methods to generate integrable mappings
Indian Academy of Sciences (India)
essential integrability features of an integrable differential equation is a .... With this in mind we first write x3(t) as a cubic polynomial in (xn−1,xn,xn+1) and then ..... coefficients, the quadratic equation in xn+N has real and distinct roots which in ...
Tataru, Paula; Hobolth, Asger
2011-12-05
Continuous time Markov chains (CTMCs) is a widely used model for describing the evolution of DNA sequences on the nucleotide, amino acid or codon level. The sufficient statistics for CTMCs are the time spent in a state and the number of changes between any two states. In applications past evolutionary events (exact times and types of changes) are unaccessible and the past must be inferred from DNA sequence data observed in the present. We describe and implement three algorithms for computing linear combinations of expected values of the sufficient statistics, conditioned on the end-points of the chain, and compare their performance with respect to accuracy and running time. The first algorithm is based on an eigenvalue decomposition of the rate matrix (EVD), the second on uniformization (UNI), and the third on integrals of matrix exponentials (EXPM). The implementation in R of the algorithms is available at http://www.birc.au.dk/~paula/. We use two different models to analyze the accuracy and eight experiments to investigate the speed of the three algorithms. We find that they have similar accuracy and that EXPM is the slowest method. Furthermore we find that UNI is usually faster than EVD.
Directory of Open Access Journals (Sweden)
Tataru Paula
2011-12-01
Full Text Available Abstract Background Continuous time Markov chains (CTMCs is a widely used model for describing the evolution of DNA sequences on the nucleotide, amino acid or codon level. The sufficient statistics for CTMCs are the time spent in a state and the number of changes between any two states. In applications past evolutionary events (exact times and types of changes are unaccessible and the past must be inferred from DNA sequence data observed in the present. Results We describe and implement three algorithms for computing linear combinations of expected values of the sufficient statistics, conditioned on the end-points of the chain, and compare their performance with respect to accuracy and running time. The first algorithm is based on an eigenvalue decomposition of the rate matrix (EVD, the second on uniformization (UNI, and the third on integrals of matrix exponentials (EXPM. The implementation in R of the algorithms is available at http://www.birc.au.dk/~paula/. Conclusions We use two different models to analyze the accuracy and eight experiments to investigate the speed of the three algorithms. We find that they have similar accuracy and that EXPM is the slowest method. Furthermore we find that UNI is usually faster than EVD.
The Playground Game: Inquiry‐Based Learning About Research Methods and Statistics
Westera, Wim; Slootmaker, Aad; Kurvers, Hub
2014-01-01
The Playground Game is a web-based game that was developed for teaching research methods and statistics to nursing and social sciences students in higher education and vocational training. The complexity and abstract nature of research methods and statistics poses many challenges for students. The
APA's Learning Objectives for Research Methods and Statistics in Practice: A Multimethod Analysis
Tomcho, Thomas J.; Rice, Diana; Foels, Rob; Folmsbee, Leah; Vladescu, Jason; Lissman, Rachel; Matulewicz, Ryan; Bopp, Kara
2009-01-01
Research methods and statistics courses constitute a core undergraduate psychology requirement. We analyzed course syllabi and faculty self-reported coverage of both research methods and statistics course learning objectives to assess the concordance with APA's learning objectives (American Psychological Association, 2007). We obtained a sample of…
Ossai, Peter Agbadobi Uloku
2016-01-01
This study examined the relationship between students' scores on Research Methods and statistics, and undergraduate project at the final year. The purpose was to find out whether students matched knowledge of research with project-writing skill. The study adopted an expost facto correlational design. Scores on Research Methods and Statistics for…
Yucel, Abdulkadir C.; Bagci, Hakan; Michielssen, Eric
2015-01-01
An efficient method for statistically characterizing multiconductor transmission line (MTL) networks subject to a large number of manufacturing uncertainties is presented. The proposed method achieves its efficiency by leveraging a high
Ryazanova, A. A.; Okladnikov, I. G.; Gordov, E. P.
2017-11-01
The frequency of occurrence and magnitude of precipitation and temperature extreme events show positive trends in several geographical regions. These events must be analyzed and studied in order to better understand their impact on the environment, predict their occurrences, and mitigate their effects. For this purpose, we augmented web-GIS called “CLIMATE” to include a dedicated statistical package developed in the R language. The web-GIS “CLIMATE” is a software platform for cloud storage processing and visualization of distributed archives of spatial datasets. It is based on a combined use of web and GIS technologies with reliable procedures for searching, extracting, processing, and visualizing the spatial data archives. The system provides a set of thematic online tools for the complex analysis of current and future climate changes and their effects on the environment. The package includes new powerful methods of time-dependent statistics of extremes, quantile regression and copula approach for the detailed analysis of various climate extreme events. Specifically, the very promising copula approach allows obtaining the structural connections between the extremes and the various environmental characteristics. The new statistical methods integrated into the web-GIS “CLIMATE” can significantly facilitate and accelerate the complex analysis of climate extremes using only a desktop PC connected to the Internet.
Chen, Wen Li Kelly; Likhitpanichkul, Morakot; Ho, Anthony; Simmons, Craig A
2010-03-01
Cell-substrate interactions are multifaceted, involving the integration of various physical and biochemical signals. The interactions among these microenvironmental factors cannot be facilely elucidated and quantified by conventional experimentation, and necessitate multifactorial strategies. Here we describe an approach that integrates statistical design and analysis of experiments with automated microscopy to systematically investigate the combinatorial effects of substrate-derived stimuli (substrate stiffness and matrix protein concentration) on mesenchymal stem cell (MSC) spreading, proliferation and osteogenic differentiation. C3H10T1/2 cells were grown on type I collagen- or fibronectin-coated polyacrylamide hydrogels with tunable mechanical properties. Experimental conditions, which were defined according to central composite design, consisted of specific permutations of substrate stiffness (3-144 kPa) and adhesion protein concentration (7-520 microg/mL). Spreading area, BrdU incorporation and Runx2 nuclear translocation were quantified using high-content microscopy and modeled as mathematical functions of substrate stiffness and protein concentration. The resulting response surfaces revealed distinct patterns of protein-specific, substrate stiffness-dependent modulation of MSC proliferation and differentiation, demonstrating the advantage of statistical modeling in the detection and description of higher-order cellular responses. In a broader context, this approach can be adapted to study other types of cell-material interactions and can facilitate the efficient screening and optimization of substrate properties for applications involving cell-material interfaces. Copyright 2009 Elsevier Ltd. All rights reserved.
Measuring the data universe data integration using statistical data and metadata exchange
Stahl, Reinhold
2018-01-01
This richly illustrated book provides an easy-to-read introduction to the challenges of organizing and integrating modern data worlds, explaining the contribution of public statistics and the ISO standard SDMX (Statistical Data and Metadata Exchange). As such, it is a must for data experts as well those aspiring to become one. Today, exponentially growing data worlds are increasingly determining our professional and private lives. The rapid increase in the amount of globally available data, fueled by search engines and social networks but also by new technical possibilities such as Big Data, offers great opportunities. But whatever the undertaking – driving the block chain revolution or making smart phones even smarter – success will be determined by how well it is possible to integrate, i.e. to collect, link and evaluate, the required data. One crucial factor in this is the introduction of a cross-domain order system in combination with a standardization of the data structure. Using everyday examples, th...
Directory of Open Access Journals (Sweden)
Turnbull Arran K
2012-08-01
Full Text Available Abstract Background Affymetrix GeneChips and Illumina BeadArrays are the most widely used commercial single channel gene expression microarrays. Public data repositories are an extremely valuable resource, providing array-derived gene expression measurements from many thousands of experiments. Unfortunately many of these studies are underpowered and it is desirable to improve power by combining data from more than one study; we sought to determine whether platform-specific bias precludes direct integration of probe intensity signals for combined reanalysis. Results Using Affymetrix and Illumina data from the microarray quality control project, from our own clinical samples, and from additional publicly available datasets we evaluated several approaches to directly integrate intensity level expression data from the two platforms. After mapping probe sequences to Ensembl genes we demonstrate that, ComBat and cross platform normalisation (XPN, significantly outperform mean-centering and distance-weighted discrimination (DWD in terms of minimising inter-platform variance. In particular we observed that DWD, a popular method used in a number of previous studies, removed systematic bias at the expense of genuine biological variability, potentially reducing legitimate biological differences from integrated datasets. Conclusion Normalised and batch-corrected intensity-level data from Affymetrix and Illumina microarrays can be directly combined to generate biologically meaningful results with improved statistical power for robust, integrated reanalysis.
Analysis of Statistical Methods and Errors in the Articles Published in the Korean Journal of Pain
Yim, Kyoung Hoon; Han, Kyoung Ah; Park, Soo Young
2010-01-01
Background Statistical analysis is essential in regard to obtaining objective reliability for medical research. However, medical researchers do not have enough statistical knowledge to properly analyze their study data. To help understand and potentially alleviate this problem, we have analyzed the statistical methods and errors of articles published in the Korean Journal of Pain (KJP), with the intention to improve the statistical quality of the journal. Methods All the articles, except case reports and editorials, published from 2004 to 2008 in the KJP were reviewed. The types of applied statistical methods and errors in the articles were evaluated. Results One hundred and thirty-nine original articles were reviewed. Inferential statistics and descriptive statistics were used in 119 papers and 20 papers, respectively. Only 20.9% of the papers were free from statistical errors. The most commonly adopted statistical method was the t-test (21.0%) followed by the chi-square test (15.9%). Errors of omission were encountered 101 times in 70 papers. Among the errors of omission, "no statistics used even though statistical methods were required" was the most common (40.6%). The errors of commission were encountered 165 times in 86 papers, among which "parametric inference for nonparametric data" was the most common (33.9%). Conclusions We found various types of statistical errors in the articles published in the KJP. This suggests that meticulous attention should be given not only in the applying statistical procedures but also in the reviewing process to improve the value of the article. PMID:20552071
International Nuclear Information System (INIS)
Frome, E.L.; Khare, M.
1980-01-01
Brodsky's paper 'A Statistical Method for Testing Epidemiological Results, as applied to the Hanford Worker Population', (Health Phys., 36, 611-628, 1979) proposed two test statistics for use in comparing the survival experience of a group of employees and controls. This letter states that both of the test statistics were computed using incorrect formulas and concludes that the results obtained using these statistics may also be incorrect. In his reply Brodsky concurs with the comments on the proper formulation of estimates of pooled standard errors in constructing test statistics but believes that the erroneous formulation does not invalidate the major points, results and discussions of his paper. (author)
Raunig, David L; McShane, Lisa M; Pennello, Gene; Gatsonis, Constantine; Carson, Paul L; Voyvodic, James T; Wahl, Richard L; Kurland, Brenda F; Schwarz, Adam J; Gönen, Mithat; Zahlmann, Gudrun; Kondratovich, Marina V; O'Donnell, Kevin; Petrick, Nicholas; Cole, Patricia E; Garra, Brian; Sullivan, Daniel C
2015-02-01
Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.
A chronicle of permutation statistical methods 1920–2000, and beyond
Berry, Kenneth J; Mielke Jr , Paul W
2014-01-01
The focus of this book is on the birth and historical development of permutation statistical methods from the early 1920s to the near present. Beginning with the seminal contributions of R.A. Fisher, E.J.G. Pitman, and others in the 1920s and 1930s, permutation statistical methods were initially introduced to validate the assumptions of classical statistical methods. Permutation methods have advantages over classical methods in that they are optimal for small data sets and non-random samples, are data-dependent, and are free of distributional assumptions. Permutation probability values may be exact, or estimated via moment- or resampling-approximation procedures. Because permutation methods are inherently computationally-intensive, the evolution of computers and computing technology that made modern permutation methods possible accompanies the historical narrative. Permutation analogs of many well-known statistical tests are presented in a historical context, including multiple correlation and regression, ana...
Statistical distribution of components of energy eigenfunctions: from nearly-integrable to chaotic
International Nuclear Information System (INIS)
Wang, Jiaozi; Wang, Wen-ge
2016-01-01
We study the statistical distribution of components in the non-perturbative parts of energy eigenfunctions (EFs), in which main bodies of the EFs lie. Our numerical simulations in five models show that deviation of the distribution from the prediction of random matrix theory (RMT) is useful in characterizing the process from nearly-integrable to chaotic, in a way somewhat similar to the nearest-level-spacing distribution. But, the statistics of EFs reveals some more properties, as described below. (i) In the process of approaching quantum chaos, the distribution of components shows a delay feature compared with the nearest-level-spacing distribution in most of the models studied. (ii) In the quantum chaotic regime, the distribution of components always shows small but notable deviation from the prediction of RMT in models possessing classical counterparts, while, the deviation can be almost negligible in models not possessing classical counterparts. (iii) In models whose Hamiltonian matrices possess a clear band structure, tails of EFs show statistical behaviors obviously different from those in the main bodies, while, the difference is smaller for Hamiltonian matrices without a clear band structure.
Joyce, Brendan; Lee, Danny; Rubio, Alex; Ogurtsov, Aleksey; Alves, Gelio; Yu, Yi-Kuo
2018-01-01
Abstract Objective RAId is a software package that has been actively developed for the past 10 years for computationally and visually analyzing MS/MS data. Founded on rigorous statistical methods, RAId’s core program computes accurate E-values for peptides and proteins identified during database searches. Making this robust tool readily accessible for the proteomics community by developing a graphical user interface (GUI) is our main goa...
Strauch, R. L.; Istanbulluoglu, E.
2017-12-01
We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.
International Nuclear Information System (INIS)
Myrheim, J.
1993-06-01
The thesis deals with the application of different methods to the quantization problem for system of identical particles in one and two dimensions. The standard method is the analytic quantization method due to Schroedinger, which leads to the concept of fractional statistics in one and two dimensions. Two-dimensional particles with fractional statistics are well known by the name of anyons. Two alternative quantization methods are shown by the author, the algebraic method of Heisenberg and the Feynman path integral method. The Feynman method is closely related to the Schroedinger method, whereas the Heisenberg and Schroedinger methods may give different results. The relation between the Heisenberg and Schroedinger methods is discussed. The Heisenberg method is applied to the equations of motion of vortices in superfluid helium, which have the form of Hamiltonian equations for a one-dimensional system. The same method is also discussed more generally for systems of identical particles in one and two dimensions. An application of the Feynman method to the problem of computing the equation of state for a gas of anyons is presented. 104 refs., 4 figs
Can We Use Polya’s Method to Improve Students’ Performance in the Statistics Classes?
Directory of Open Access Journals (Sweden)
Indika Wickramasinghe
2015-01-01
Full Text Available In this study, Polya’s problem-solving method is introduced in a statistics class in an effort to enhance students’ performance. Teaching the method was applied to one of the two introductory-level statistics classes taught by the same instructor, and a comparison was made between the performances in the two classes. The results indicate there was a significant improvement of the students’ performance in the class in which Polya’s method was introduced.
Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar
Meneghini, R.; Jones, J. A.; Iguchi, T.; Okamoto, K.; Liao, L.; Busalacchi, Antonio J. (Technical Monitor)
2000-01-01
The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by
Integrated circuit and method of arbitration in a network on an integrated circuit.
2011-01-01
The invention relates to an integrated circuit and to a method of arbitration in a network on an integrated circuit. According to the invention, a method of arbitration in a network on an integrated circuit is provided, the network comprising a router unit, the router unit comprising a first input
Integrals of Frullani type and the method of brackets
Directory of Open Access Journals (Sweden)
Bravo Sergio
2017-01-01
Full Text Available The method of brackets is a collection of heuristic rules, some of which have being made rigorous, that provide a flexible, direct method for the evaluation of definite integrals. The present work uses this method to establish classical formulas due to Frullani which provide values of a specific family of integrals. Some generalizations are established.
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.
Accurate Electromagnetic Modeling Methods for Integrated Circuits
Sheng, Z.
2010-01-01
The present development of modern integrated circuits (IC’s) is characterized by a number of critical factors that make their design and verification considerably more difficult than before. This dissertation addresses the important questions of modeling all electromagnetic behavior of features on
Faghihi, Foroozandeh; Rakow, Ernest A.
This study, conducted at the University of Memphis (Tennessee), compared the effects of a self-paced method of instruction on the attitudes and perceptions of students enrolled in an undergraduate statistics course with those of a comparable group of students taking statistics in a traditional lecture setting. The non-traditional course used a…
Multivariate Statistical Methods as a Tool of Financial Analysis of Farm Business
Czech Academy of Sciences Publication Activity Database
Novák, J.; Sůvová, H.; Vondráček, Jiří
2002-01-01
Roč. 48, č. 1 (2002), s. 9-12 ISSN 0139-570X Institutional research plan: AV0Z1030915 Keywords : financial analysis * financial ratios * multivariate statistical methods * correlation analysis * discriminant analysis * cluster analysis Subject RIV: BB - Applied Statistics, Operational Research
de Vries, John
This paper addresses the issue of measuring the integration of various ethnocultural communities into Canadian society by means of statistical or social indicators. The overall philosophy of the study is based on the following principles: (1) indicators should have a clear meaning with respect to the underlying concept of integration; (2)…
Evaluation of the ICS and DEW scatter correction methods for low statistical content scans in 3D PET
International Nuclear Information System (INIS)
Sossi, V.; Oakes, T.R.; Ruth, T.J.
1996-01-01
The performance of the Integral Convolution and the Dual Energy Window scatter correction methods in 3D PET has been evaluated over a wide range of statistical content of acquired data (1M to 400M events) The order in which scatter correction and detector normalization should be applied has also been investigated. Phantom and human neuroreceptor studies were used with the following figures of merit: axial and radial uniformity, sinogram and image noise, contrast accuracy and contrast accuracy uniformity. Both scatter correction methods perform reliably in the range of number of events examined. Normalization applied after scatter correction yields better radial uniformity and fewer image artifacts
Chen, Zhe; Qiu, Zurong; Huo, Xinming; Fan, Yuming; Li, Xinghua
2017-03-01
A fiber-capacitive drop analyzer is an instrument which monitors a growing droplet to produce a capacitive opto-tensiotrace (COT). Each COT is an integration of fiber light intensity signals and capacitance signals and can reflect the unique physicochemical property of a liquid. In this study, we propose a solution analytical and concentration quantitative method based on multivariate statistical methods. Eight characteristic values are extracted from each COT. A series of COT characteristic values of training solutions at different concentrations compose a data library of this kind of solution. A two-stage linear discriminant analysis is applied to analyze different solution libraries and establish discriminant functions. Test solutions can be discriminated by these functions. After determining the variety of test solutions, Spearman correlation test and principal components analysis are used to filter and reduce dimensions of eight characteristic values, producing a new representative parameter. A cubic spline interpolation function is built between the parameters and concentrations, based on which we can calculate the concentration of the test solution. Methanol, ethanol, n-propanol, and saline solutions are taken as experimental subjects in this paper. For each solution, nine or ten different concentrations are chosen to be the standard library, and the other two concentrations compose the test group. By using the methods mentioned above, all eight test solutions are correctly identified and the average relative error of quantitative analysis is 1.11%. The method proposed is feasible which enlarges the applicable scope of recognizing liquids based on the COT and improves the concentration quantitative precision, as well.
Adaptive integral equation methods in transport theory
International Nuclear Information System (INIS)
Kelley, C.T.
1992-01-01
In this paper, an adaptive multilevel algorithm for integral equations is described that has been developed with the Chandrasekhar H equation and its generalizations in mind. The algorithm maintains good performance when the Frechet derivative of the nonlinear map is singular at the solution, as happens in radiative transfer with conservative scattering and in critical neutron transport. Numerical examples that demonstrate the algorithm's effectiveness are presented
A symplectic integration method for elastic filaments
Ladd, Tony; Misra, Gaurav
2009-03-01
Elastic rods are a ubiquitous coarse-grained model of semi-flexible biopolymers such as DNA, actin, and microtubules. The Worm-Like Chain (WLC) is the standard numerical model for semi-flexible polymers, but it is only a linearized approximation to the dynamics of an elastic rod, valid for small deflections; typically the torsional motion is neglected as well. In the standard finite-difference and finite-element formulations of an elastic rod, the continuum equations of motion are discretized in space and time, but it is then difficult to ensure that the Hamiltonian structure of the exact equations is preserved. Here we discretize the Hamiltonian itself, expressed as a line integral over the contour of the filament. This discrete representation of the continuum filament can then be integrated by one of the explicit symplectic integrators frequently used in molecular dynamics. The model systematically approximates the continuum partial differential equations, but has the same level of computational complexity as molecular dynamics and is constraint free. Numerical tests show that the algorithm is much more stable than a finite-difference formulation and can be used for high aspect ratio filaments, such as actin. We present numerical results for the deterministic and stochastic motion of single filaments.
Probability of Detection (POD) as a statistical model for the validation of qualitative methods.
Wehling, Paul; LaBudde, Robert A; Brunelle, Sharon L; Nelson, Maria T
2011-01-01
A statistical model is presented for use in validation of qualitative methods. This model, termed Probability of Detection (POD), harmonizes the statistical concepts and parameters between quantitative and qualitative method validation. POD characterizes method response with respect to concentration as a continuous variable. The POD model provides a tool for graphical representation of response curves for qualitative methods. In addition, the model allows comparisons between candidate and reference methods, and provides calculations of repeatability, reproducibility, and laboratory effects from collaborative study data. Single laboratory study and collaborative study examples are given.
Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka
2017-04-09
Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.
Directory of Open Access Journals (Sweden)
Jude Adekunle Adeleke
2017-04-01
Full Text Available Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.
An Efficient Graph-based Method for Long-term Land-use Change Statistics
Directory of Open Access Journals (Sweden)
Yipeng Zhang
2015-12-01
Full Text Available Statistical analysis of land-use change plays an important role in sustainable land management and has received increasing attention from scholars and administrative departments. However, the statistical process involving spatial overlay analysis remains difficult and needs improvement to deal with mass land-use data. In this paper, we introduce a spatio-temporal flow network model to reveal the hidden relational information among spatio-temporal entities. Based on graph theory, the constant condition of saturated multi-commodity flow is derived. A new method based on a network partition technique of spatio-temporal flow network are proposed to optimize the transition statistical process. The effectiveness and efficiency of the proposed method is verified through experiments using land-use data in Hunan from 2009 to 2014. In the comparison among three different land-use change statistical methods, the proposed method exhibits remarkable superiority in efficiency.
International Nuclear Information System (INIS)
Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan
2017-01-01
analysis (PCA) and cluster analysis (CA). - Highlights: • Critically reviewed field studies of regional distribution of heavy metal in soil. • Reviewed studies combined GIS with multivariate statistical analysis. • Summarized the most common sampling strategies, GIS method, and multivariate technique. • Identified determining and correlating factors for soil heavy metals. • Discussed major natural and anthropogenic sources of soil heavy metals. - The integration of GIS and multivariate statistical analysis is a valuable tool in studying the regional distribution of heavy metals in soil.
Statistical methods of discrimination and classification advances in theory and applications
Choi, Sung C
1986-01-01
Statistical Methods of Discrimination and Classification: Advances in Theory and Applications is a collection of papers that tackles the multivariate problems of discriminating and classifying subjects into exclusive population. The book presents 13 papers that cover that advancement in the statistical procedure of discriminating and classifying. The studies in the text primarily focus on various methods of discriminating and classifying variables, such as multiple discriminant analysis in the presence of mixed continuous and categorical data; choice of the smoothing parameter and efficiency o
Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.
2016-01-01
Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal, Ginsburg, & Schau, 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof, Ceroni, Jeong, & Moghaddam, 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to...
An improved method for statistical analysis of raw accelerator mass spectrometry data
International Nuclear Information System (INIS)
Gutjahr, A.; Phillips, F.; Kubik, P.W.; Elmore, D.
1987-01-01
Hierarchical statistical analysis is an appropriate method for statistical treatment of raw accelerator mass spectrometry (AMS) data. Using Monte Carlo simulations we show that this method yields more accurate estimates of isotope ratios and analytical uncertainty than the generally used propagation of errors approach. The hierarchical analysis is also useful in design of experiments because it can be used to identify sources of variability. 8 refs., 2 figs
Statistical methods to monitor the West Valley off-gas system
International Nuclear Information System (INIS)
Eggett, D.L.
1990-01-01
This paper reports on the of-gas system for the ceramic melter operated at the West Valley Demonstration Project at West Valley, NY, monitored during melter operation. A one-at-a-time method of monitoring the parameters of the off-gas system is not statistically sound. Therefore, multivariate statistical methods appropriate for the monitoring of many correlated parameters will be used. Monitoring a large number of parameters increases the probability of a false out-of-control signal. If the parameters being monitored are statistically independent, the control limits can be easily adjusted to obtain the desired probability of a false out-of-control signal. The principal component (PC) scores have desirable statistical properties when the original variables are distributed as multivariate normals. Two statistics derived from the PC scores and used to form multivariate control charts are outlined and their distributional properties reviewed
Physics-based statistical model and simulation method of RF propagation in urban environments
Pao, Hsueh-Yuan; Dvorak, Steven L.
2010-09-14
A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.
Statistical Methods for the detection of answer copying on achievement tests
Sotaridona, Leonardo
2003-01-01
This thesis contains a collection of studies where statistical methods for the detection of answer copying on achievement tests in multiple-choice format are proposed and investigated. Although all methods are suited to detect answer copying, each method is designed to address specific
Transport coefficients for deeply inelastic scattering from the Feynman path integral method
International Nuclear Information System (INIS)
Brink, D.M.; Neto, J.; Weidenmueller, H.A.
1979-01-01
Friction and diffusion coefficients can be derived simply by combining statistical arguments with the Feynman path integral method. A transport equation for Feynman's influence functional is obtained, and transport coefficients are deduced from it. The expressions are discussed in the limits of weak, and of strong coupling. (Auth.)
Assessment of statistical methods used in library-based approaches to microbial source tracking.
Ritter, Kerry J; Carruthers, Ethan; Carson, C Andrew; Ellender, R D; Harwood, Valerie J; Kingsley, Kyle; Nakatsu, Cindy; Sadowsky, Michael; Shear, Brian; West, Brian; Whitlock, John E; Wiggins, Bruce A; Wilbur, Jayson D
2003-12-01
Several commonly used statistical methods for fingerprint identification in microbial source tracking (MST) were examined to assess the effectiveness of pattern-matching algorithms to correctly identify sources. Although numerous statistical methods have been employed for source identification, no widespread consensus exists as to which is most appropriate. A large-scale comparison of several MST methods, using identical fecal sources, presented a unique opportunity to assess the utility of several popular statistical methods. These included discriminant analysis, nearest neighbour analysis, maximum similarity and average similarity, along with several measures of distance or similarity. Threshold criteria for excluding uncertain or poorly matched isolates from final analysis were also examined for their ability to reduce false positives and increase prediction success. Six independent libraries used in the study were constructed from indicator bacteria isolated from fecal materials of humans, seagulls, cows and dogs. Three of these libraries were constructed using the rep-PCR technique and three relied on antibiotic resistance analysis (ARA). Five of the libraries were constructed using Escherichia coli and one using Enterococcus spp. (ARA). Overall, the outcome of this study suggests a high degree of variability across statistical methods. Despite large differences in correct classification rates among the statistical methods, no single statistical approach emerged as superior. Thresholds failed to consistently increase rates of correct classification and improvement was often associated with substantial effective sample size reduction. Recommendations are provided to aid in selecting appropriate analyses for these types of data.
A robust statistical method for association-based eQTL analysis.
Directory of Open Access Journals (Sweden)
Ning Jiang
Full Text Available It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS is statistical inference of linkage disequilibrium (LD between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation.We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations.The analyses show that the new method confers an improved statistical power for detecting genuine genetic association in subpopulations and an effective control of spurious associations stemmed from population structure when compared with other two popularly implemented methods in the literature of GWAS.
LaBudde, Robert A; Harnly, James M
2012-01-01
A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.
Integral Method of Boundary Characteristics: Neumann Condition
Kot, V. A.
2018-05-01
A new algorithm, based on systems of identical equalities with integral and differential boundary characteristics, is proposed for solving boundary-value problems on the heat conduction in bodies canonical in shape at a Neumann boundary condition. Results of a numerical analysis of the accuracy of solving heat-conduction problems with variable boundary conditions with the use of this algorithm are presented. The solutions obtained with it can be considered as exact because their errors comprise hundredths and ten-thousandths of a persent for a wide range of change in the parameters of a problem.
Using HIV&AIDS statistics in pre-service Mathematics Education to integrate HIV&AIDS education.
van Laren, Linda
2012-12-01
In South Africa, the HIV&AIDS education policy documents indicate opportunities for integration across disciplines/subjects. There are different interpretations of integration/inclusion and mainstreaming HIV&AIDS education, and numerous levels of integration. Integration ensures that learners experience the disciplines/subjects as being linked and related, and integration is required to support and expand the learners' opportunities to attain skills, acquire knowledge and develop attitudes and values across the curriculum. This study makes use of self-study methodology where I, a teacher educator, aim to improve my practice through including HIV&AIDS statistics in Mathematics Education. This article focuses on how I used HIV&AIDS statistics to facilitate pre-service teacher reflection and introduce them to integration of HIV&AIDS education across the curriculum. After pre-service teachers were provided with HIV statistics, they drew a pie chart which graphically illustrated the situation and reflected on issues relating to HIV&AIDS. Three themes emerged from the analysis of their reflections. The themes relate to the need for further HIV&AIDS education, the changing pastoral role of teachers and the changing context of teaching. This information indicates that the use of statistics is an appropriate means of initiating the integration of HIV&AIDS education into the academic curriculum.
Spectral-Lagrangian methods for collisional models of non-equilibrium statistical states
International Nuclear Information System (INIS)
Gamba, Irene M.; Tharkabhushanam, Sri Harsha
2009-01-01
We propose a new spectral Lagrangian based deterministic solver for the non-linear Boltzmann transport equation (BTE) in d-dimensions for variable hard sphere (VHS) collision kernels with conservative or non-conservative binary interactions. The method is based on symmetries of the Fourier transform of the collision integral, where the complexity in its computation is reduced to a separate integral over the unit sphere S d-1 . The conservation of moments is enforced by Lagrangian constraints. The resulting scheme, implemented in free space, is very versatile and adjusts in a very simple manner to several cases that involve energy dissipation due to local micro-reversibility (inelastic interactions) or elastic models of slowing down process. Our simulations are benchmarked with available exact self-similar solutions, exact moment equations and analytical estimates for the homogeneous Boltzmann equation, both for elastic and inelastic VHS interactions. Benchmarking of the simulations involves the selection of a time self-similar rescaling of the numerical distribution function which is performed using the continuous spectrum of the equation for Maxwell molecules as studied first in Bobylev et al. [A.V. Bobylev, C. Cercignani, G. Toscani, Proof of an asymptotic property of self-similar solutions of the Boltzmann equation for granular materials, Journal of Statistical Physics 111 (2003) 403-417] and generalized to a wide range of related models in Bobylev et al. [A.V. Bobylev, C. Cercignani, I.M. Gamba, On the self-similar asymptotics for generalized non-linear kinetic Maxwell models, Communication in Mathematical Physics, in press. URL: ( )]. The method also produces accurate results in the case of inelastic diffusive Boltzmann equations for hard spheres (inelastic collisions under thermal bath), where overpopulated non-Gaussian exponential tails have been conjectured in computations by stochastic methods [T.V. Noije, M. Ernst, Velocity distributions in homogeneously
Selective Integration in the Material-Point Method
DEFF Research Database (Denmark)
Andersen, Lars; Andersen, Søren; Damkilde, Lars
2009-01-01
The paper deals with stress integration in the material-point method. In order to avoid parasitic shear in bending, a formulation is proposed, based on selective integration in the background grid that is used to solve the governing equations. The suggested integration scheme is compared...... to a traditional material-point-method computation in which the stresses are evaluated at the material points. The deformation of a cantilever beam is analysed, assuming elastic or elastoplastic material behaviour....
Numerical method of singular problems on singular integrals
International Nuclear Information System (INIS)
Zhao Huaiguo; Mou Zongze
1992-02-01
As first part on the numerical research of singular problems, a numerical method is proposed for singular integrals. It is shown that the procedure is quite powerful for solving physics calculation with singularity such as the plasma dispersion function. Useful quadrature formulas for some class of the singular integrals are derived. In general, integrals with more complex singularities can be dealt by this method easily
Meta-analysis as Statistical and Analytical Method of Journal's Content Scientific Evaluation.
Masic, Izet; Begic, Edin
2015-02-01
A meta-analysis is a statistical and analytical method which combines and synthesizes different independent studies and integrates their results into one common result. Analysis of the journals "Medical Archives", "Materia Socio Medica" and "Acta Informatica Medica", which are located in the most eminent indexed databases of the biomedical milieu. The study has retrospective and descriptive character, and included the period of the calendar year 2014. Study included six editions of all three journals (total of 18 journals). In this period was published a total of 291 articles (in the "Medical Archives" 110, "Materia Socio Medica" 97, and in "Acta Informatica Medica" 84). The largest number of articles was original articles. Small numbers have been published as professional, review articles and case reports. Clinical events were most common in the first two journals, while in the journal "Acta Informatica Medica" belonged to the field of medical informatics, as part of pre-clinical medical disciplines. Articles are usually required period of fifty to fifty nine days for review. Articles were received from four continents, mostly from Europe. The authors are most often from the territory of Bosnia and Herzegovina, then Iran, Kosovo and Macedonia. The number of articles published each year is increasing, with greater participation of authors from different continents and abroad. Clinical medical disciplines are the most common, with the broader spectrum of topics and with a growing number of original articles. Greater support of the wider scientific community is needed for further development of all three of the aforementioned journals.
Using Statistical and Probabilistic Methods to Evaluate Health Risk Assessment: A Case Study
Directory of Open Access Journals (Sweden)
Hongjing Wu
2014-06-01
Full Text Available The toxic chemical and heavy metals within wastewater can cause serious adverse impacts on human health. Health risk assessment (HRA is an effective tool for supporting decision-making and corrective actions in water quality management. HRA can also help people understand the water quality and quantify the adverse effects of pollutants on human health. Due to the imprecision of data, measurement error and limited available information, uncertainty is inevitable in the HRA process. The purpose of this study is to integrate statistical and probabilistic methods to deal with censored and limited numbers of input data to improve the reliability of the non-cancer HRA of dermal contact exposure to contaminated river water by considering uncertainty. A case study in the Kelligrews River in St. John’s, Canada, was conducted to demonstrate the feasibility and capacity of the proposed approach. Five heavy metals were selected to evaluate the risk level, including arsenic, molybdenum, zinc, uranium and manganese. The results showed that the probability of the total hazard index of dermal exposure exceeding 1 is very low, and there is no obvious evidence of risk in the study area.
Narayanan, Roshni; Nugent, Rebecca; Nugent, Kenneth
2015-10-01
Accreditation Council for Graduate Medical Education guidelines require internal medicine residents to develop skills in the interpretation of medical literature and to understand the principles of research. A necessary component is the ability to understand the statistical methods used and their results, material that is not an in-depth focus of most medical school curricula and residency programs. Given the breadth and depth of the current medical literature and an increasing emphasis on complex, sophisticated statistical analyses, the statistical foundation and education necessary for residents are uncertain. We reviewed the statistical methods and terms used in 49 articles discussed at the journal club in the Department of Internal Medicine residency program at Texas Tech University between January 1, 2013 and June 30, 2013. We collected information on the study type and on the statistical methods used for summarizing and comparing samples, determining the relations between independent variables and dependent variables, and estimating models. We then identified the typical statistics education level at which each term or method is learned. A total of 14 articles came from the Journal of the American Medical Association Internal Medicine, 11 from the New England Journal of Medicine, 6 from the Annals of Internal Medicine, 5 from the Journal of the American Medical Association, and 13 from other journals. Twenty reported randomized controlled trials. Summary statistics included mean values (39 articles), category counts (38), and medians (28). Group comparisons were based on t tests (14 articles), χ2 tests (21), and nonparametric ranking tests (10). The relations between dependent and independent variables were analyzed with simple regression (6 articles), multivariate regression (11), and logistic regression (8). Nine studies reported odds ratios with 95% confidence intervals, and seven analyzed test performance using sensitivity and specificity calculations
8th International Conference on Soft Methods in Probability and Statistics
Giordani, Paolo; Vantaggi, Barbara; Gagolewski, Marek; Gil, María; Grzegorzewski, Przemysław; Hryniewicz, Olgierd
2017-01-01
This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.
Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.
2016-01-01
Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147
Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M
2016-01-01
Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.
Application of the functional integration method to the Dicke-type models
International Nuclear Information System (INIS)
Popov, V.N.; Fedotov, S.A.
1981-01-01
The asymptotics of the statistical model sum of the Dicke-type (Z/Z 6 ) is obtained and strictly proved at large N (N is an atomic number; Z is a statistical model sum; Z 0 is a statistical free system sum) using the functional integration method. The model with one bose-field mode is considered. A detailed proof is carried out at T > Tsub(c). An idea of the proof is planned and asymptotic formulae are presented for T < Tsub(c) and in the vicinity of Tsub(c)
Schaid, Daniel J
2010-01-01
Measures of genomic similarity are the basis of many statistical analytic methods. We review the mathematical and statistical basis of similarity methods, particularly based on kernel methods. A kernel function converts information for a pair of subjects to a quantitative value representing either similarity (larger values meaning more similar) or distance (smaller values meaning more similar), with the requirement that it must create a positive semidefinite matrix when applied to all pairs of subjects. This review emphasizes the wide range of statistical methods and software that can be used when similarity is based on kernel methods, such as nonparametric regression, linear mixed models and generalized linear mixed models, hierarchical models, score statistics, and support vector machines. The mathematical rigor for these methods is summarized, as is the mathematical framework for making kernels. This review provides a framework to move from intuitive and heuristic approaches to define genomic similarities to more rigorous methods that can take advantage of powerful statistical modeling and existing software. A companion paper reviews novel approaches to creating kernels that might be useful for genomic analyses, providing insights with examples [1]. Copyright © 2010 S. Karger AG, Basel.
Hybrid statistics-simulations based method for atom-counting from ADF STEM images
Energy Technology Data Exchange (ETDEWEB)
De wael, Annelies, E-mail: annelies.dewael@uantwerpen.be [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); De Backer, Annick [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); Jones, Lewys; Nellist, Peter D. [Department of Materials, University of Oxford, Parks Road, OX1 3PH Oxford (United Kingdom); Van Aert, Sandra, E-mail: sandra.vanaert@uantwerpen.be [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium)
2017-06-15
A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. - Highlights: • A hybrid method for atom-counting from ADF STEM images is introduced. • Image simulations are incorporated into a statistical framework in a reliable manner. • Limits of the existing methods for atom-counting are far exceeded. • Reliable counting results from an experimental low dose image are obtained. • Progress towards reliable quantitative analysis of beam-sensitive materials is made.
Analyzing Planck and low redshift data sets with advanced statistical methods
Eifler, Tim
The recent ESA/NASA Planck mission has provided a key data set to constrain cosmology that is most sensitive to physics of the early Universe, such as inflation and primordial NonGaussianity (Planck 2015 results XIII). In combination with cosmological probes of the LargeScale Structure (LSS), the Planck data set is a powerful source of information to investigate late time phenomena (Planck 2015 results XIV), e.g. the accelerated expansion of the Universe, the impact of baryonic physics on the growth of structure, and the alignment of galaxies in their dark matter halos. It is the main objective of this proposal to re-analyze the archival Planck data, 1) with different, more recently developed statistical methods for cosmological parameter inference, and 2) to combine Planck and ground-based observations in an innovative way. We will make the corresponding analysis framework publicly available and believe that it will set a new standard for future CMB-LSS analyses. Advanced statistical methods, such as the Gibbs sampler (Jewell et al 2004, Wandelt et al 2004) have been critical in the analysis of Planck data. More recently, Approximate Bayesian Computation (ABC, see Weyant et al 2012, Akeret et al 2015, Ishida et al 2015, for cosmological applications) has matured to an interesting tool in cosmological likelihood analyses. It circumvents several assumptions that enter the standard Planck (and most LSS) likelihood analyses, most importantly, the assumption that the functional form of the likelihood of the CMB observables is a multivariate Gaussian. Beyond applying new statistical methods to Planck data in order to cross-check and validate existing constraints, we plan to combine Planck and DES data in a new and innovative way and run multi-probe likelihood analyses of CMB and LSS observables. The complexity of multiprobe likelihood analyses scale (non-linearly) with the level of correlations amongst the individual probes that are included. For the multi
Trends in study design and the statistical methods employed in a leading general medicine journal.
Gosho, M; Sato, Y; Nagashima, K; Takahashi, S
2018-02-01
Study design and statistical methods have become core components of medical research, and the methodology has become more multifaceted and complicated over time. The study of the comprehensive details and current trends of study design and statistical methods is required to support the future implementation of well-planned clinical studies providing information about evidence-based medicine. Our purpose was to illustrate study design and statistical methods employed in recent medical literature. This was an extension study of Sato et al. (N Engl J Med 2017; 376: 1086-1087), which reviewed 238 articles published in 2015 in the New England Journal of Medicine (NEJM) and briefly summarized the statistical methods employed in NEJM. Using the same database, we performed a new investigation of the detailed trends in study design and individual statistical methods that were not reported in the Sato study. Due to the CONSORT statement, prespecification and justification of sample size are obligatory in planning intervention studies. Although standard survival methods (eg Kaplan-Meier estimator and Cox regression model) were most frequently applied, the Gray test and Fine-Gray proportional hazard model for considering competing risks were sometimes used for a more valid statistical inference. With respect to handling missing data, model-based methods, which are valid for missing-at-random data, were more frequently used than single imputation methods. These methods are not recommended as a primary analysis, but they have been applied in many clinical trials. Group sequential design with interim analyses was one of the standard designs, and novel design, such as adaptive dose selection and sample size re-estimation, was sometimes employed in NEJM. Model-based approaches for handling missing data should replace single imputation methods for primary analysis in the light of the information found in some publications. Use of adaptive design with interim analyses is increasing
Momentum integral network method for thermal-hydraulic transient analysis
International Nuclear Information System (INIS)
Van Tuyle, G.J.
1983-01-01
A new momentum integral network method has been developed, and tested in the MINET computer code. The method was developed in order to facilitate the transient analysis of complex fluid flow and heat transfer networks, such as those found in the balance of plant of power generating facilities. The method employed in the MINET code is a major extension of a momentum integral method reported by Meyer. Meyer integrated the momentum equation over several linked nodes, called a segment, and used a segment average pressure, evaluated from the pressures at both ends. Nodal mass and energy conservation determined nodal flows and enthalpies, accounting for fluid compression and thermal expansion
A new method for curve fitting to the data with low statistics not using the chi2-method
International Nuclear Information System (INIS)
Awaya, T.
1979-01-01
A new method which does not use the chi 2 -fitting method is investigated in order to fit the theoretical curve to data with low statistics. The method is compared with the usual and modified chi 2 -fitting ones. The analyses are done for data which are generated by computers. It is concluded that the new method gives good results in all the cases. (Auth.)
Meta-analysis as Statistical and Analytical Method of Journal’s Content Scientific Evaluation
Masic, Izet; Begic, Edin
2015-01-01
Introduction: A meta-analysis is a statistical and analytical method which combines and synthesizes different independent studies and integrates their results into one common result. Goal: Analysis of the journals “Medical Archives”, “Materia Socio Medica” and “Acta Informatica Medica”, which are located in the most eminent indexed databases of the biomedical milieu. Material and methods: The study has retrospective and descriptive character, and included the period of the calendar year 2014. Study included six editions of all three journals (total of 18 journals). Results: In this period was published a total of 291 articles (in the “Medical Archives” 110, “Materia Socio Medica” 97, and in “Acta Informatica Medica” 84). The largest number of articles was original articles. Small numbers have been published as professional, review articles and case reports. Clinical events were most common in the first two journals, while in the journal “Acta Informatica Medica” belonged to the field of medical informatics, as part of pre-clinical medical disciplines. Articles are usually required period of fifty to fifty nine days for review. Articles were received from four continents, mostly from Europe. The authors are most often from the territory of Bosnia and Herzegovina, then Iran, Kosovo and Macedonia. Conclusion: The number of articles published each year is increasing, with greater participation of authors from different continents and abroad. Clinical medical disciplines are the most common, with the broader spectrum of topics and with a growing number of original articles. Greater support of the wider scientific community is needed for further development of all three of the aforementioned journals. PMID:25870484
Lowe, David J.; Pearce, Nicholas J. G.; Jorgensen, Murray A.; Kuehn, Stephen C.; Tryon, Christian A.; Hayward, Chris L.
2017-11-01
We define tephras and cryptotephras and their components (mainly ash-sized particles of glass ± crystals in distal deposits) and summarize the basis of tephrochronology as a chronostratigraphic correlational and dating tool for palaeoenvironmental, geological, and archaeological research. We then document and appraise recent advances in analytical methods used to determine the major, minor, and trace elements of individual glass shards from tephra or cryptotephra deposits to aid their correlation and application. Protocols developed recently for the electron probe microanalysis of major elements in individual glass shards help to improve data quality and standardize reporting procedures. A narrow electron beam (diameter ∼3-5 μm) can now be used to analyze smaller glass shards than previously attainable. Reliable analyses of 'microshards' (defined here as glass shards T2 test). Randomization tests can be used where distributional assumptions such as multivariate normality underlying parametric tests are doubtful. Compositional data may be transformed and scaled before being subjected to multivariate statistical procedures including calculation of distance matrices, hierarchical cluster analysis, and PCA. Such transformations may make the assumption of multivariate normality more appropriate. A sequential procedure using Mahalanobis distance and the Hotelling two-sample T2 test is illustrated using glass major element data from trachytic to phonolitic Kenyan tephras. All these methods require a broad range of high-quality compositional data which can be used to compare 'unknowns' with reference (training) sets that are sufficiently complete to account for all possible correlatives, including tephras with heterogeneous glasses that contain multiple compositional groups. Currently, incomplete databases are tending to limit correlation efficacy. The development of an open, online global database to facilitate progress towards integrated, high
Energy Technology Data Exchange (ETDEWEB)
Chukbar, B. K., E-mail: bchukbar@mail.ru [National Research Center Kurchatov Institute (Russian Federation)
2015-12-15
Two methods of modeling a double-heterogeneity fuel are studied: the deterministic positioning and the statistical method CORN of the MCU software package. The effect of distribution of microfuel in a pebble bed on the calculation results is studied. The results of verification of the statistical method CORN for the cases of the microfuel concentration up to 170 cm{sup –3} in a pebble bed are presented. The admissibility of homogenization of the microfuel coating with the graphite matrix is studied. The dependence of the reactivity on the relative location of fuel and graphite spheres in a pebble bed is found.
A statistical method (cross-validation) for bone loss region detection after spaceflight
Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.
2010-01-01
Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144
Classical Methods of Statistics With Applications in Fusion-Oriented Plasma Physics
Kardaun, Otto J W F
2005-01-01
Classical Methods of Statistics is a blend of theory and practical statistical methods written for graduate students and researchers interested in applications to plasma physics and its experimental aspects. It can also fruitfully be used by students majoring in probability theory and statistics. In the first part, the mathematical framework and some of the history of the subject are described. Many exercises help readers to understand the underlying concepts. In the second part, two case studies are presented exemplifying discriminant analysis and multivariate profile analysis. The introductions of these case studies outline contextual magnetic plasma fusion research. In the third part, an overview of statistical software is given and, in particular, SAS and S-PLUS are discussed. In the last chapter, several datasets with guided exercises, predominantly from the ASDEX Upgrade tokamak, are included and their physical background is concisely described. The book concludes with a list of essential keyword transl...
DEFF Research Database (Denmark)
Eslamimanesh, Ali; Gharagheizi, Farhad; Mohammadi, Amir H.
2012-01-01
We, herein, present a statistical method for diagnostics of the outliers in phase equilibrium data (dissociation data) of simple clathrate hydrates. The applied algorithm is performed on the basis of the Leverage mathematical approach, in which the statistical Hat matrix, Williams Plot, and the r......We, herein, present a statistical method for diagnostics of the outliers in phase equilibrium data (dissociation data) of simple clathrate hydrates. The applied algorithm is performed on the basis of the Leverage mathematical approach, in which the statistical Hat matrix, Williams Plot...... in exponential form is used to represent/predict the hydrate dissociation pressures for three-phase equilibrium conditions (liquid water/ice–vapor-hydrate). The investigated hydrate formers are methane, ethane, propane, carbon dioxide, nitrogen, and hydrogen sulfide. It is interpreted from the obtained results...
Cutting-edge statistical methods for a life-course approach.
Bub, Kristen L; Ferretti, Larissa K
2014-01-01
Advances in research methods, data collection and record keeping, and statistical software have substantially increased our ability to conduct rigorous research across the lifespan. In this article, we review a set of cutting-edge statistical methods that life-course researchers can use to rigorously address their research questions. For each technique, we describe the method, highlight the benefits and unique attributes of the strategy, offer a step-by-step guide on how to conduct the analysis, and illustrate the technique using data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development. In addition, we recommend a set of technical and empirical readings for each technique. Our goal was not to address a substantive question of interest but instead to provide life-course researchers with a useful reference guide to cutting-edge statistical methods.
Achieving Integration in Mixed Methods Designs—Principles and Practices
Fetters, Michael D; Curry, Leslie A; Creswell, John W
2013-01-01
Mixed methods research offers powerful tools for investigating complex processes and systems in health and health care. This article describes integration principles and practices at three levels in mixed methods research and provides illustrative examples. Integration at the study design level occurs through three basic mixed method designs—exploratory sequential, explanatory sequential, and convergent—and through four advanced frameworks—multistage, intervention, case study, and participato...
Mendoza Beltran, A.; Heijungs, R.; Guinée, J.; Tukker, A.
2016-01-01
Purpose: Despite efforts to treat uncertainty due to methodological choices in life cycle assessment (LCA) such as standardization, one-at-a-time (OAT) sensitivity analysis, and analytical and statistical methods, no method exists that propagate this source of uncertainty for all relevant processes
Statistical Analysis of a Method to Predict Drug-Polymer Miscibility
DEFF Research Database (Denmark)
Knopp, Matthias Manne; Olesen, Niels Erik; Huang, Yanbin
2016-01-01
In this study, a method proposed to predict drug-polymer miscibility from differential scanning calorimetry measurements was subjected to statistical analysis. The method is relatively fast and inexpensive and has gained popularity as a result of the increasing interest in the formulation of drug...... as provided in this study. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci....
animation : An R Package for Creating Animations and Demonstrating Statistical Methods
Directory of Open Access Journals (Sweden)
Yihui Xie
2013-04-01
Full Text Available Animated graphs that demonstrate statistical ideas and methods can both attract interest and assist understanding. In this paper we first discuss how animations can be related to some statistical topics such as iterative algorithms, random simulations, (resampling methods and dynamic trends, then we describe the approaches that may be used to create animations, and give an overview to the R package animation, including its design, usage and the statistical topics in the package. With the animation package, we can export the animations produced by R into a variety of formats, such as a web page, a GIF animation, a Flash movie, a PDF document, or an MP4/AVI video, so that users can publish the animations fairly easily. The design of this package is flexible enough to be readily incorporated into web applications, e.g., we can generate animations online with Rweb, which means we do not even need R to be installed locally to create animations. We will show examples of the use of animations in teaching statistics and in the presentation of statistical reports using Sweave or knitr. In fact, this paper itself was written with the knitr and animation package, and the animations are embedded in the PDF document, so that readers can watch the animations in real time when they read the paper (the Adobe Reader is required.Animations can add insight and interest to traditional static approaches to teaching statistics and reporting, making statistics a more interesting and appealing subject.
On nonequilibrium many-body systems. 1: The nonequilibrium statistical operator method
International Nuclear Information System (INIS)
Algarte, A.C.S.; Vasconcellos, A.R.; Luzzi, R.; Sampaio, A.J.C.
1985-01-01
The theoretical aspects involved in the treatment of many-body systems strongly departed from equilibrium are discussed. The nonequilibrium statistical operator (NSO) method is considered in detail. Using Jaynes' maximum entropy formalism complemented with an ad hoc hypothesis a nonequilibrium statistical operator is obtained. This approach introduces irreversibility from the outset and we recover statistical operators like those of Green-Mori and Zubarev as particular cases. The connection with Generalized Thermodynamics and the construction of nonlinear transport equations are briefly described. (Author) [pt
The choice of statistical methods for comparisons of dosimetric data in radiotherapy.
Chaikh, Abdulhamid; Giraud, Jean-Yves; Perrin, Emmanuel; Bresciani, Jean-Pierre; Balosso, Jacques
2014-09-18
Novel irradiation techniques are continuously introduced in radiotherapy to optimize the accuracy, the security and the clinical outcome of treatments. These changes could raise the question of discontinuity in dosimetric presentation and the subsequent need for practice adjustments in case of significant modifications. This study proposes a comprehensive approach to compare different techniques and tests whether their respective dose calculation algorithms give rise to statistically significant differences in the treatment doses for the patient. Statistical investigation principles are presented in the framework of a clinical example based on 62 fields of radiotherapy for lung cancer. The delivered doses in monitor units were calculated using three different dose calculation methods: the reference method accounts the dose without tissues density corrections using Pencil Beam Convolution (PBC) algorithm, whereas new methods calculate the dose with tissues density correction for 1D and 3D using Modified Batho (MB) method and Equivalent Tissue air ratio (ETAR) method, respectively. The normality of the data and the homogeneity of variance between groups were tested using Shapiro-Wilks and Levene test, respectively, then non-parametric statistical tests were performed. Specifically, the dose means estimated by the different calculation methods were compared using Friedman's test and Wilcoxon signed-rank test. In addition, the correlation between the doses calculated by the three methods was assessed using Spearman's rank and Kendall's rank tests. The Friedman's test showed a significant effect on the calculation method for the delivered dose of lung cancer patients (p Wilcoxon signed-rank test of paired comparisons indicated that the delivered dose was significantly reduced using density-corrected methods as compared to the reference method. Spearman's and Kendall's rank tests indicated a positive correlation between the doses calculated with the different methods
Integrated management of thesis using clustering method
Astuti, Indah Fitri; Cahyadi, Dedy
2017-02-01
Thesis is one of major requirements for student in pursuing their bachelor degree. In fact, finishing the thesis involves a long process including consultation, writing manuscript, conducting the chosen method, seminar scheduling, searching for references, and appraisal process by the board of mentors and examiners. Unfortunately, most of students find it hard to match all the lecturers' free time to sit together in a seminar room in order to examine the thesis. Therefore, seminar scheduling process should be on the top of priority to be solved. Manual mechanism for this task no longer fulfills the need. People in campus including students, staffs, and lecturers demand a system in which all the stakeholders can interact each other and manage the thesis process without conflicting their timetable. A branch of computer science named Management Information System (MIS) could be a breakthrough in dealing with thesis management. This research conduct a method called clustering to distinguish certain categories using mathematics formulas. A system then be developed along with the method to create a well-managed tool in providing some main facilities such as seminar scheduling, consultation and review process, thesis approval, assessment process, and also a reliable database of thesis. The database plays an important role in present and future purposes.
Fractional statistics and quantum scaling properties of the integrable Penson-Kolb-Hubbard chain
Vitoriano, Carlindo; Coutinho-Filho, M. D.
2010-09-01
We investigate the ground-state and low-temperature properties of the integrable version of the Penson-Kolb-Hubbard chain. The model obeys fractional statistical properties, which give rise to fractional elementary excitations and manifest differently in the four regions of the phase diagram U/t versus n , where U is the Coulomb coupling, t is the correlated hopping amplitude, and n is the particle density. In fact, we can find local pair formation, fractionalization of the average occupation number per orbital k , or U - and n -dependent average electric charge per orbital k . We also study the scaling behavior near the U -driven quantum phase transitions and characterize their universality classes. Finally, it is shown that in the regime of parameters where local pair formation is energetically more favorable, the ground state exhibits power-law superconductivity; we also stress that above half filling the pair-hopping term stabilizes local Cooper pairs in the repulsive- U regime for U
Directory of Open Access Journals (Sweden)
Wakako Umene-Nakano
Full Text Available In the present study, we aimed to investigate the difference in white matter between smokers and nonsmokers. In addition, we examined relationships between white matter integrity and nicotine dependence parameters in smoking subjects. Nineteen male smokers were enrolled in this study. Eighteen age-matched non-smokers with no current or past psychiatric history were included as controls. Diffusion tensor imaging scans were performed, and the analysis was conducted using a tract-based special statistics approach. Compared with nonsmokers, smokers exhibited a significant decrease in fractional anisotropy (FA throughout the whole corpus callosum. There were no significant differences in radial diffusivity or axial diffusivity between the two groups. There was a significant negative correlation between FA in the whole corpus callosum and the amount of tobacco use (cigarettes/day; R = - 0.580, p = 0.023. These results suggest that the corpus callosum may be one of the key areas influenced by chronic smoking.
Funk, Chris; Verdin, James P.; Husak, Gregory
2007-01-01
Famine early warning in Africa presents unique challenges and rewards. Hydrologic extremes must be tracked and anticipated over complex and changing climate regimes. The successful anticipation and interpretation of hydrologic shocks can initiate effective government response, saving lives and softening the impacts of droughts and floods. While both monitoring and forecast technologies continue to advance, discontinuities between monitoring and forecast systems inhibit effective decision making. Monitoring systems typically rely on high resolution satellite remote-sensed normalized difference vegetation index (NDVI) and rainfall imagery. Forecast systems provide information on a variety of scales and formats. Non-meteorologists are often unable or unwilling to connect the dots between these disparate sources of information. To mitigate these problem researchers at UCSB's Climate Hazard Group, NASA GIMMS and USGS/EROS are implementing a NASA-funded integrated decision support system that combines the monitoring of precipitation and NDVI with statistical one-to-three month forecasts. We present the monitoring/forecast system, assess its accuracy, and demonstrate its application in food insecure sub-Saharan Africa.
IMP: Integrated method for power analysis
Energy Technology Data Exchange (ETDEWEB)
1989-03-01
An integrated, easy to use, economical package of microcomputer programs has been developed which can be used by small hydro developers to evaluate potential sites for small scale hydroelectric plants in British Columbia. The programs enable evaluation of sites located far from the nearest stream gauging station, for which streamflow data are not available. For each of the province's 6 hydrologic regions, a streamflow record for one small watershed is provided in the data base. The program can then be used to generate synthetic streamflow records and to compare results obtained by the modelling procedure with the actual data. The program can also be used to explore the significance of modelling parameters and to develop a detailed appreciation for the accuracy which can be obtained under various circumstances. The components of the program are an atmospheric model of precipitation; a watershed model that will generate a continuous series of streamflow data, based on information from the atmospheric model; a flood frequency analysis system that uses site-specific topographic data plus information from the atmospheric model to generate a flood frequency curve; a hydroelectric power simulation program which determines daily energy output for a run-of-river or reservoir storage site based on selected generation facilities and the time series generated in the watershed model; and a graphic analysis package that provides direct visualization of data and modelling results. This report contains a description of the programs, a user guide, the theory behind the model, the modelling methodology, and results from a workshop that reviewed the program package. 32 refs., 16 figs., 18 tabs.
Raymond, Ogbuka Obinna
2017-01-01
In analyzing survey data, most researchers and analysts make use of statistical methods with straight forward statistical approaches. More common, is the use of one‐way, two‐way or multi‐way tables, and graphical displays such as bar charts, line charts, etc. A brief overview of these approaches and a good discussion on aspects needing attention during the data analysis process can be found in Wilson & Stern (2001). In most cases however, analysis procedures that go beyond simp...
International Nuclear Information System (INIS)
Murayama, Hideo; Tanaka, Eiichi; Toyama, Hinako.
1985-01-01
The weighted backprojection (WBP) method and the radial post-correction (RPC) method were compared with other several attenuation correction methods for single photon emission computed tomography by computer simulation. These methods are the pre-correction method with arithmetic means of opposing projections, the post-correction method with a correction matrix, and the inverse attenuated Randon transform method. Statistical mean square noise in a reconstructed image was formulated, and was displayed two-dimensionally for typical simulated phantoms. The noise image for the WBP method was dependent on several parameters, namely, size of an attenuating object, distribution of activity, the attenuation coefficient, and choise of the reconstruction index, k and position of the reconstruction origin. The noise image for the WBP method with k=0 was almost the same for the RPC method. It has been shown that position of the reconstruction origin has to be chosen appropriately in order to improve the noise properties of the reconstructed image for the WBP method as well as the RPC method. Comparision of the different attenuation correction methods accomplished by using both the reconstructed images and the statistical noise images with the same mathematical phantom and convolving function concluded that the WBP method and the RPC method were more amenable to any radioisotope distributions than the other methods, and had the advantage of flexibility to improve image noise of any local positions. (author)
Approximate calculation method for integral of mean square value of nonstationary response
International Nuclear Information System (INIS)
Aoki, Shigeru; Fukano, Azusa
2010-01-01
The response of the structure subjected to nonstationary random vibration such as earthquake excitation is nonstationary random vibration. Calculating method for statistical characteristics of such a response is complicated. Mean square value of the response is usually used to evaluate random response. Integral of mean square value of the response corresponds to total energy of the response. In this paper, a simplified calculation method to obtain integral of mean square value of the response is proposed. As input excitation, nonstationary white noise and nonstationary filtered white noise are used. Integrals of mean square value of the response are calculated for various values of parameters. It is found that the proposed method gives exact value of integral of mean square value of the response.
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; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van' t [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands)
2012-03-15
Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.
International Nuclear Information System (INIS)
Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van’t
2012-01-01
Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.
Deterministic methods to solve the integral transport equation in neutronic
International Nuclear Information System (INIS)
Warin, X.
1993-11-01
We present a synthesis of the methods used to solve the integral transport equation in neutronic. This formulation is above all used to compute solutions in 2D in heterogeneous assemblies. Three kinds of methods are described: - the collision probability method; - the interface current method; - the current coupling collision probability method. These methods don't seem to be the most effective in 3D. (author). 9 figs
New method for eliminating the statistical bias in highly turbulent flow measurements
International Nuclear Information System (INIS)
Nakao, S.I.; Terao, Y.; Hirata, K.I.; Kitakyushu Industrial Research Institute, Fukuoka, Japan)
1987-01-01
A simple method was developed for eliminating statistical bias which can be applied to highly turbulent flows with the sparse and nonuniform seeding conditions. Unlike the method proposed so far, a weighting function was determined based on the idea that the statistical bias could be eliminated if the asymmetric form of the probability density function of the velocity data were corrected. Moreover, the data more than three standard deviations away from the mean were discarded to remove the apparent turbulent intensity resulting from noise. The present method was applied to data obtained in the wake of a block, which provided local turbulent intensities up to about 120 percent, it was found to eliminate the statistical bias with high accuracy. 9 references
Mai, Lan-Yin; Li, Yi-Xuan; Chen, Yong; Xie, Zhen; Li, Jie; Zhong, Ming-Yu
2014-05-01
The compatibility of traditional Chinese medicines (TCMs) formulae containing enormous information, is a complex component system. Applications of mathematical statistics methods on the compatibility researches of traditional Chinese medicines formulae have great significance for promoting the modernization of traditional Chinese medicines and improving clinical efficacies and optimizations of formulae. As a tool for quantitative analysis, data inference and exploring inherent rules of substances, the mathematical statistics method can be used to reveal the working mechanisms of the compatibility of traditional Chinese medicines formulae in qualitatively and quantitatively. By reviewing studies based on the applications of mathematical statistics methods, this paper were summarized from perspective of dosages optimization, efficacies and changes of chemical components as well as the rules of incompatibility and contraindication of formulae, will provide the references for further studying and revealing the working mechanisms and the connotations of traditional Chinese medicines.
Statistical method on nonrandom clustering with application to somatic mutations in cancer
Directory of Open Access Journals (Sweden)
Rejto Paul A
2010-01-01
Full Text Available Abstract Background Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention. Results We propose a new statistical method for detecting activating mutations in cancer by identifying nonrandom clusters of amino acid mutations in protein sequences. A probability model is derived using order statistics assuming that the location of amino acid mutations on a protein follows a uniform distribution. Our statistical measure is the differences between pair-wise order statistics, which is equivalent to the size of an amino acid mutation cluster, and the probabilities are derived from exact and approximate distributions of the statistical measure. Using data in the Catalog of Somatic Mutations in Cancer (COSMIC database, we have demonstrated that our method detects well-known clusters of activating mutations in KRAS, BRAF, PI3K, and β-catenin. The method can also identify new cancer targets as well as gain-of-function mutations in tumor suppressors. Conclusions Our proposed method is useful to discover activating driver mutations in cancer by identifying nonrandom clusters of somatic amino acid mutations in protein sequences.
Statistics: a Bayesian perspective
National Research Council Canada - National Science Library
Berry, Donald A
1996-01-01
...: it is the only introductory textbook based on Bayesian ideas, it combines concepts and methods, it presents statistics as a means of integrating data into the significant process, it develops ideas...
Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A
2012-03-15
To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright Â© 2012 Elsevier Inc. All rights reserved.
Quadratic algebras in the noncommutative integration method of wave equation
International Nuclear Information System (INIS)
Varaksin, O.L.
1995-01-01
The paper deals with the investigation of applications of the method of noncommutative integration of linear differential equations by partial derivatives. Nontrivial example was taken for integration of three-dimensions wave equation with the use of non-Abelian quadratic algebras
Statistical and numerical methods to improve the transient divided bar method
DEFF Research Database (Denmark)
Bording, Thue Sylvester; Nielsen, S.B.; Balling, N.
The divided bar method is a commonly used method to measure thermal conductivity of rock samples in laboratory. We present improvements to this method that allows for simultaneous measurements of both thermal conductivity and thermal diffusivity. The divided bar setup is run in a transient mode...
Study on the Orion spiral arm structure by the statistical modelling method
International Nuclear Information System (INIS)
Basharina, T.S.; Pavlovskaya, E.D.; Filippova, A.A.
1980-01-01
A method of investigation of the spiral structure based on the statistical modelling methods is suggested. This method is used for the study of the Orion spiral arm. The maxima of density and the widths of the Orion arm in the direction of the areas considered for the longitude interval 55 deg - 187 deg are defined under the assumption of normal distribution of stars across the arm. The Sun is shown to be at the inner edge of the arm [ru
New method for calculation of integral characteristics of thermal plumes
DEFF Research Database (Denmark)
Zukowska, Daria; Popiolek, Zbigniew; Melikov, Arsen Krikor
2008-01-01
A method for calculation of integral characteristics of thermal plumes is proposed. The method allows for determination of the integral parameters of plumes based on speed measurements performed with omnidirectional low velocity thermoanemometers. The method includes a procedure for calculation...... of the directional velocity (upward component of the mean velocity). The method is applied for determination of the characteristics of an asymmetric thermal plume generated by a sitting person. The method was validated in full-scale experiments in a climatic chamber with a thermal manikin as a simulator of a sitting...
INTEGRATED FUSION METHOD FOR MULTIPLE TEMPORAL-SPATIAL-SPECTRAL IMAGES
Directory of Open Access Journals (Sweden)
H. Shen
2012-08-01
Full Text Available Data fusion techniques have been widely researched and applied in remote sensing field. In this paper, an integrated fusion method for remotely sensed images is presented. Differently from the existed methods, the proposed method has the performance to integrate the complementary information in multiple temporal-spatial-spectral images. In order to represent and process the images in one unified framework, two general image observation models are firstly presented, and then the maximum a posteriori (MAP framework is used to set up the fusion model. The gradient descent method is employed to solve the fused image. The efficacy of the proposed method is validated using simulated images.
International Nuclear Information System (INIS)
Vidal-Codina, F.; Nguyen, N.C.; Giles, M.B.; Peraire, J.
2015-01-01
We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method
The Integrated Medical Model: Statistical Forecasting of Risks to Crew Health and Mission Success
Fitts, M. A.; Kerstman, E.; Butler, D. J.; Walton, M. E.; Minard, C. G.; Saile, L. G.; Toy, S.; Myers, J.
2008-01-01
The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions
Alternative containment integrity test methods, an overview of possible techniques
International Nuclear Information System (INIS)
Spletzer, B.L.
1986-01-01
A study is being conducted to develop and analyze alternative methods for testing of containment integrity. The study is focused on techniques for continuously monitoring containment integrity to provide rapid detection of existing leaks, thus providing greater certainty of the integrity of the containment at any time. The study is also intended to develop techniques applicable to the currently required Type A integrated leakage rate tests. A brief discussion of the range of alternative methods currently being considered is presented. The methods include applicability to all major containment types, operating and shutdown plant conditions, and quantitative and qualitative leakage measurements. The techniques are analyzed in accordance with the current state of knowledge of each method. The bulk of the techniques discussed are in the conceptual stage, have not been tested in actual plant conditions, and are presented here as a possible future direction for evaluating containment integrity. Of the methods considered, no single method provides optimum performance for all containment types. Several methods are limited in the types of containment for which they are applicable. The results of the study to date indicate that techniques for continuous monitoring of containment integrity exist for many plants and may be implemented at modest cost
Microvariability in AGNs: study of different statistical methods - I. Observational analysis
Zibecchi, L.; Andruchow, I.; Cellone, S. A.; Carpintero, D. D.; Romero, G. E.; Combi, J. A.
2017-05-01
We present the results of a study of different statistical methods currently used in the literature to analyse the (micro)variability of active galactic nuclei (AGNs) from ground-based optical observations. In particular, we focus on the comparison between the results obtained by applying the so-called C and F statistics, which are based on the ratio of standard deviations and variances, respectively. The motivation for this is that the implementation of these methods leads to different and contradictory results, making the variability classification of the light curves of a certain source dependent on the statistics implemented. For this purpose, we re-analyse the results on an AGN sample observed along several sessions with the 2.15 m 'Jorge Sahade' telescope (CASLEO), San Juan, Argentina. For each AGN, we constructed the nightly differential light curves. We thus obtained a total of 78 light curves for 39 AGNs, and we then applied the statistical tests mentioned above, in order to re-classify the variability state of these light curves and in an attempt to find the suitable statistical methodology to study photometric (micro)variations. We conclude that, although the C criterion is not proper a statistical test, it could still be a suitable parameter to detect variability and that its application allows us to get more reliable variability results, in contrast with the F test.
QSPR Study of the Retention/release Property of Odorant Molecules in Water Using Statistical Methods
Directory of Open Access Journals (Sweden)
Assia Belhassan
2017-10-01
Full Text Available An integrated approach physicochemistry and structures property relationships has been carried out to study the odorant molecules retention/release phenomenon in the water. This study aimed to identify the molecular properties (molecular descriptors that govern this phenomenon assuming that modifying the structure leads automatically to a change in the retention/release property of odorant molecules. ACD/ChemSketch, MarvinSketch, and ChemOffice programs were used to calculate several molecular descriptors of 51 odorant molecules (15 alcohols, 11 aldehydes, 9 ketones and 16 esters. A total of 37 molecules (2/3 of the data set were placed in the training set to build the QSPR models, whereas the remaining, 14 molecules (1/3 of the data set constitute the test set. The best descriptors were selected to establish the quantitative structure property relationship (QSPR of the retention/release property of odorant molecules in water using multiple linear regression (MLR, multiple non-linear regression (MNLR and an artificial neural network (ANN methods. We propose a quantitative model according to these analyses. The models were used to predict the retention/release property of the test set compounds, and agreement between the experimental and predicted values was verified. The descriptors showed by QSPR study are used for study and designing of new compounds. The statistical results indicate that the predicted values are in good agreement with the experimental results. To validate the predictive power of the resulting models, external validation multiple correlation coefficient was calculated and has both in addition to a performant prediction power, a favorable estimation of stability. DOI: http://dx.doi.org/10.17807/orbital.v9i4.978
Two pricing methods for solving an integrated commercial fishery ...
African Journals Online (AJOL)
a model (Hasan and Raffensperger, 2006) to solve this problem: the integrated ... planning and labour allocation for that processing firm, but did not consider any fleet- .... the DBONP method actually finds such price information, and uses it.
Critical Analysis of Methods for Integrating Economic and Environmental Indicators
Huguet Ferran, Pau; Heijungs, Reinout; Vogtländer, Joost G.
2018-01-01
The application of environmental strategies requires scoring and evaluation methods that provide an integrated vision of the economic and environmental performance of systems. The vector optimisation, ratio and weighted addition of indicators are the three most prevalent techniques for addressing
A simple flow-concentration modelling method for integrating water ...
African Journals Online (AJOL)
A simple flow-concentration modelling method for integrating water quality and ... flow requirements are assessed for maintenance low flow, drought low flow ... the instream concentrations of chemical constituents that will arise from different ...
APPLICATION OF BOUNDARY INTEGRAL EQUATION METHOD FOR THERMOELASTICITY PROBLEMS
Directory of Open Access Journals (Sweden)
Vorona Yu.V.
2015-12-01
Full Text Available Boundary Integral Equation Method is used for solving analytically the problems of coupled thermoelastic spherical wave propagation. The resulting mathematical expressions coincide with the solutions obtained in a conventional manner.
Statistical approach for selection of regression model during validation of bioanalytical method
Directory of Open Access Journals (Sweden)
Natalija Nakov
2014-06-01
Full Text Available The selection of an adequate regression model is the basis for obtaining accurate and reproducible results during the bionalytical method validation. Given the wide concentration range, frequently present in bioanalytical assays, heteroscedasticity of the data may be expected. Several weighted linear and quadratic regression models were evaluated during the selection of the adequate curve fit using nonparametric statistical tests: One sample rank test and Wilcoxon signed rank test for two independent groups of samples. The results obtained with One sample rank test could not give statistical justification for the selection of linear vs. quadratic regression models because slight differences between the error (presented through the relative residuals were obtained. Estimation of the significance of the differences in the RR was achieved using Wilcoxon signed rank test, where linear and quadratic regression models were treated as two independent groups. The application of this simple non-parametric statistical test provides statistical confirmation of the choice of an adequate regression model.
New Approaches to Aluminum Integral Foam Production with Casting Methods
Directory of Open Access Journals (Sweden)
Ahmet Güner
2015-08-01
Full Text Available Integral foam has been used in the production of polymer materials for a long time. Metal integral foam casting systems are obtained by transferring and adapting polymer injection technology. Metal integral foam produced by casting has a solid skin at the surface and a foam core. Producing near-net shape reduces production expenses. Insurance companies nowadays want the automotive industry to use metallic foam parts because of their higher impact energy absorption properties. In this paper, manufacturing processes of aluminum integral foam with casting methods will be discussed.