Quality assurance and applied statistics. Method 3
International Nuclear Information System (INIS)
1992-01-01
This German-Industry-Standards-paperback contains the International Standards from the Series ISO 9000 (or, as the case may be, the European Standards from the Series EN 29000) concerning quality assurance and including the already completed supplementary guidelines with ISO 9000- and ISO 9004-section numbers, which have been adopted as German Industry Standards and which are observed and applied world-wide to a great extent. It also includes the German-Industry-Standards ISO 10011 parts 1, 2 and 3 concerning the auditing of quality-assurance systems and the German-Industry-Standard ISO 10012 part 1 concerning quality-assurance demands (confirmation system) for measuring devices. The standards also include English and French versions. They are applicable independent of the user's line of industry and thus constitute basic standards. (orig.) [de
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...
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.
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.
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.
Applying contemporary statistical techniques
Wilcox, Rand R
2003-01-01
Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible.* Assumes no previous training in statistics * Explains how and why modern statistical methods provide more accurate results than conventional methods* Covers the latest developments on multiple comparisons * Includes recent advanc
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
Applied statistics for economists
Lewis, Margaret
2012-01-01
This book is an undergraduate text that introduces students to commonly-used statistical methods in economics. Using examples based on contemporary economic issues and readily-available data, it not only explains the mechanics of the various methods, it also guides students to connect statistical results to detailed economic interpretations. Because the goal is for students to be able to apply the statistical methods presented, online sources for economic data and directions for performing each task in Excel are also included.
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.
Applied statistical thermodynamics
Lucas, Klaus
1991-01-01
The book guides the reader from the foundations of statisti- cal thermodynamics including the theory of intermolecular forces to modern computer-aided applications in chemical en- gineering and physical chemistry. The approach is new. The foundations of quantum and statistical mechanics are presen- ted in a simple way and their applications to the prediction of fluid phase behavior of real systems are demonstrated. A particular effort is made to introduce the reader to expli- cit formulations of intermolecular interaction models and to show how these models influence the properties of fluid sy- stems. The established methods of statistical mechanics - computer simulation, perturbation theory, and numerical in- tegration - are discussed in a style appropriate for newcom- ers and are extensively applied. Numerous worked examples illustrate how practical calculations should be carried out.
Huizingh, Eelko K. R. E.
2007-01-01
Accessibly written and easy to use, "Applied Statistics Using SPSS" is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. What is unique about Eelko Huizingh's approach is that this book is based around the needs of undergraduate students embarking on their own research project, and its self-help style is designed to…
Stolzer, Alan J.; Halford, Carl
2007-01-01
In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.
International Nuclear Information System (INIS)
Brodsky, A.
1979-01-01
Some recent reports of Mancuso, Stewart and Kneale claim findings of radiation-produced cancer in the Hanford worker population. These claims are based on statistical computations that use small differences in accumulated exposures between groups dying of cancer and groups dying of other causes; actual mortality and longevity were not reported. This paper presents a statistical method for evaluation of actual mortality and longevity longitudinally over time, as applied in a primary analysis of the mortality experience of the Hanford worker population. Although available, this method was not utilized in the Mancuso-Stewart-Kneale paper. The author's preliminary longitudinal analysis shows that the gross mortality experience of persons employed at Hanford during 1943-70 interval did not differ significantly from that of certain controls, when both employees and controls were selected from families with two or more offspring and comparison were matched by age, sex, race and year of entry into employment. This result is consistent with findings reported by Sanders (Health Phys. vol.35, 521-538, 1978). The method utilizes an approximate chi-square (1 D.F.) statistic for testing population subgroup comparisons, as well as the cumulation of chi-squares (1 D.F.) for testing the overall result of a particular type of comparison. The method is available for computer testing of the Hanford mortality data, and could also be adapted to morbidity or other population studies. (author)
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
International Nuclear Information System (INIS)
Suzuki, Mitsutoshi; Hori, Masato; Asou, Ryoji; Usuda, Shigekazu
2006-01-01
The multiscale statistical process control (MSSPC) method is applied to clarify the elements of material unaccounted for (MUF) in large scale reprocessing plants using numerical calculations. Continuous wavelet functions are used to decompose the process data, which simulate batch operation superimposed by various types of disturbance, and the disturbance components included in the data are divided into time and frequency spaces. The diagnosis of MSSPC is applied to distinguish abnormal events from the process data and shows how to detect abrupt and protracted diversions using principle component analysis. Quantitative performance of MSSPC for the time series data is shown with average run lengths given by Monte-Carlo simulation to compare to the non-detection probability β. Recent discussion about bias corrections in material balances is introduced and another approach is presented to evaluate MUF without assuming the measurement error model. (author)
The reduction method of statistic scale applied to study of climatic change
International Nuclear Information System (INIS)
Bernal Suarez, Nestor Ricardo; Molina Lizcano, Alicia; Martinez Collantes, Jorge; Pabon Jose Daniel
2000-01-01
In climate change studies the global circulation models of the atmosphere (GCMAs) enable one to simulate the global climate, with the field variables being represented on a grid points 300 km apart. One particular interest concerns the simulation of possible changes in rainfall and surface air temperature due to an assumed increase of greenhouse gases. However, the models yield the climatic projections on grid points that in most cases do not correspond to the sites of major interest. To achieve local estimates of the climatological variables, methods like the one known as statistical down scaling are applied. In this article we show a case in point by applying canonical correlation analysis (CCA) to the Guajira Region in the northeast of Colombia
Non-parametric order statistics method applied to uncertainty propagation in fuel rod calculations
International Nuclear Information System (INIS)
Arimescu, V.E.; Heins, L.
2001-01-01
method, which is computationally efficient, is presented for the evaluation of the global statement. It is proved that, r, the expected fraction of fuel rods exceeding a certain limit is equal to the (1-r)-quantile of the overall distribution of all possible values from all fuel rods. In this way, the problem is reduced to that of estimating a certain quantile of the overall distribution, and the same techniques used for a single rod distribution can be applied again. A simplified test case was devised to verify and validate the methodology. The fuel code was replaced by a transfer function dependent on two input parameters. The function was chosen so that analytic results could be obtained for the distribution of the output. This offers a direct validation for the statistical procedure. Also, a sensitivity study has been performed to analyze the effect on the final outcome of the sampling procedure, simple Monte Carlo and Latin Hypercube Sampling. Also, the effect on the accuracy and bias of the statistical results due to the size of the sample was studied and the conclusion was reached that the results of the statistical methodology are typically conservative. In the end, an example of applying these statistical techniques to a PWR reload is presented together with the improvements and new insights the statistical methodology brings to fuel rod design calculations. (author)
Kowalski, Jeanne
2008-01-01
A timely and applied approach to the newly discovered methods and applications of U-statisticsBuilt on years of collaborative research and academic experience, Modern Applied U-Statistics successfully presents a thorough introduction to the theory of U-statistics using in-depth examples and applications that address contemporary areas of study including biomedical and psychosocial research. Utilizing a "learn by example" approach, this book provides an accessible, yet in-depth, treatment of U-statistics, as well as addresses key concepts in asymptotic theory by integrating translational and cross-disciplinary research.The authors begin with an introduction of the essential and theoretical foundations of U-statistics such as the notion of convergence in probability and distribution, basic convergence results, stochastic Os, inference theory, generalized estimating equations, as well as the definition and asymptotic properties of U-statistics. With an emphasis on nonparametric applications when and where applic...
Applied multivariate statistical analysis
Härdle, Wolfgang Karl
2015-01-01
Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added. All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior. All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...
Principles of applied statistics
National Research Council Canada - National Science Library
Cox, D. R; Donnelly, Christl A
2011-01-01
.... David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation...
Statistical methods applied to gamma-ray spectroscopy algorithms in nuclear security missions.
Fagan, Deborah K; Robinson, Sean M; Runkle, Robert C
2012-10-01
Gamma-ray spectroscopy is a critical research and development priority to a range of nuclear security missions, specifically the interdiction of special nuclear material involving the detection and identification of gamma-ray sources. We categorize existing methods by the statistical methods on which they rely and identify methods that have yet to be considered. Current methods estimate the effect of counting uncertainty but in many cases do not address larger sources of decision uncertainty, which may be significantly more complex. Thus, significantly improving algorithm performance may require greater coupling between the problem physics that drives data acquisition and statistical methods that analyze such data. Untapped statistical methods, such as Bayes Modeling Averaging and hierarchical and empirical Bayes methods, could reduce decision uncertainty by rigorously and comprehensively incorporating all sources of uncertainty. Application of such methods should further meet the needs of nuclear security missions by improving upon the existing numerical infrastructure for which these analyses have not been conducted. Copyright © 2012 Elsevier Ltd. All rights reserved.
Window least squares method applied to statistical noise smoothing of positron annihilation data
International Nuclear Information System (INIS)
Adam, G.; Adam, S.; Barbiellini, B.; Hoffmann, L.; Manuel, A.A.; Peter, M.
1993-06-01
The paper deals with the off-line processing of experimental data obtained by two-dimensional angular correlation of the electron-positron annihilation radiation (2D-ACAR) technique on high-temperature superconductors. A piecewise continuous window least squares (WLS) method devoted to the statistical noise smoothing of 2D-ACAR data, under close control of the crystal reciprocal lattice periodicity, is derived. Reliability evaluation of the constant local weight WLS smoothing formula (CW-WLSF) shows that consistent processing 2D-ACAR data by CW-WLSF is possible. CW-WLSF analysis of 2D-ACAR data collected on untwinned Y Ba 2 Cu 3 O 7-δ single crystals yields significantly improved signature of the Fermi surface ridge at second Umklapp processes and resolves, for the first time, the ridge signature at third Umklapp processes. (author). 24 refs, 9 figs
Statistical methods for quantitative indicators of impacts, applied to transmission line projects
International Nuclear Information System (INIS)
Ospina Norena, Jesus Efren; Lema Tapias, Alvaro de Jesus
2005-01-01
Multivariate statistical analyses are proposed for encountering the relationships between variables and impacts, to obtain high explanatory power for interpretation of the causes and effects and achieve the highest certainty possible, to evaluate and classify impacts by their level of influence
International Nuclear Information System (INIS)
Peluso, E; Gelfusa, M; Gaudio, P; Murari, A
2014-01-01
Access to the H mode of confinement in tokamaks is characterized by an abrupt transition, which has been the subject of continuous investigation for decades. Various theoretical models have been developed and multi-machine databases of experimental data have been collected. In this paper, a new methodology is reviewed for the investigation of the scaling laws for the temperature threshold to access the H mode. The approach is based on symbolic regression via genetic programming and allows first the extraction of the most statistically reliable models from the available experimental data. Nonlinear fitting is then applied to the mathematical expressions found by symbolic regression; this second step permits to easily compare the quality of the data-driven scalings with the most widely accepted theoretical models. The application of a complete set of statistical indicators shows that the data-driven scaling laws are qualitatively better than the theoretical models. The main limitations of the theoretical models are that they are all expressed as power laws, which are too rigid to fit the available experimental data and to extrapolate to ITER. The proposed method is absolutely general and can be applied to the extraction or scaling law from any experimental database of sufficient statistical relevance. (paper)
Applied multivariate statistics with R
Zelterman, Daniel
2015-01-01
This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays, linear algebra, univariate, bivariate and multivariate normal distributions, factor methods, linear regression, discrimination and classification, clustering, time series models, and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the B...
Applied Behavior Analysis and Statistical Process Control?
Hopkins, B. L.
1995-01-01
Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…
Applied statistics for social and management sciences
Miah, Abdul Quader
2016-01-01
This book addresses the application of statistical techniques and methods across a wide range of disciplines. While its main focus is on the application of statistical methods, theoretical aspects are also provided as fundamental background information. It offers a systematic interpretation of results often discovered in general descriptions of methods and techniques such as linear and non-linear regression. SPSS is also used in all the application aspects. The presentation of data in the form of tables and graphs throughout the book not only guides users, but also explains the statistical application and assists readers in interpreting important features. The analysis of statistical data is presented consistently throughout the text. Academic researchers, practitioners and other users who work with statistical data will benefit from reading Applied Statistics for Social and Management Sciences. .
APPLIED STATISTICS – THE STATE AND THE PROSPECTS
Orlov A. I.
2016-01-01
Applied Statistics - the science of how to analyze the statistical data. As an independent scientificpractical area it develops very quickly. It includes numerous widely and deeply developed scientific directions. Those who use the applied statistics and other statistical methods, usually focused on specific areas of study, ie, are not specialists in applied statistics. Therefore, it is useful to make a critical analysis of the current state of applied statistics and discuss trends in the dev...
Ohyanagi, S.; Dileonardo, C.
2013-12-01
As a natural phenomenon earthquake occurrence is difficult to predict. Statistical analysis of earthquake data was performed using candlestick chart and Bollinger Band methods. These statistical methods, commonly used in the financial world to analyze market trends were tested against earthquake data. Earthquakes above Mw 4.0 located on shore of Sanriku (37.75°N ~ 41.00°N, 143.00°E ~ 144.50°E) from February 1973 to May 2013 were selected for analysis. Two specific patterns in earthquake occurrence were recognized through the analysis. One is a spread of candlestick prior to the occurrence of events greater than Mw 6.0. A second pattern shows convergence in the Bollinger Band, which implies a positive or negative change in the trend of earthquakes. Both patterns match general models for the buildup and release of strain through the earthquake cycle, and agree with both the characteristics of the candlestick chart and Bollinger Band analysis. These results show there is a high correlation between patterns in earthquake occurrence and trend analysis by these two statistical methods. The results of this study agree with the appropriateness of the application of these financial analysis methods to the analysis of earthquake occurrence.
Applying Statistical Mechanics to pixel detectors
International Nuclear Information System (INIS)
Pindo, Massimiliano
2002-01-01
Pixel detectors, being made of a large number of active cells of the same kind, can be considered as significant sets to which Statistical Mechanics variables and methods can be applied. By properly redefining well known statistical parameters in order to let them match the ones that actually characterize pixel detectors, an analysis of the way they work can be performed in a totally new perspective. A deeper understanding of pixel detectors is attained, helping in the evaluation and comparison of their intrinsic characteristics and performance
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
Directory of Open Access Journals (Sweden)
Kuo Zhang
2018-01-01
Full Text Available The mechanisms of acupuncture are still unclear. In order to reveal the regulatory effect of manual acupuncture (MA on the neuroendocrine-immune (NEI network and identify the key signaling molecules during MA modulating NEI network, we used a rat complete Freund’s adjuvant (CFA model to observe the analgesic and anti-inflammatory effect of MA, and, what is more, we used statistical and complex network methods to analyze the data about the expression of 55 common signaling molecules of NEI network in ST36 (Zusanli acupoint, and serum and hind foot pad tissue. The results indicate that MA had significant analgesic, anti-inflammatory effects on CFA rats; the key signaling molecules may play a key role during MA regulating NEI network, but further research is needed.
Energy Technology Data Exchange (ETDEWEB)
Kraut, W. [Duale Hochschule Baden-Wuerttemberg (DHBW), Karlsruhe (Germany). Studiengang Sicherheitswesen
2016-07-01
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.
Topics in theoretical and applied statistics
Giommi, Andrea
2016-01-01
This book highlights the latest research findings from the 46th International Meeting of the Italian Statistical Society (SIS) in Rome, during which both methodological and applied statistical research was discussed. This selection of fully peer-reviewed papers, originally presented at the meeting, addresses a broad range of topics, including the theory of statistical inference; data mining and multivariate statistical analysis; survey methodologies; analysis of social, demographic and health data; and economic statistics and econometrics.
von Larcher, Thomas; Blome, Therese; Klein, Rupert; Schneider, Reinhold; Wolf, Sebastian; Huber, Benjamin
2016-04-01
Handling high-dimensional data sets like they occur e.g. in turbulent flows or in multiscale behaviour of certain types in Geosciences are one of the big challenges in numerical analysis and scientific computing. A suitable solution is to represent those large data sets in an appropriate compact form. In this context, tensor product decomposition methods currently emerge as an important tool. One reason is that these methods often enable one to attack high-dimensional problems successfully, another that they allow for very compact representations of large data sets. We follow the novel Tensor-Train (TT) decomposition method to support the development of improved understanding of the multiscale behavior and the development of compact storage schemes for solutions of such problems. One long-term goal of the project is the construction of a self-consistent closure for Large Eddy Simulations (LES) of turbulent flows that explicitly exploits the tensor product approach's capability of capturing self-similar structures. Secondly, we focus on a mixed deterministic-stochastic subgrid scale modelling strategy currently under development for application in Finite Volume Large Eddy Simulation (LES) codes. Advanced methods of time series analysis for the databased construction of stochastic models with inherently non-stationary statistical properties and concepts of information theory based on a modified Akaike information criterion and on the Bayesian information criterion for the model discrimination are used to construct surrogate models for the non-resolved flux fluctuations. Vector-valued auto-regressive models with external influences form the basis for the modelling approach [1], [2], [4]. Here, we present the reconstruction capabilities of the two modeling approaches tested against 3D turbulent channel flow data computed by direct numerical simulation (DNS) for an incompressible, isothermal fluid at Reynolds number Reτ = 590 (computed by [3]). References [1] I
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
International Nuclear Information System (INIS)
Pirkle, F.L.
1981-04-01
STAARS is a new series which is being published to disseminate information concerning statistical procedures for interpreting aerial radiometric data. The application of a particular data interpretation technique to geologic understanding for delineating regions favorable to uranium deposition is the primary concern of STAARS. Statements concerning the utility of a technique on aerial reconnaissance data as well as detailed aerial survey data will be included
Applied matrix algebra in the statistical sciences
Basilevsky, Alexander
2005-01-01
This comprehensive text offers teachings relevant to both applied and theoretical branches of matrix algebra and provides a bridge between linear algebra and statistical models. Appropriate for advanced undergraduate and graduate students. 1983 edition.
2015 ICSA/Graybill Applied Statistics Symposium
Wang, Bushi; Hu, Xiaowen; Chen, Kun; Liu, Ray
2016-01-01
The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins. The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. Each papers was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. Focuses on statistical applications from clinical trials, biomarker analysis, and personalized medicine to applications in finance and business analytics A unique selection of papers from broad and multi-disciplinary critical hot topics - from academic, government, and industry perspectives - to appeal to a wide variety of applied research interests All papers feature origina...
SPSS for applied sciences basic statistical testing
Davis, Cole
2013-01-01
This book offers a quick and basic guide to using SPSS and provides a general approach to solving problems using statistical tests. It is both comprehensive in terms of the tests covered and the applied settings it refers to, and yet is short and easy to understand. Whether you are a beginner or an intermediate level test user, this book will help you to analyse different types of data in applied settings. It will also give you the confidence to use other statistical software and to extend your expertise to more specific scientific settings as required.The author does not use mathematical form
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...
Modern applied statistics with S-plus
Venables, W N
1994-01-01
S-Plus is a powerful environment for statistical and graphical analysis of data. It provides the tools to implement many statistical ideas which have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S-Plus to perform statistical analyses and provides both an introduction to the use of S-Plus and a course in modern statistical methods. The aim of the book is to show how to use S-Plus as a powerful and graphical system. Readers are assumed to have a basic grounding in statistics, and so the book is intended for would-be users of S-Plus, and both students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets.
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 ...
Applied Statistics Using SPSS, STATISTICA, MATLAB and R
De Sá, Joaquim P Marques
2007-01-01
This practical reference provides a comprehensive introduction and tutorial on the main statistical analysis topics, demonstrating their solution with the most common software package. Intended for anyone needing to apply statistical analysis to a large variety of science and enigineering problems, the book explains and shows how to use SPSS, MATLAB, STATISTICA and R for analysis such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. It concisely explains key concepts and methods, illustrated by practical examp
Studies in Theoretical and Applied Statistics
Pratesi, Monica; Ruiz-Gazen, Anne
2018-01-01
This book includes a wide selection of the papers presented at the 48th Scientific Meeting of the Italian Statistical Society (SIS2016), held in Salerno on 8-10 June 2016. Covering a wide variety of topics ranging from modern data sources and survey design issues to measuring sustainable development, it provides a comprehensive overview of the current Italian scientific research in the fields of open data and big data in public administration and official statistics, survey sampling, ordinal and symbolic data, statistical models and methods for network data, time series forecasting, spatial analysis, environmental statistics, economic and financial data analysis, statistics in the education system, and sustainable development. Intended for researchers interested in theoretical and empirical issues, this volume provides interesting starting points for further research.
Applied statistics a handbook of BMDP analyses
Snell, E J
1987-01-01
This handbook is a realization of a long term goal of BMDP Statistical Software. As the software supporting statistical analysis has grown in breadth and depth to the point where it can serve many of the needs of accomplished statisticians it can also serve as an essential support to those needing to expand their knowledge of statistical applications. Statisticians should not be handicapped by heavy computation or by the lack of needed options. When Applied Statistics, Principle and Examples by Cox and Snell appeared we at BMDP were impressed with the scope of the applications discussed and felt that many statisticians eager to expand their capabilities in handling such problems could profit from having the solutions carried further, to get them started and guided to a more advanced level in problem solving. Who would be better to undertake that task than the authors of Applied Statistics? A year or two later discussions with David Cox and Joyce Snell at Imperial College indicated that a wedding of the proble...
Modern applied statistics with s-plus
Venables, W N
1997-01-01
S-PLUS is a powerful environment for the statistical and graphical analysis of data. It provides the tools to implement many statistical ideas which have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S-PLUS to perform statistical analyses and provides both an introduction to the use of S-PLUS and a course in modern statistical methods. S-PLUS is available for both Windows and UNIX workstations, and both versions are covered in depth. The aim of the book is to show how to use S-PLUS as a powerful and graphical system. Readers are assumed to have a basic grounding in statistics, and so the book is intended for would-be users of S-PLUS, and both students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets. Many of the methods discussed are state-of-the-art approaches to topics such as linear and non-linear regression models, robust a...
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...
Applied statistics for civil and environmental engineers
Kottegoda, N T
2009-01-01
Civil and environmental engineers need an understanding of mathematical statistics and probability theory to deal with the variability that affects engineers'' structures, soil pressures, river flows and the like. Students, too, need to get to grips with these rather difficult concepts.This book, written by engineers for engineers, tackles the subject in a clear, up-to-date manner using a process-orientated approach. It introduces the subjects of mathematical statistics and probability theory, and then addresses model estimation and testing, regression and multivariate methods, analysis of extreme events, simulation techniques, risk and reliability, and economic decision making.325 examples and case studies from European and American practice are included and each chapter features realistic problems to be solved.For the second edition new sections have been added on Monte Carlo Markov chain modeling with details of practical Gibbs sampling, sensitivity analysis and aleatory and epistemic uncertainties, and co...
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.)
Applied statistical designs for the researcher
Paulson, Daryl S
2003-01-01
Research and Statistics Basic Review of Parametric Statistics Exploratory Data Analysis Two Sample Tests Completely Randomized One-Factor Analysis of Variance One and Two Restrictions on Randomization Completely Randomized Two-Factor Factorial Designs Two-Factor Factorial Completely Randomized Blocked Designs Useful Small Scale Pilot Designs Nested Statistical Designs Linear Regression Nonparametric Statistics Introduction to Research Synthesis and "Meta-Analysis" and Conclusory Remarks References Index.
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 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
Quantum mechanics as applied mathematical statistics
International Nuclear Information System (INIS)
Skala, L.; Cizek, J.; Kapsa, V.
2011-01-01
Basic mathematical apparatus of quantum mechanics like the wave function, probability density, probability density current, coordinate and momentum operators, corresponding commutation relation, Schroedinger equation, kinetic energy, uncertainty relations and continuity equation is discussed from the point of view of mathematical statistics. It is shown that the basic structure of quantum mechanics can be understood as generalization of classical mechanics in which the statistical character of results of measurement of the coordinate and momentum is taken into account and the most important general properties of statistical theories are correctly respected.
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)
Applied Bayesian hierarchical methods
National Research Council Canada - National Science Library
Congdon, P
2010-01-01
... . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Posterior Inference from Bayes Formula . . . . . . . . . . . . 1.3 Markov Chain Monte Carlo Sampling in Relation to Monte Carlo Methods: Obtaining Posterior...
Methods of applied mathematics
Hildebrand, Francis B
1992-01-01
This invaluable book offers engineers and physicists working knowledge of a number of mathematical facts and techniques not commonly treated in courses in advanced calculus, but nevertheless extremely useful when applied to typical problems in many different fields. It deals principally with linear algebraic equations, quadratic and Hermitian forms, operations with vectors and matrices, the calculus of variations, and the formulations and theory of linear integral equations. Annotated problems and exercises accompany each chapter.
Applied statistics for economics and business
Özdemir, Durmuş
2016-01-01
This textbook introduces readers to practical statistical issues by presenting them within the context of real-life economics and business situations. It presents the subject in a non-threatening manner, with an emphasis on concise, easily understandable explanations. It has been designed to be accessible and student-friendly and, as an added learning feature, provides all the relevant data required to complete the accompanying exercises and computing problems, which are presented at the end of each chapter. It also discusses index numbers and inequality indices in detail, since these are of particular importance to students and commonly omitted in textbooks. Throughout the text it is assumed that the student has no prior knowledge of statistics. It is aimed primarily at business and economics undergraduates, providing them with the basic statistical skills necessary for further study of their subject. However, students of other disciplines will also find it relevant.
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...
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
Applied statistics for business and economics
Leekley, Robert M
2010-01-01
While there are numerous texts on the market with the same goal, this text takes a practical and effective approach to engaging students with a topic that, as the author notes, they are most likely not that interested in learning. The text accomplishes this goal quite well. … It is written in a very straightforward and understandable manner that fits its intended audience quite well. … Given that there are dozens of introductory statistics texts on the market. it has become exceedingly difficult to create one that can be truly differentiated from the rest. However, in this case, the author app
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
Topics in mathematical and applied statistics
Pas, van der S.L.
2017-01-01
This thesis is composed of papers on four topics: Bayesian theory for the sparse normal means problem, specifically for the horseshoe prior (Chapters 1-3), Bayesian theory for community detection (Chapter 4), nested model selection (Chapter 5), and the application of competing risk methods in the
Applied statistics for agriculture, veterinary, fishery, dairy and allied fields
Sahu, Pradip Kumar
2016-01-01
This book is aimed at a wide range of readers who lack confidence in the mathematical and statistical sciences, particularly in the fields of Agriculture, Veterinary, Fishery, Dairy and other related areas. Its goal is to present the subject of statistics and its useful tools in various disciplines in such a manner that, after reading the book, readers will be equipped to apply the statistical tools to extract otherwise hidden information from their data sets with confidence. Starting with the meaning of statistics, the book introduces measures of central tendency, dispersion, association, sampling methods, probability, inference, designs of experiments and many other subjects of interest in a step-by-step and lucid manner. The relevant theories are described in detail, followed by a broad range of real-world worked-out examples, solved either manually or with the help of statistical packages. In closing, the book also includes a chapter on which statistical packages to use, depending on the user’s respecti...
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...
Bordogna, Clelia María; Albano, Ezequiel V.
2007-02-01
The aim of this paper is twofold. On the one hand we present a brief overview on the application of statistical physics methods to the modelling of social phenomena focusing our attention on models for opinion formation. On the other hand, we discuss and present original results of a model for opinion formation based on the social impact theory developed by Latané. The presented model accounts for the interaction among the members of a social group under the competitive influence of a strong leader and the mass media, both supporting two different states of opinion. Extensive simulations of the model are presented, showing that they led to the observation of a rich scenery of complex behaviour including, among others, critical behaviour and phase transitions between a state of opinion dominated by the leader and another dominated by the mass media. The occurrence of interesting finite-size effects reveals that, in small communities, the opinion of the leader may prevail over that of the mass media. This observation is relevant for the understanding of social phenomena involving a finite number of individuals, in contrast to actual physical phase transitions that take place in the thermodynamic limit. Finally, we give a brief outlook of open questions and lines for future work.
International Nuclear Information System (INIS)
Bordogna, Clelia Maria; Albano, Ezequiel V
2007-01-01
The aim of this paper is twofold. On the one hand we present a brief overview on the application of statistical physics methods to the modelling of social phenomena focusing our attention on models for opinion formation. On the other hand, we discuss and present original results of a model for opinion formation based on the social impact theory developed by Latane. The presented model accounts for the interaction among the members of a social group under the competitive influence of a strong leader and the mass media, both supporting two different states of opinion. Extensive simulations of the model are presented, showing that they led to the observation of a rich scenery of complex behaviour including, among others, critical behaviour and phase transitions between a state of opinion dominated by the leader and another dominated by the mass media. The occurrence of interesting finite-size effects reveals that, in small communities, the opinion of the leader may prevail over that of the mass media. This observation is relevant for the understanding of social phenomena involving a finite number of individuals, in contrast to actual physical phase transitions that take place in the thermodynamic limit. Finally, we give a brief outlook of open questions and lines for future work
Resources on quantitative/statistical research for applied linguists
Brown , James Dean
2004-01-01
Abstract The purpose of this review article is to survey and evaluate existing books on quantitative/statistical research in applied linguistics. The article begins by explaining the types of texts that will not be reviewed, then it briefly describes nine books that address how to do quantitative/statistical applied linguistics research. The review then compares (in prose and tables) the general characteris...
Resources on Quantitative/Statistical Research for Applied Linguists
Brown, James Dean
2004-01-01
The purpose of this review article is to survey and evaluate existing books on quantitative/statistical research in applied linguistics. The article begins by explaining the types of texts that will not be reviewed, then it briefly describes nine books that address how to do quantitative/statistical applied linguistics research. The review then…
Statistical Literacy among Applied Linguists and Second Language Acquisition Researchers
Loewen, Shawn; Lavolette, Elizabeth; Spino, Le Anne; Papi, Mostafa; Schmidtke, Jens; Sterling, Scott; Wolff, Dominik
2014-01-01
The importance of statistical knowledge in applied linguistics and second language acquisition (SLA) research has been emphasized in recent publications. However, the last investigation of the statistical literacy of applied linguists occurred more than 25 years ago (Lazaraton, Riggenbach, & Ediger, 1987). The current study undertook a partial…
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 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
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...
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...
Model output statistics applied to wind power prediction
Energy Technology Data Exchange (ETDEWEB)
Joensen, A; Giebel, G; Landberg, L [Risoe National Lab., Roskilde (Denmark); Madsen, H; Nielsen, H A [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)
1999-03-01
Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.
Applying Statistical Process Control to Clinical Data: An Illustration.
Pfadt, Al; And Others
1992-01-01
Principles of statistical process control are applied to a clinical setting through the use of control charts to detect changes, as part of treatment planning and clinical decision-making processes. The logic of control chart analysis is derived from principles of statistical inference. Sample charts offer examples of evaluating baselines and…
Applied Formal Methods for Elections
DEFF Research Database (Denmark)
Wang, Jian
development time, or second dynamically, i.e. monitoring while an implementation is used during an election, or after the election is over, for forensic analysis. This thesis contains two chapters on this subject: the chapter Analyzing Implementations of Election Technologies describes a technique...... process. The chapter Measuring Voter Lines describes an automated data collection method for measuring voters' waiting time, and discusses statistical models designed to provide an understanding of the voter behavior in polling stations....
2014 ICSA/KISS Joint Applied Statistics Symposium
Liu, Mengling; Luo, Xiaolong
2016-01-01
The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events. The most timely and advanced contributions from the joint 2014 ICSA/KISS Applied Statistics Symposium All papers feature original, peer-reviewed content Coverage consists of new developments in statisti...
Applied Statistics for the Social and Health Sciences
Gordon, Rachel A A
2012-01-01
Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish statistical models using contemporary standards. The book targets the social and health science branches such as human development, public health, sociology, psychology, education, and social work in which students bring a wide range of mathematical skills and have a wide range of methodological affinities. For these students, a successful course in statistics will not only offer statistical content
DEFF Research Database (Denmark)
Deporte, Nicolas; Ulrich, Clara; Mahévas, Stephanie
2012-01-01
The European Common Fisheries Policy recognizes the importance of accounting for heterogeneity in fishing practices, and métier-based sampling is now at the core of the EU Data Collection Framework. The implementation of such an approach would require Member States to agree on the standard regional...... métier definitions and on practical rules to categorize logbook records into métiers. Several alternative approaches have been used in the past to categorize landings profiles, but no consensus has yet emerged. A generic open-source workflow is developed to test and compare a selection of methods...
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
Applying intelligent statistical methods on biometric systems
Betschart, Willie
2005-01-01
This master’s thesis work was performed at Optimum Biometric Labs, OBL, located in Karlskrona, Sweden. Optimum Biometric Labs perform independent scenario evaluations to companies who develop biometric devices. The company has a product Optimum preConTM which is surveillance and diagnosis tool for biometric systems. This thesis work’s objective was to develop a conceptual model and implement it as an additional layer above the biometric layer with intelligence about the biometric users. The l...
Introduction to applied Bayesian statistics and estimation for social scientists
Lynch, Scott M
2007-01-01
""Introduction to Applied Bayesian Statistics and Estimation for Social Scientists"" covers the complete process of Bayesian statistical analysis in great detail from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.The first part of the book provides a detailed
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 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 planning of experiments applied in zeolite 4A synthesis
International Nuclear Information System (INIS)
Santos, Armindo; Santos, Liessi Luiz; Oliveira, Maria Lucia M. de; Pinto, Joao Mario Andrade
1995-01-01
Zeolite, an aluminum silicate which can be used in high level radioactive waste immobilization is presented. A brief description of various aspects of 4A Zeolite is made emphasizing the fractioned factorial statistic planning results, with two levels without replication, applied in the synthesis of this compound. (author). 7 refs., 3 figs
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 ...
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 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
Agronomic and Environmental research experiments result in data that are analyzed using statistical methods. These data are unavoidably accompanied by uncertainty. Decisions about hypotheses, based on statistical analyses of these data are therefore subject to error. This error is of three types,...
Applied statistics in agricultural, biological, and environmental sciences.
Agronomic research often involves measurement and collection of multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate statistical methods encompass the simultaneous analysis of all random variables measured on each experimental or s...
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 ...
Statistical process control applied to the manufacturing of beryllia ceramics
International Nuclear Information System (INIS)
Ferguson, G.P.; Jech, D.E.; Sepulveda, J.L.
1991-01-01
To compete effectively in an international market, scrap and re-work costs must be minimized. Statistical Process Control (SPC) provides powerful tools to optimize production performance. These techniques are currently being applied to the forming, metallizing, and brazing of beryllia ceramic components. This paper describes specific examples of applications of SPC to dry-pressing of beryllium oxide 2x2 substrates, to Mo-Mn refractory metallization, and to metallization and brazing of plasma tubes used in lasers where adhesion strength is critical
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,
Applying incomplete statistics to nonextensive systems with different q indices
International Nuclear Information System (INIS)
Nivanen, L.; Pezeril, M.; Wang, Q.A.; Mehaute, A. Le
2005-01-01
The nonextensive statistics based on the q-entropy Sq=--bar i=1v(pi-piq)1-q has been so far applied to systems in which the q value is uniformly distributed. For the systems containing different q's, the applicability of the theory is still a matter of investigation. The difficulty is that the class of systems to which the theory can be applied is actually limited by the usual nonadditivity rule of entropy which is no more valid when the systems contain non uniform distribution of q values. In this paper, within the framework of the so called incomplete information theory, we propose a more general nonadditivity rule of entropy prescribed by the zeroth law of thermodynamics. This new nonadditivity generalizes in a simple way the usual one and can be proved to lead uniquely to the q-entropy
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
Statistical sampling techniques as applied to OSE inspections
International Nuclear Information System (INIS)
Davis, J.J.; Cote, R.W.
1987-01-01
The need has been recognized for statistically valid methods for gathering information during OSE inspections; and for interpretation of results, both from performance testing and from records reviews, interviews, etc. Battelle Columbus Division, under contract to DOE OSE has performed and is continuing to perform work in the area of statistical methodology for OSE inspections. This paper represents some of the sampling methodology currently being developed for use during OSE inspections. Topics include population definition, sample size requirements, level of confidence and practical logistical constraints associated with the conduct of an inspection based on random sampling. Sequential sampling schemes and sampling from finite populations are also discussed. The methods described are applicable to various data gathering activities, ranging from the sampling and examination of classified documents to the sampling of Protective Force security inspectors for skill testing
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.
Statistical analysis and Kalman filtering applied to nuclear materials accountancy
International Nuclear Information System (INIS)
Annibal, P.S.
1990-08-01
Much theoretical research has been carried out on the development of statistical methods for nuclear material accountancy. In practice, physical, financial and time constraints mean that the techniques must be adapted to give an optimal performance in plant conditions. This thesis aims to bridge the gap between theory and practice, to show the benefits to be gained from a knowledge of the facility operation. Four different aspects are considered; firstly, the use of redundant measurements to reduce the error on the estimate of the mass of heavy metal in an 'accountancy tank' is investigated. Secondly, an analysis of the calibration data for the same tank is presented, establishing bounds for the error and suggesting a means of reducing them. Thirdly, a plant-specific method of producing an optimal statistic from the input, output and inventory data, to help decide between 'material loss' and 'no loss' hypotheses, is developed and compared with existing general techniques. Finally, an application of the Kalman Filter to materials accountancy is developed, to demonstrate the advantages of state-estimation techniques. The results of the analyses and comparisons illustrate the importance of taking into account a complete and accurate knowledge of the plant operation, measurement system, and calibration methods, to derive meaningful results from statistical tests on materials accountancy data, and to give a better understanding of critical random and systematic error sources. The analyses were carried out on the head-end of the Fast Reactor Reprocessing Plant, where fuel from the prototype fast reactor is cut up and dissolved. However, the techniques described are general in their application. (author)
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
Applied Formal Methods for Elections
DEFF Research Database (Denmark)
Wang, Jian
Information technology is changing the way elections are organized. Technology renders the electoral process more efficient, but things could also go wrong: Voting software is complex, it consists of over thousands of lines of code, which makes it error-prone. Technical problems may cause delays...... bounded model-checking and satisfiability modulo theories (SMT) solvers can be used to check these criteria. Voter Experience: Technology profoundly affects the voter experience. These effects need to be measured and the data should be used to make decisions regarding the implementation of the electoral...... at polling stations, or even delay the announcement of the final result. This thesis describes a set of methods to be used, for example, by system developers, administrators, or decision makers to examine election technologies, social choice algorithms and voter experience. Technology: Verifiability refers...
DEFF Research Database (Denmark)
Lopes Antunes, Ana Carolina; Jensen, Dan; Hisham Beshara Halasa, Tariq
2017-01-01
Disease monitoring and surveillance play a crucial role in control and eradication programs, as it is important to track implemented strategies in order to reduce and/or eliminate a specific disease. The objectives of this study were to assess the performance of different statistical monitoring......, decreases and constant sero-prevalence levels (referred as events). Two space-state models were used to model the time series, and different statistical monitoring methods (such as univariate process control algorithms–Shewart Control Chart, Tabular Cumulative Sums, and the V-mask- and monitoring...... of noise in the baseline was greater for the Shewhart Control Chart and Tabular Cumulative Sums than for the V-Mask and trend-based methods. The performance of the different statistical monitoring methods varied when monitoring increases and decreases in disease sero-prevalence. Combining two of more...
DEFF Research Database (Denmark)
Lopes Antunes, Ana Carolina; Jensen, Dan; Hisham Beshara Halasa, Tariq
2017-01-01
, decreases and constant sero-prevalence levels (referred as events). Two space-state models were used to model the time series, and different statistical monitoring methods (such as univariate process control algorithms–Shewart Control Chart, Tabular Cumulative Sums, and the V-mask- and monitoring......Disease monitoring and surveillance play a crucial role in control and eradication programs, as it is important to track implemented strategies in order to reduce and/or eliminate a specific disease. The objectives of this study were to assess the performance of different statistical monitoring...... of noise in the baseline was greater for the Shewhart Control Chart and Tabular Cumulative Sums than for the V-Mask and trend-based methods. The performance of the different statistical monitoring methods varied when monitoring increases and decreases in disease sero-prevalence. Combining two of more...
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.
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.
Hagen, Brad; Awosoga, Oluwagbohunmi A; Kellett, Peter; Damgaard, Marie
2013-04-23
This article describes the results of a qualitative research study evaluating nursing students' experiences of a mandatory course in applied statistics, and the perceived effectiveness of teaching methods implemented during the course. Fifteen nursing students in the third year of a four-year baccalaureate program in nursing participated in focus groups before and after taking the mandatory course in statistics. The interviews were transcribed and analyzed using content analysis to reveal four major themes: (i) "one of those courses you throw out?," (ii) "numbers and terrifying equations," (iii) "first aid for statistics casualties," and (iv) "re-thinking curriculum." Overall, the data revealed that although nursing students initially enter statistics courses with considerable skepticism, fear, and anxiety, there are a number of concrete actions statistics instructors can take to reduce student fear and increase the perceived relevance of courses in statistics.
Statistical sampling applied to the radiological characterization of historical waste
Directory of Open Access Journals (Sweden)
Zaffora Biagio
2016-01-01
Full Text Available The evaluation of the activity of radionuclides in radioactive waste is required for its disposal in final repositories. Easy-to-measure nuclides, like γ-emitters and high-energy X-rays, can be measured via non-destructive nuclear techniques from outside a waste package. Some radionuclides are difficult-to-measure (DTM from outside a package because they are α- or β-emitters. The present article discusses the application of linear regression, scaling factors (SF and the so-called “mean activity method” to estimate the activity of DTM nuclides on metallic waste produced at the European Organization for Nuclear Research (CERN. Various statistical sampling techniques including simple random sampling, systematic sampling, stratified and authoritative sampling are described and applied to 2 waste populations of activated copper cables. The bootstrap is introduced as a tool to estimate average activities and standard errors in waste characterization. The analysis of the DTM Ni-63 is used as an example. Experimental and theoretical values of SFs are calculated and compared. Guidelines for sampling historical waste using probabilistic and non-probabilistic sampling are finally given.
Applied statistics in ecology: common pitfalls and simple solutions
E. Ashley Steel; Maureen C. Kennedy; Patrick G. Cunningham; John S. Stanovick
2013-01-01
The most common statistical pitfalls in ecological research are those associated with data exploration, the logic of sampling and design, and the interpretation of statistical results. Although one can find published errors in calculations, the majority of statistical pitfalls result from incorrect logic or interpretation despite correct numerical calculations. There...
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...
Spectral deformation techniques applied to the study of quantum statistical irreversible processes
International Nuclear Information System (INIS)
Courbage, M.
1978-01-01
A procedure of analytic continuation of the resolvent of Liouville operators for quantum statistical systems is discussed. When applied to the theory of irreversible processes of the Brussels School, this method supports the idea that the restriction to a class of initial conditions is necessary to obtain an irreversible behaviour. The general results are tested on the Friedrichs model. (Auth.)
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.
Applying Statistical Process Quality Control Methodology to Educational Settings.
Blumberg, Carol Joyce
A subset of Statistical Process Control (SPC) methodology known as Control Charting is introduced. SPC methodology is a collection of graphical and inferential statistics techniques used to study the progress of phenomena over time. The types of control charts covered are the null X (mean), R (Range), X (individual observations), MR (moving…
Applied Mathematical Methods in Theoretical Physics
Masujima, Michio
2005-04-01
All there is to know about functional analysis, integral equations and calculus of variations in a single volume. This advanced textbook is divided into two parts: The first on integral equations and the second on the calculus of variations. It begins with a short introduction to functional analysis, including a short review of complex analysis, before continuing a systematic discussion of different types of equations, such as Volterra integral equations, singular integral equations of Cauchy type, integral equations of the Fredholm type, with a special emphasis on Wiener-Hopf integral equations and Wiener-Hopf sum equations. After a few remarks on the historical development, the second part starts with an introduction to the calculus of variations and the relationship between integral equations and applications of the calculus of variations. It further covers applications of the calculus of variations developed in the second half of the 20th century in the fields of quantum mechanics, quantum statistical mechanics and quantum field theory. Throughout the book, the author presents over 150 problems and exercises -- many from such branches of physics as quantum mechanics, quantum statistical mechanics, and quantum field theory -- together with outlines of the solutions in each case. Detailed solutions are given, supplementing the materials discussed in the main text, allowing problems to be solved making direct use of the method illustrated. The original references are given for difficult problems. The result is complete coverage of the mathematical tools and techniques used by physicists and applied mathematicians Intended for senior undergraduates and first-year graduates in science and engineering, this is equally useful as a reference and self-study guide.
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 analysis applied to safety culture self-assessment
International Nuclear Information System (INIS)
Macedo Soares, P.P.
2002-01-01
Interviews and opinion surveys are instruments used to assess the safety culture in an organization as part of the Safety Culture Enhancement Programme. Specific statistical tools are used to analyse the survey results. This paper presents an example of an opinion survey with the corresponding application of the statistical analysis and the conclusions obtained. Survey validation, Frequency statistics, Kolmogorov-Smirnov non-parametric test, Student (T-test) and ANOVA means comparison tests and LSD post-hoc multiple comparison test, are discussed. (author)
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.
Using Data Mining to Teach Applied Statistics and Correlation
Hartnett, Jessica L.
2016-01-01
This article describes two class activities that introduce the concept of data mining and very basic data mining analyses. Assessment data suggest that students learned some of the conceptual basics of data mining, understood some of the ethical concerns related to the practice, and were able to perform correlations via the Statistical Package for…
Applying Bayesian Statistics to Educational Evaluation. Theoretical Paper No. 62.
Brumet, Michael E.
Bayesian statistical inference is unfamiliar to many educational evaluators. While the classical model is useful in educational research, it is not as useful in evaluation because of the need to identify solutions to practical problems based on a wide spectrum of information. The reason Bayesian analysis is effective for decision making is that it…
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
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.
Statistical distributions as applied to environmental surveillance data
International Nuclear Information System (INIS)
Speer, D.R.; Waite, D.A.
1975-09-01
Application of normal, log normal, and Weibull distributions to environmental surveillance data was investigated for approximately 300 nuclide-medium-year-location combinations. Corresponding W test calculations were made to determine the probability of a particular data set falling within the distribution of interest. Conclusions are drawn as to the fit of any data group to the various distributions. The significance of fitting statistical distributions to the data is discussed
Applied Bayesian statistical studies in biology and medicine
D’Amore, G; Scalfari, F
2004-01-01
It was written on another occasion· that "It is apparent that the scientific culture, if one means production of scientific papers, is growing exponentially, and chaotically, in almost every field of investigation". The biomedical sciences sensu lato and mathematical statistics are no exceptions. One might say then, and with good reason, that another collection of bio statistical papers would only add to the overflow and cause even more confusion. Nevertheless, this book may be greeted with some interest if we state that most of the papers in it are the result of a collaboration between biologists and statisticians, and partly the product of the Summer School th "Statistical Inference in Human Biology" which reaches its 10 edition in 2003 (information about the School can be obtained at the Web site http://www2. stat. unibo. itleventilSito%20scuolalindex. htm). is common experience - and not only This is rather important. Indeed, it in Italy - that encounters between statisticians and researchers are spora...
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.
International Nuclear Information System (INIS)
Oksengendler, B. L.; Turaeva, N. N.; Uralov, I.; Marasulov, M. B.
2012-01-01
The effect of multiple exciton generation is analyzed based on statistical physics, quantum mechanics, and synergetics. Statistical problems of the effect of multiple exciton generation (MEG) are broadened and take into account not only exciton generation, but also background excitation. The study of the role of surface states of quantum dots is based on the synergy of self-catalyzed electronic reactions. An analysis of the MEG mechanism is based on the idea of electronic shaking using the sudden perturbation method in quantum mechanics. All of the above-mentioned results are applied to the problem of calculating the limiting efficiency to transform solar energy into electric energy. (authors)
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...
Applying Bayesian statistics to the study of psychological trauma: A suggestion for future research.
Yalch, Matthew M
2016-03-01
Several contemporary researchers have noted the virtues of Bayesian methods of data analysis. Although debates continue about whether conventional or Bayesian statistics is the "better" approach for researchers in general, there are reasons why Bayesian methods may be well suited to the study of psychological trauma in particular. This article describes how Bayesian statistics offers practical solutions to the problems of data non-normality, small sample size, and missing data common in research on psychological trauma. After a discussion of these problems and the effects they have on trauma research, this article explains the basic philosophical and statistical foundations of Bayesian statistics and how it provides solutions to these problems using an applied example. Results of the literature review and the accompanying example indicates the utility of Bayesian statistics in addressing problems common in trauma research. Bayesian statistics provides a set of methodological tools and a broader philosophical framework that is useful for trauma researchers. Methodological resources are also provided so that interested readers can learn more. (c) 2016 APA, all rights reserved).
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
[Montessori method applied to dementia - literature review].
Brandão, Daniela Filipa Soares; Martín, José Ignacio
2012-06-01
The Montessori method was initially applied to children, but now it has also been applied to people with dementia. The purpose of this study is to systematically review the research on the effectiveness of this method using Medical Literature Analysis and Retrieval System Online (Medline) with the keywords dementia and Montessori method. We selected lo studies, in which there were significant improvements in participation and constructive engagement, and reduction of negative affects and passive engagement. Nevertheless, systematic reviews about this non-pharmacological intervention in dementia rate this method as weak in terms of effectiveness. This apparent discrepancy can be explained because the Montessori method may have, in fact, a small influence on dimensions such as behavioral problems, or because there is no research about this method with high levels of control, such as the presence of several control groups or a double-blind study.
Statistical distributions as applied to environmental surveillance data
International Nuclear Information System (INIS)
Speer, D.R.; Waite, D.A.
1976-01-01
Application of normal, lognormal, and Weibull distributions to radiological environmental surveillance data was investigated for approximately 300 nuclide-medium-year-location combinations. The fit of data to distributions was compared through probability plotting (special graph paper provides a visual check) and W test calculations. Results show that 25% of the data fit the normal distribution, 50% fit the lognormal, and 90% fit the Weibull.Demonstration of how to plot each distribution shows that normal and lognormal distributions are comparatively easy to use while Weibull distribution is complicated and difficult to use. Although current practice is to use normal distribution statistics, normal fit the least number of data groups considered in this study
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
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 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.
A BRDF statistical model applying to space target materials modeling
Liu, Chenghao; Li, Zhi; Xu, Can; Tian, Qichen
2017-10-01
In order to solve the problem of poor effect in modeling the large density BRDF measured data with five-parameter semi-empirical model, a refined statistical model of BRDF which is suitable for multi-class space target material modeling were proposed. The refined model improved the Torrance-Sparrow model while having the modeling advantages of five-parameter model. Compared with the existing empirical model, the model contains six simple parameters, which can approximate the roughness distribution of the material surface, can approximate the intensity of the Fresnel reflectance phenomenon and the attenuation of the reflected light's brightness with the azimuth angle changes. The model is able to achieve parameter inversion quickly with no extra loss of accuracy. The genetic algorithm was used to invert the parameters of 11 different samples in the space target commonly used materials, and the fitting errors of all materials were below 6%, which were much lower than those of five-parameter model. The effect of the refined model is verified by comparing the fitting results of the three samples at different incident zenith angles in 0° azimuth angle. Finally, the three-dimensional modeling visualizations of these samples in the upper hemisphere space was given, in which the strength of the optical scattering of different materials could be clearly shown. It proved the good describing ability of the refined model at the material characterization as well.
VISUALIZATION OF DATA AND RESULTS AS А METHODOLOGICAL BASIS OF APPLIED STATISTICS TEACHING
Directory of Open Access Journals (Sweden)
R. R. Nuriakhmetov
2014-01-01
Full Text Available Traditional methods of teaching in medical high school of informatics as computer sciences and statistics as a section of high mathematics contradict to requirements of modern applied medicine and a medical science. A research objective is revealing of the reasons of the given discrepancy and its elimination ways. Similar discrepancy was revealed earlier by foreign researchers studying efficiency of the statistic school programs. The revealed laws appeared to be extended to a technique of teaching of statistics in a high medical school. Pursuing this aim the tests of educational achievements developed by the author were applied on the students of medical and biologic department of the Siberian State Medical Universirty that trained on specialities of “biophysics" and “biochemistry". The fundamental problem of statistical education is that symbols used by these science concern to the objects, which students still have to design. As a substantiation of this conclusion serves the ontosemiotical approach to working out of the maintenance of a course. In the article there are considered the approaches to the permission of the given contradiction, based on the experience of teaching of statistics in foreign schools and on the workings out of the author. In particular the conclusion about necessity of revision the tradition of using professional statistical packages and introduction of a special educational software. To working out the maintenance of a learning course it is offered to more widely apply the historical approach which concrete definition is represented by a principle of a guided reinvention.
Directory of Open Access Journals (Sweden)
P. Moreno Quintana
2002-05-01
Full Text Available La introducción de los simuladores en el proceso de instrucción en el país cuenta con una dificultad al no conocerse el realimpacto de este tipo de equipamiento en la adquisición de las habilidades dentro del proceso de entrenamiento a que vadirigido.El empleo del método estadístico factorial a dos niveles permite la obtención de un modelo lineal de respuesta de laeficiencia, o calificación, en función de la forma cuantitativa de empleo de los diversos medios de entrenamiento y suscombinaciones.Este modelo es validado con un nivel de confianza calculado y puede ser optimizado por los métodos matemáticoscorrespondientes. Para esto se realiza un grupo de recomendaciones en la organización de los experimentos que han sidoobtenidos durante la aplicación de este método en diversas ocasiones.Palabras claves: Simuladores, modelación matemática, diseño de experimentos._____________________________________________________________________________Abstract.The introduction of simulators in the country´s instruction process deals with the difficulty of not knowing the real impactof this equipment in the acquisition of abilities within the training process. The use of the factorial statistical method at twolevels allows the obtaining of a linear model with answer about efficiency or qualification based on the quantitative form ofuse of diverse means of training and its combinations. This model is validated with a calculated level of confidence and canbe optimized by the corresponding mathematical methods. For this a group of recommendations is made in the organizationof experiments that have been obtained during the application of this method in diverse combnations.Key words: Simulators, mathematical modelation, experiment design.
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.
Statistics applied to the testing of cladding tubes
International Nuclear Information System (INIS)
Perdijon, J.
1987-01-01
Cladding tubes, either steel or zircaloy, are generally given a 100 % inspection through ultrasonic non-destructive testing. This inspection may be completed beneficially with an eddy current test, as this is not sensitive to the same defects as those typically traced by ultrasonic testing. Unfortunately, the two methods (as with other non-destructive tests) exhibit poor precision; this means that a flaw, whose size is close to that denoted as rejection limit, may be accepted or rejected. Currently, rejection, i.e. the measurement above which a tube is rejected, is generally determined through measuring a calibration tube at regular time intervals, and the signal of a given tube is compared to that of the most recently completed calibration. This measurement is thus subject to variations which can be attributed to an actual shift of adjustments as well as to poor precision. For this reason, monitoring instrument adjustments using the so-called control chart method are proposed
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
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,
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
Geostatistical methods applied to field model residuals
DEFF Research Database (Denmark)
Maule, Fox; Mosegaard, K.; Olsen, Nils
consists of measurement errors and unmodelled signal), and is typically assumed to be uncorrelated and Gaussian distributed. We have applied geostatistical methods to analyse the residuals of the Oersted(09d/04) field model [http://www.dsri.dk/Oersted/Field_models/IGRF_2005_candidates/], which is based...
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.
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.
[Statistical analysis of articles in "Chinese journal of applied physiology" from 1999 to 2008].
Du, Fei; Fang, Tao; Ge, Xue-ming; Jin, Peng; Zhang, Xiao-hong; Sun, Jin-li
2010-05-01
To evaluate the academic level and influence of "Chinese Journal of Applied Physiology" through statistical analysis for the fund sponsored articles published in the recent ten years. The articles of "Chinese Journal of Applied Physiology" from 1999 to 2008 were investigated. The number and the percentage of the fund sponsored articles, the fund organization and the author region were quantitatively analyzed by using the literature metrology method. The number of the fund sponsored articles increased unceasingly. The ratio of the fund from local government significantly enhanced in the latter five years. Most of the articles were from institutes located at Beijing, Zhejiang and Tianjin. "Chinese Journal of Applied Physiology" has a fine academic level and social influence.
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
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).
1980-03-18
of Operations Research Society , 25, 1977, 493-505. Limit probabilities n a multi-type critical age-dependent branching process, Howard Weiner...11, 9/23/77. Scandi Acturial Journal, 1978, 211-224. q. On the distribution of the greatest coon divisor, Persl Diaconis & Paul Erdos. Technical Report...Technical Report No. 20, 7/12/78. Journal of the Roya-- Eatistical Society , Series B, 40, 1978, 64,70. Toward characterizing Boolean transformations, Alan
Applied mathematical methods in nuclear thermal hydraulics
International Nuclear Information System (INIS)
Ransom, V.H.; Trapp, J.A.
1983-01-01
Applied mathematical methods are used extensively in modeling of nuclear reactor thermal-hydraulic behavior. This application has required significant extension to the state-of-the-art. The problems encountered in modeling of two-phase fluid transients and the development of associated numerical solution methods are reviewed and quantified using results from a numerical study of an analogous linear system of differential equations. In particular, some possible approaches for formulating a well-posed numerical problem for an ill-posed differential model are investigated and discussed. The need for closer attention to numerical fidelity is indicated
Entropy viscosity method applied to Euler equations
International Nuclear Information System (INIS)
Delchini, M. O.; Ragusa, J. C.; Berry, R. A.
2013-01-01
The entropy viscosity method [4] has been successfully applied to hyperbolic systems of equations such as Burgers equation and Euler equations. The method consists in adding dissipative terms to the governing equations, where a viscosity coefficient modulates the amount of dissipation. The entropy viscosity method has been applied to the 1-D Euler equations with variable area using a continuous finite element discretization in the MOOSE framework and our results show that it has the ability to efficiently smooth out oscillations and accurately resolve shocks. Two equations of state are considered: Ideal Gas and Stiffened Gas Equations Of State. Results are provided for a second-order time implicit schemes (BDF2). Some typical Riemann problems are run with the entropy viscosity method to demonstrate some of its features. Then, a 1-D convergent-divergent nozzle is considered with open boundary conditions. The correct steady-state is reached for the liquid and gas phases with a time implicit scheme. The entropy viscosity method correctly behaves in every problem run. For each test problem, results are shown for both equations of state considered here. (authors)
Analytical methods applied to water pollution
International Nuclear Information System (INIS)
Baudin, G.
1977-01-01
A comparison of different methods applied to water analysis is given. The discussion is limited to the problems presented by inorganic elements, accessible to nuclear activation analysis methods. The following methods were compared: activation analysis: with gamma-ray spectrometry, atomic absorption spectrometry, fluorimetry, emission spectrometry, colorimetry or spectrophotometry, X-ray fluorescence, mass spectrometry, voltametry, polarography or other electrochemical methods, activation analysis-beta measurements. Drinking-water, irrigation waters, sea waters, industrial wastes and very pure waters are the subjects of the investigations. The comparative evaluation is made on the basis of storage of samples, in situ analysis, treatment and concentration, specificity and interference, monoelement or multielement analysis, analysis time and accuracy. The significance of the neutron analysis is shown. (T.G.)
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.
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...
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.
Hagen, Brad; Awosoga, Olu; Kellett, Peter; Dei, Samuel Ofori
2013-09-01
Undergraduate nursing students must often take a course in statistics, yet there is scant research to inform teaching pedagogy. The objectives of this study were to assess nursing students' overall attitudes towards statistics courses - including (among other things) overall fear and anxiety, preferred learning and teaching styles, and the perceived utility and benefit of taking a statistics course - before and after taking a mandatory course in applied statistics. The authors used a pre-experimental research design (a one-group pre-test/post-test research design), by administering a survey to nursing students at the beginning and end of the course. The study was conducted at a University in Western Canada that offers an undergraduate Bachelor of Nursing degree. Participants included 104 nursing students, in the third year of a four-year nursing program, taking a course in statistics. Although students only reported moderate anxiety towards statistics, student anxiety about statistics had dropped by approximately 40% by the end of the course. Students also reported a considerable and positive change in their attitudes towards learning in groups by the end of the course, a potential reflection of the team-based learning that was used. Students identified preferred learning and teaching approaches, including the use of real-life examples, visual teaching aids, clear explanations, timely feedback, and a well-paced course. Students also identified preferred instructor characteristics, such as patience, approachability, in-depth knowledge of statistics, and a sense of humor. Unfortunately, students only indicated moderate agreement with the idea that statistics would be useful and relevant to their careers, even by the end of the course. Our findings validate anecdotal reports on statistics teaching pedagogy, although more research is clearly needed, particularly on how to increase students' perceptions of the benefit and utility of statistics courses for their nursing
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
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
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
Bayesian statistics applied to neutron activation data for reactor flux spectrum analysis
International Nuclear Information System (INIS)
Chiesa, Davide; Previtali, Ezio; Sisti, Monica
2014-01-01
Highlights: • Bayesian statistics to analyze the neutron flux spectrum from activation data. • Rigorous statistical approach for accurate evaluation of the neutron flux groups. • Cross section and activation data uncertainties included for the problem solution. • Flexible methodology applied to analyze different nuclear reactor flux spectra. • The results are in good agreement with the MCNP simulations of neutron fluxes. - Abstract: In this paper, we present a statistical method, based on Bayesian statistics, to analyze the neutron flux spectrum from the activation data of different isotopes. The experimental data were acquired during a neutron activation experiment performed at the TRIGA Mark II reactor of Pavia University (Italy) in four irradiation positions characterized by different neutron spectra. In order to evaluate the neutron flux spectrum, subdivided in energy groups, a system of linear equations, containing the group effective cross sections and the activation rate data, has to be solved. However, since the system’s coefficients are experimental data affected by uncertainties, a rigorous statistical approach is fundamental for an accurate evaluation of the neutron flux groups. For this purpose, we applied the Bayesian statistical analysis, that allows to include the uncertainties of the coefficients and the a priori information about the neutron flux. A program for the analysis of Bayesian hierarchical models, based on Markov Chain Monte Carlo (MCMC) simulations, was used to define the problem statistical model and solve it. The first analysis involved the determination of the thermal, resonance-intermediate and fast flux components and the dependence of the results on the Prior distribution choice was investigated to confirm the reliability of the Bayesian analysis. After that, the main resonances of the activation cross sections were analyzed to implement multi-group models with finer energy subdivisions that would allow to determine the
Statistical models and methods for reliability and survival analysis
Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo
2013-01-01
Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical
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...
Schindler, Maike; Mackrell, Kate; Pratt, Dave; Bakker, A.
2017-01-01
Schindler, M., Mackrell, K., Pratt, D., & Bakker, A. (2017). Applying contemporary philosophy in mathematics and statistics education: The perspective of inferentialism. In G. Kaiser (Ed.). Proceedings of the 13th International Congress on Mathematical Education, ICME-13
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.
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.
Shiavi, Richard
2007-01-01
Introduction to Applied Statistical Signal Analysis is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech.Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical
An Applied Statistics Course for Systematics and Ecology PhD Students
Ojeda, Mario Miguel; Sosa, Victoria
2002-01-01
Statistics education is under review at all educational levels. Statistical concepts, as well as the use of statistical methods and techniques, can be taught in at least two contrasting ways. Specifically, (1) teaching can be theoretically and mathematically oriented, or (2) it can be less mathematically oriented being focused, instead, on…
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.
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 methods for the planning of inspections
International Nuclear Information System (INIS)
Hough, C.G.; Beetle, T.M.
1976-01-01
Inspection plans are designed to detect diversions of M kilograms of nuclear material with a high degree of confidence. Attribute sample plans were first developed and applied at a zero-energy fast reactor in the United Kingdom in co-operation with the Agency. Battelle-Northwest in the United States of America proposed a variables sample plan based on decision theory. The Karlsruhe Research Center in the Federal Republic of Germany developed the strategic points concept and sample plans based on game theory considerations. All these approaches were combined into a common approach which is summarized in this report. (author)
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/
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
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
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...
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
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.
Statistical methods for damage detection applied to civil structures
DEFF Research Database (Denmark)
Gres, Szymon; Ulriksen, Martin Dalgaard; Döhler, Michael
2017-01-01
Damage detection consists of monitoring the deviations of a current system from its reference state, characterized by some nominal property repeatable for every healthy state. Preferably, the damage detection is performed directly on vibration data, hereby avoiding modal identification of the str...
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
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)
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.
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
Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM
Warner, Rebecca M.
2007-01-01
This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…
Applying scrum methods to ITS projects.
2017-08-01
The introduction of new technology generally brings new challenges and new methods to help with deployments. Agile methodologies have been introduced in the information technology industry to potentially speed up development. The Federal Highway Admi...
Applying Fuzzy Possibilistic Methods on Critical Objects
DEFF Research Database (Denmark)
Yazdani, Hossein; Ortiz-Arroyo, Daniel; Choros, Kazimierz
2016-01-01
Providing a ﬂexible environment to process data objects is a desirable goal of machine learning algorithms. In fuzzy and possibilistic methods, the relevance of data objects is evaluated and a membership degree is assigned. However, some critical objects objects have the potential ability to affect...... the performance of the clustering algorithms if they remain in a speciﬁc cluster or they are moved into another. In this paper we analyze and compare how critical objects affect the behaviour of fuzzy possibilistic methods in several data sets. The comparison is based on the accuracy and ability of learning...... methods to provide a proper searching space for data objects. The membership functions used by each method when dealing with critical objects is also evaluated. Our results show that relaxing the conditions of participation for data objects in as many partitions as they can, is beneﬁcial....
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
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.
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)
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.
Lavine method applied to three body problems
International Nuclear Information System (INIS)
Mourre, Eric.
1975-09-01
The methods presently proposed for the three body problem in quantum mechanics, using the Faddeev approach for proving the asymptotic completeness, come up against the presence of new singularities when the potentials considered v(α)(x(α)) for two-particle interactions decay less rapidly than /x(α)/ -2 ; and also when trials are made for solving the problem with a representation space whose dimension for a particle is lower than three. A method is given that allows the mathematical approach to be extended to three body problem, in spite of singularities. Applications are given [fr
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
Applying Human Computation Methods to Information Science
Harris, Christopher Glenn
2013-01-01
Human Computation methods such as crowdsourcing and games with a purpose (GWAP) have each recently drawn considerable attention for their ability to synergize the strengths of people and technology to accomplish tasks that are challenging for either to do well alone. Despite this increased attention, much of this transformation has been focused on…
Applying Mixed Methods Techniques in Strategic Planning
Voorhees, Richard A.
2008-01-01
In its most basic form, strategic planning is a process of anticipating change, identifying new opportunities, and executing strategy. The use of mixed methods, blending quantitative and qualitative analytical techniques and data, in the process of assembling a strategic plan can help to ensure a successful outcome. In this article, the author…
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
[The diagnostic methods applied in mycology].
Kurnatowska, Alicja; Kurnatowski, Piotr
2008-01-01
The systemic fungal invasions are recognized with increasing frequency and constitute a primary cause of morbidity and mortality, especially in immunocompromised patients. Early diagnosis improves prognosis, but remains a problem because there is lack of sensitive tests to aid in the diagnosis of systemic mycoses on the one hand, and on the other the patients only present unspecific signs and symptoms, thus delaying early diagnosis. The diagnosis depends upon a combination of clinical observation and laboratory investigation. The successful laboratory diagnosis of fungal infection depends in major part on the collection of appropriate clinical specimens for investigations and on the selection of appropriate microbiological test procedures. So these problems (collection of specimens, direct techniques, staining methods, cultures on different media and non-culture-based methods) are presented in article.
Monte Carlo method applied to medical physics
International Nuclear Information System (INIS)
Oliveira, C.; Goncalves, I.F.; Chaves, A.; Lopes, M.C.; Teixeira, N.; Matos, B.; Goncalves, I.C.; Ramalho, A.; Salgado, J.
2000-01-01
The main application of the Monte Carlo method to medical physics is dose calculation. This paper shows some results of two dose calculation studies and two other different applications: optimisation of neutron field for Boron Neutron Capture Therapy and optimization of a filter for a beam tube for several purposes. The time necessary for Monte Carlo calculations - the highest boundary for its intensive utilisation - is being over-passed with faster and cheaper computers. (author)
Proteomics methods applied to malaria: Plasmodium falciparum
International Nuclear Information System (INIS)
Cuesta Astroz, Yesid; Segura Latorre, Cesar
2012-01-01
Malaria is a parasitic disease that has a high impact on public health in developing countries. The sequencing of the plasmodium falciparum genome and the development of proteomics have enabled a breakthrough in understanding the biology of the parasite. Proteomics have allowed to characterize qualitatively and quantitatively the parasite s expression of proteins and has provided information on protein expression under conditions of stress induced by antimalarial. Given the complexity of their life cycle, this takes place in the vertebrate host and mosquito vector. It has proven difficult to characterize the protein expression during each stage throughout the infection process in order to determine the proteome that mediates several metabolic, physiological and energetic processes. Two dimensional electrophoresis, liquid chromatography and mass spectrometry have been useful to assess the effects of antimalarial on parasite protein expression and to characterize the proteomic profile of different p. falciparum stages and organelles. The purpose of this review is to present state of the art tools and advances in proteomics applied to the study of malaria, and to present different experimental strategies used to study the parasite's proteome in order to show the advantages and disadvantages of each one.
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
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
METHOD OF APPLYING NICKEL COATINGS ON URANIUM
Gray, A.G.
1959-07-14
A method is presented for protectively coating uranium which comprises etching the uranium in an aqueous etching solution containing chloride ions, electroplating a coating of nickel on the etched uranium and heating the nickel plated uranium by immersion thereof in a molten bath composed of a material selected from the group consisting of sodium chloride, potassium chloride, lithium chloride, and mixtures thereof, maintained at a temperature of between 700 and 800 deg C, for a time sufficient to alloy the nickel and uranium and form an integral protective coating of corrosion-resistant uranium-nickel alloy.
Applied statistics in the pharmaceutical industry with case studies using S-PLUS
Krause, Andreas
2001-01-01
The purpose of this book is to provide a general guide to statistical methods used in the pharmaceutical industry, and to illustrate how to use S-PLUS to implement these methods. Specifically, the goal is to: *Illustrate statistical applications in the pharmaceutical industry; *Illustrate how the statistical applications can be carried out using S-PLUS; *Illustrate why S-PLUS is a useful software package for carrying out these applications; *Discuss the results and implications of a particular application; The target audience for this book is very broad, including: *Graduate students in biostatistics; *Statisticians who are involved in the industry as research scientists, regulators, academics, and/or consultants who want to know more about how to use S-PLUS and learn about other sub-fields within the indsutry that they may not be familiar with; *Statisticians in other fields who want to know more about statistical applications in the pharmaceutical industry.
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.
Versatile Formal Methods Applied to Quantum Information.
Energy Technology Data Exchange (ETDEWEB)
Witzel, Wayne [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Rudinger, Kenneth Michael [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Sarovar, Mohan [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
2015-11-01
Using a novel formal methods approach, we have generated computer-veri ed proofs of major theorems pertinent to the quantum phase estimation algorithm. This was accomplished using our Prove-It software package in Python. While many formal methods tools are available, their practical utility is limited. Translating a problem of interest into these systems and working through the steps of a proof is an art form that requires much expertise. One must surrender to the preferences and restrictions of the tool regarding how mathematical notions are expressed and what deductions are allowed. Automation is a major driver that forces restrictions. Our focus, on the other hand, is to produce a tool that allows users the ability to con rm proofs that are essentially known already. This goal is valuable in itself. We demonstrate the viability of our approach that allows the user great exibility in expressing state- ments and composing derivations. There were no major obstacles in following a textbook proof of the quantum phase estimation algorithm. There were tedious details of algebraic manipulations that we needed to implement (and a few that we did not have time to enter into our system) and some basic components that we needed to rethink, but there were no serious roadblocks. In the process, we made a number of convenient additions to our Prove-It package that will make certain algebraic manipulations easier to perform in the future. In fact, our intent is for our system to build upon itself in this manner.
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
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
Nuclear and nuclear related analytical methods applied in environmental research
International Nuclear Information System (INIS)
Popescu, Ion V.; Gheboianu, Anca; Bancuta, Iulian; Cimpoca, G. V; Stihi, Claudia; Radulescu, Cristiana; Oros Calin; Frontasyeva, Marina; Petre, Marian; Dulama, Ioana; Vlaicu, G.
2010-01-01
Nuclear Analytical Methods can be used for research activities on environmental studies like water quality assessment, pesticide residues, global climatic change (transboundary), pollution and remediation. Heavy metal pollution is a problem associated with areas of intensive industrial activity. In this work the moss bio monitoring technique was employed to study the atmospheric deposition in Dambovita County Romania. Also, there were used complementary nuclear and atomic analytical methods: Neutron Activation Analysis (NAA), Atomic Absorption Spectrometry (AAS) and Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES). These high sensitivity analysis methods were used to determine the chemical composition of some samples of mosses placed in different areas with different pollution industrial sources. The concentrations of Cr, Fe, Mn, Ni and Zn were determined. The concentration of Fe from the same samples was determined using all these methods and we obtained a very good agreement, in statistical limits, which demonstrate the capability of these analytical methods to be applied on a large spectrum of environmental samples with the same results. (authors)
Optimization methods applied to hybrid vehicle design
Donoghue, J. F.; Burghart, J. H.
1983-01-01
The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.
Excel 2016 in applied statistics for high school students a guide to solving practical problems
Quirk, Thomas J
2018-01-01
This textbook is a step-by-step guide for high school, community college, or undergraduate students who are taking a course in applied statistics and wish to learn how to use Excel to solve statistical problems. All of the statistics problems in this book will come from the following fields of study: business, education, psychology, marketing, engineering and advertising. Students will learn how to perform key statistical tests in Excel without being overwhelmed by statistical theory. Each chapter briefly explains a topic and then demonstrates how to use Excel commands and formulas to solve specific statistics problems. This book gives practice in using Excel in two different ways: (1) writing formulas (e.g., confidence interval about the mean, one-group t-test, two-group t-test, correlation) and (2) using Excel’s drop-down formula menus (e.g., simple linear regression, multiple correlations and multiple regression, and one-way ANOVA). Three practice problems are provided at the end of each chapter, along w...
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
Comparison of small n statistical tests of differential expression applied to microarrays
Directory of Open Access Journals (Sweden)
Lee Anna Y
2009-02-01
Full Text Available Abstract Background DNA microarrays provide data for genome wide patterns of expression between observation classes. Microarray studies often have small samples sizes, however, due to cost constraints or specimen availability. This can lead to poor random error estimates and inaccurate statistical tests of differential expression. We compare the performance of the standard t-test, fold change, and four small n statistical test methods designed to circumvent these problems. We report results of various normalization methods for empirical microarray data and of various random error models for simulated data. Results Three Empirical Bayes methods (CyberT, BRB, and limma t-statistics were the most effective statistical tests across simulated and both 2-colour cDNA and Affymetrix experimental data. The CyberT regularized t-statistic in particular was able to maintain expected false positive rates with simulated data showing high variances at low gene intensities, although at the cost of low true positive rates. The Local Pooled Error (LPE test introduced a bias that lowered false positive rates below theoretically expected values and had lower power relative to the top performers. The standard two-sample t-test and fold change were also found to be sub-optimal for detecting differentially expressed genes. The generalized log transformation was shown to be beneficial in improving results with certain data sets, in particular high variance cDNA data. Conclusion Pre-processing of data influences performance and the proper combination of pre-processing and statistical testing is necessary for obtaining the best results. All three Empirical Bayes methods assessed in our study are good choices for statistical tests for small n microarray studies for both Affymetrix and cDNA data. Choice of method for a particular study will depend on software and normalization preferences.
Applying the Socratic Method to Physics Education
Corcoran, Ed
2005-04-01
We have restructured University Physics I and II in accordance with methods that PER has shown to be effective, including a more interactive discussion- and activity-based curriculum based on the premise that developing understanding requires an interactive process in which students have the opportunity to talk through and think through ideas with both other students and the teacher. Studies have shown that in classes implementing this approach to teaching as compared to classes using a traditional approach, students have significantly higher gains on the Force Concept Inventory (FCI). This has been true in UPI. However, UPI FCI results seem to suggest that there is a significant conceptual hole in students' understanding of Newton's Second Law. Two labs in UPI which teach Newton's Second Law will be redesigned replacing more activity with students as a group talking through, thinking through, and answering conceptual questions asked by the TA. The results will be measured by comparing FCI results to those from previous semesters, coupled with interviews. The results will be analyzed, and we will attempt to understand why gains were or were not made.
Scanning probe methods applied to molecular electronics
Energy Technology Data Exchange (ETDEWEB)
Pavlicek, Niko
2013-08-01
Scanning probe methods on insulating films offer a rich toolbox to study electronic, structural and spin properties of individual molecules. This work discusses three issues in the field of molecular and organic electronics. An STM head to be operated in high magnetic fields has been designed and built up. The STM head is very compact and rigid relying on a robust coarse approach mechanism. This will facilitate investigations of the spin properties of individual molecules in the future. Combined STM/AFM studies revealed a reversible molecular switch based on two stable configurations of DBTH molecules on ultrathin NaCl films. AFM experiments visualize the molecular structure in both states. Our experiments allowed to unambiguously determine the pathway of the switch. Finally, tunneling into and out of the frontier molecular orbitals of pentacene molecules has been investigated on different insulating films. These experiments show that the local symmetry of initial and final electron wave function are decisive for the ratio between elastic and vibration-assisted tunneling. The results can be generalized to electron transport in organic materials.
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
Energy Technology Data Exchange (ETDEWEB)
Gabriel Filho, Luis Roberto Almeida [Universidade Estadual Paulista Julio de Mesquita Filho (FCA/UNESP), Botucatu, SP (Brazil). Fac. de Ciencias Agronomicas], email: gabrielfilho@tupa.unesp.br; Cremasco, Camila P. [Faculdade de Tecnologia (FATEC), Presidente Prudente, SP (Brazil); Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), Botucatu, SP (Brazil). Dept. de Bioestatistica; Verri, Juliano A. [Universidade Estadual Paulista Julio de Mesquita Filho (FCT/UNESP), Presidente Prudente, SP (Brazil). Dept. de Matematica, Estatistica e Computacao; Viais Neto, Daniel dos S. [Faculdade de Tecnologia (FATEC), Presidente Prudente, SP (Brazil); Universidade Estadual Paulista Julio de Mesquita Filho (FCA/UNESP), Botucatu, SP (Brazil). Fac. de Ciencias Agronomicas; Seraphim, Odivaldo J. [Universidade Estadual Paulista Julio de Mesquita Filho (FCA/UNESP), Botucatu, SP (Brazil). Fac. de Ciencias Agronomicas. Dept. de Engenharia Rural
2011-07-01
The wind energy is an abundant source of renewable energy, clean and available almost everywhere. For its use, studies are needed to adequately describe its intensity for statistical methods and design for wind turbines. The objective is to structure the mathematical methods used to conduct a general description of the wind, to establish a description of the wind regime using the parameters described using the Weibull function and the analytical model of power from a wind turbine, as well as applications of these methods show. This work was developed at Rural Empowerment Lab of FCA/UNESP in Botucatu-SP. For the application of methods were utilized measurements of wind speed and direction, between 2004 and 2005, obtained by anemometer RM Young Wind Monitor-Campbell. As a result, they estimated the wind behavior and distribution of wind in the region, with 78 kWh of energy production, relatively low potential to supply a small house. Moreover, this energy could possibly be applied in ambient illumination, power supply for electric fences and irrigation of vegetables. (author)
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
Teleni, Vicki; Baldauf, Richard B., Jr.
A study investigated the statistical techniques used by applied linguists and reported in three journals, "Language Learning,""Applied Linguistics," and "TESOL Quarterly," between 1980 and 1986. It was found that 47% of the published articles used statistical procedures. In these articles, 63% of the techniques used could be called basic, 28%…
International Nuclear Information System (INIS)
Beedgen, R.
1988-03-01
The computer program PROSA (PROgram for Statistical Analysis of near-real-time accountancy data) was developed as a tool to apply statistical test procedures to a sequence of materials balance results for detecting losses of material. First applications of PROSA to model facility data and real plant data showed that PROSA is also usable as a tool for process or measurement control. To deepen the experience for the application of PROSA to real data of bulk-handling facilities, we applied it to uranium data of the Allied General Nuclear Services miniruns, where accountancy data were collected on a near-real-time basis. Minirun 6 especially was considered, and the pulsed columns were chosen as materials balance area. The structure of the measurement models for flow sheet data and actual operation data are compared, and methods are studied to reduce the error for inventory measurements of the columns
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...
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
Cluster detection methods applied to the Upper Cape Cod cancer data
Directory of Open Access Journals (Sweden)
Ozonoff David
2005-09-01
Full Text Available Abstract Background A variety of statistical methods have been suggested to assess the degree and/or the location of spatial clustering of disease cases. However, there is relatively little in the literature devoted to comparison and critique of different methods. Most of the available comparative studies rely on simulated data rather than real data sets. Methods We have chosen three methods currently used for examining spatial disease patterns: the M-statistic of Bonetti and Pagano; the Generalized Additive Model (GAM method as applied by Webster; and Kulldorff's spatial scan statistic. We apply these statistics to analyze breast cancer data from the Upper Cape Cancer Incidence Study using three different latency assumptions. Results The three different latency assumptions produced three different spatial patterns of cases and controls. For 20 year latency, all three methods generally concur. However, for 15 year latency and no latency assumptions, the methods produce different results when testing for global clustering. Conclusion The comparative analyses of real data sets by different statistical methods provides insight into directions for further research. We suggest a research program designed around examining real data sets to guide focused investigation of relevant features using simulated data, for the purpose of understanding how to interpret statistical methods applied to epidemiological data with a spatial component.
Six Sigma methods applied to cryogenic coolers assembly line
Ventre, Jean-Marc; Germain-Lacour, Michel; Martin, Jean-Yves; Cauquil, Jean-Marc; Benschop, Tonny; Griot, René
2009-05-01
Six Sigma method have been applied to manufacturing process of a rotary Stirling cooler: RM2. Name of the project is NoVa as main goal of the Six Sigma approach is to reduce variability (No Variability). Project has been based on the DMAIC guideline following five stages: Define, Measure, Analyse, Improve, Control. Objective has been set on the rate of coolers succeeding performance at first attempt with a goal value of 95%. A team has been gathered involving people and skills acting on the RM2 manufacturing line. Measurement System Analysis (MSA) has been applied to test bench and results after R&R gage show that measurement is one of the root cause for variability in RM2 process. Two more root causes have been identified by the team after process mapping analysis: regenerator filling factor and cleaning procedure. Causes for measurement variability have been identified and eradicated as shown by new results from R&R gage. Experimental results show that regenerator filling factor impacts process variability and affects yield. Improved process haven been set after new calibration process for test bench, new filling procedure for regenerator and an additional cleaning stage have been implemented. The objective for 95% coolers succeeding performance test at first attempt has been reached and kept for a significant period. RM2 manufacturing process is now managed according to Statistical Process Control based on control charts. Improvement in process capability have enabled introduction of sample testing procedure before delivery.
Reflections on Mixing Methods in Applied Linguistics Research
Hashemi, Mohammad R.
2012-01-01
This commentary advocates the use of mixed methods research--that is the integration of qualitative and quantitative methods in a single study--in applied linguistics. Based on preliminary findings from a research project in progress, some reflections on the current practice of mixing methods as a new trend in applied linguistics are put forward.…
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.
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 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.
Applying homotopy analysis method for solving differential-difference equation
International Nuclear Information System (INIS)
Wang Zhen; Zou Li; Zhang Hongqing
2007-01-01
In this Letter, we apply the homotopy analysis method to solving the differential-difference equations. A simple but typical example is applied to illustrate the validity and the great potential of the generalized homotopy analysis method in solving differential-difference equation. Comparisons are made between the results of the proposed method and exact solutions. The results show that the homotopy analysis method is an attractive method in solving the differential-difference equations
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.
Applying Statistical Design to Control the Risk of Over-Design with Stochastic Simulation
Directory of Open Access Journals (Sweden)
Yi Wu
2010-02-01
Full Text Available By comparing a hard real-time system and a soft real-time system, this article elicits the risk of over-design in soft real-time system designing. To deal with this risk, a novel concept of statistical design is proposed. The statistical design is the process accurately accounting for and mitigating the effects of variation in part geometry and other environmental conditions, while at the same time optimizing a target performance factor. However, statistical design can be a very difficult and complex task when using clas-sical mathematical methods. Thus, a simulation methodology to optimize the design is proposed in order to bridge the gap between real-time analysis and optimization for robust and reliable system design.
Menzerath-Altmann Law: Statistical Mechanical Interpretation as Applied to a Linguistic Organization
Eroglu, Sertac
2014-10-01
The distribution behavior described by the empirical Menzerath-Altmann law is frequently encountered during the self-organization of linguistic and non-linguistic natural organizations at various structural levels. This study presents a statistical mechanical derivation of the law based on the analogy between the classical particles of a statistical mechanical organization and the distinct words of a textual organization. The derived model, a transformed (generalized) form of the Menzerath-Altmann model, was termed as the statistical mechanical Menzerath-Altmann model. The derived model allows interpreting the model parameters in terms of physical concepts. We also propose that many organizations presenting the Menzerath-Altmann law behavior, whether linguistic or not, can be methodically examined by the transformed distribution model through the properly defined structure-dependent parameter and the energy associated states.
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
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...
Robust functional statistics applied to Probability Density Function shape screening of sEMG data.
Boudaoud, S; Rix, H; Al Harrach, M; Marin, F
2014-01-01
Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.
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...
The Bayesian statistical decision theory applied to the optimization of generating set maintenance
International Nuclear Information System (INIS)
Procaccia, H.; Cordier, R.; Muller, S.
1994-11-01
The difficulty in RCM methodology is the allocation of a new periodicity of preventive maintenance on one equipment when a critical failure has been identified: until now this new allocation has been based on the engineer's judgment, and one must wait for a full cycle of feedback experience before to validate it. Statistical decision theory could be a more rational alternative for the optimization of preventive maintenance periodicity. This methodology has been applied to inspection and maintenance optimization of cylinders of diesel generator engines of 900 MW nuclear plants, and has shown that previous preventive maintenance periodicity can be extended. (authors). 8 refs., 5 figs
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
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.
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
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.
International Nuclear Information System (INIS)
Porch, W.M.; Dickerson, M.H.
1976-08-01
Continuous monitoring of extensive meteorological instrument arrays is a requirement in the study of important mesoscale atmospheric phenomena. The phenomena include pollution transport prediction from continuous area sources, or one time releases of toxic materials and wind energy prospecting in areas of topographic enhancement of the wind. Quality control techniques that can be applied to these data to determine if the instruments are operating within their prescribed tolerances were investigated. Savannah River Plant data were analyzed with both independent and comparative statistical techniques. The independent techniques calculate the mean, standard deviation, moments about the mean, kurtosis, skewness, probability density distribution, cumulative probability and power spectra. The comparative techniques include covariance, cross-spectral analysis and two dimensional probability density. At present the calculating and plotting routines for these statistical techniques do not reside in a single code so it is difficult to ascribe independent memory size and computation time accurately. However, given the flexibility of a data system which includes simple and fast running statistics at the instrument end of the data network (ASF) and more sophisticated techniques at the computational end (ACF) a proper balance will be attained. These techniques are described in detail and preliminary results are presented
2010-10-01
... 45 Public Welfare 2 2010-10-01 2010-10-01 false What statistical and narrative reporting... (IV-D) PROGRAM Statistical and Narrative Reporting Requirements § 309.170 What statistical and narrative reporting requirements apply to Tribal IV-D programs? (a) Tribes and Tribal organizations...
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
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...
Printing method and printer used for applying this method
2006-01-01
The invention pertains to a method for transferring ink to a receiving material using an inkjet printer having an ink chamber (10) with a nozzle (8) and an electromechanical transducer (16) in cooperative connection with the ink chamber, comprising actuating the transducer to generate a pressure
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...
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
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.
Ranaie, Mehrdad; Soffianian, Alireza; Pourmanafi, Saeid; Mirghaffari, Noorollah; Tarkesh, Mostafa
2018-03-01
In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other.
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.
DEFF Research Database (Denmark)
Madsen, Tobias
2017-01-01
In the present thesis I develop, implement and apply statistical methods for detecting genomic elements implicated in cancer development and progression. This is done in two separate bodies of work. The first uses the somatic mutation burden to distinguish cancer driver mutations from passenger m...
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....
International Nuclear Information System (INIS)
Villani, N.; Noel, A.; Villani, N.; Gerard, K.; Marchesi, V.; Huger, S.; Noel, A.; Francois, P.
2010-01-01
Purpose The first purpose of this study was to illustrate the contribution of statistical process control for a better security in intensity modulated radiotherapy (I.M.R.T.) treatments. This improvement is possible by controlling the dose delivery process, characterized by pretreatment quality control results. So, it is necessary to put under control portal dosimetry measurements (currently, the ionisation chamber measurements were already monitored by statistical process control thanks to statistical process control tools). The second objective was to state whether it is possible to substitute ionisation chamber with portal dosimetry in order to optimize time devoted to pretreatment quality control. Patients and methods At Alexis-Vautrin center, pretreatment quality controls in I.M.R.T. for prostate and head and neck treatments were performed for each beam of each patient. These controls were made with an ionisation chamber, which is the reference detector for the absolute dose measurement, and with portal dosimetry for the verification of dose distribution. Statistical process control is a statistical analysis method, coming from industry, used to control and improve the studied process quality. It uses graphic tools as control maps to follow-up process, warning the operator in case of failure, and quantitative tools to evaluate the process toward its ability to respect guidelines: this is the capability study. The study was performed on 450 head and neck beams and on 100 prostate beams. Results Control charts, showing drifts, both slow and weak, and also both strong and fast, of mean and standard deviation have been established and have shown special cause introduced (manual shift of the leaf gap of the multi-leaf collimator). Correlation between dose measured at one point, given with the E.P.I.D. and the ionisation chamber has been evaluated at more than 97% and disagreement cases between the two measurements were identified. Conclusion The study allowed to
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
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.
Mascaró, Maite; Sacristán, Ana Isabel; Rufino, Marta M.
2016-01-01
For the past 4 years, we have been involved in a project that aims to enhance the teaching and learning of experimental analysis and statistics, of environmental and biological sciences students, through computational programming activities (using R code). In this project, through an iterative design, we have developed sequences of R-code-based…
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)
Graph theory applied to noise and vibration control in statistical energy analysis models.
Guasch, Oriol; Cortés, Lluís
2009-06-01
A fundamental aspect of noise and vibration control in statistical energy analysis (SEA) models consists in first identifying and then reducing the energy flow paths between subsystems. In this work, it is proposed to make use of some results from graph theory to address both issues. On the one hand, linear and path algebras applied to adjacency matrices of SEA graphs are used to determine the existence of any order paths between subsystems, counting and labeling them, finding extremal paths, or determining the power flow contributions from groups of paths. On the other hand, a strategy is presented that makes use of graph cut algorithms to reduce the energy flow from a source subsystem to a receiver one, modifying as few internal and coupling loss factors as possible.
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
Discrimination symbol applying method for sintered nuclear fuel product
International Nuclear Information System (INIS)
Ishizaki, Jin
1998-01-01
The present invention provides a symbol applying method for applying discrimination information such as an enrichment degree on the end face of a sintered nuclear product. Namely, discrimination symbols of information of powders are applied by a sintering aid to the end face of a molded member formed by molding nuclear fuel powders under pressure. Then, the molded product is sintered. The sintering aid comprises aluminum oxide, a mixture of aluminum oxide and silicon dioxide, aluminum hydride or aluminum stearate alone or in admixture. As an applying means of the sintering aid, discrimination symbols of information of powders are drawn by an isostearic acid on the end face of the molded product, and the sintering aid is sprayed thereto, or the sintering aid is applied directly, or the sintering aid is suspended in isostearic acid, and the suspension is applied with a brush. As a result, visible discrimination information can be applied to the sintered member easily. (N.H.)
Applied statistical training to strengthen analysis and health research capacity in Rwanda.
Thomson, Dana R; Semakula, Muhammed; Hirschhorn, Lisa R; Murray, Megan; Ndahindwa, Vedaste; Manzi, Anatole; Mukabutera, Assumpta; Karema, Corine; Condo, Jeanine; Hedt-Gauthier, Bethany
2016-09-29
To guide efficient investment of limited health resources in sub-Saharan Africa, local researchers need to be involved in, and guide, health system and policy research. While extensive survey and census data are available to health researchers and program officers in resource-limited countries, local involvement and leadership in research is limited due to inadequate experience, lack of dedicated research time and weak interagency connections, among other challenges. Many research-strengthening initiatives host prolonged fellowships out-of-country, yet their approaches have not been evaluated for effectiveness in involvement and development of local leadership in research. We developed, implemented and evaluated a multi-month, deliverable-driven, survey analysis training based in Rwanda to strengthen skills of five local research leaders, 15 statisticians, and a PhD candidate. Research leaders applied with a specific research question relevant to country challenges and committed to leading an analysis to publication. Statisticians with prerequisite statistical training and experience with a statistical software applied to participate in class-based trainings and complete an assigned analysis. Both statisticians and research leaders were provided ongoing in-country mentoring for analysis and manuscript writing. Participants reported a high level of skill, knowledge and collaborator development from class-based trainings and out-of-class mentorship that were sustained 1 year later. Five of six manuscripts were authored by multi-institution teams and submitted to international peer-reviewed scientific journals, and three-quarters of the participants mentored others in survey data analysis or conducted an additional survey analysis in the year following the training. Our model was effective in utilizing existing survey data and strengthening skills among full-time working professionals without disrupting ongoing work commitments and using few resources. Critical to our
Building "Applied Linguistic Historiography": Rationale, Scope, and Methods
Smith, Richard
2016-01-01
In this article I argue for the establishment of "Applied Linguistic Historiography" (ALH), that is, a new domain of enquiry within applied linguistics involving a rigorous, scholarly, and self-reflexive approach to historical research. Considering issues of rationale, scope, and methods in turn, I provide reasons why ALH is needed and…
Statistical fault diagnosis of wind turbine drivetrain applied to a 5MW floating wind turbine
DEFF Research Database (Denmark)
Ghane, Mahdi; Nejad, Amir R.; Blanke, Mogens
2016-01-01
to prevent them to develop into failure, statistical change detection is used in this paper. The Cumulative Sum Method (CUSUM) is employed to detect possible defects in the downwind main bearing. A high fidelity gearbox model on a 5-MW spar-type wind turbine is used to generate data for fault-free and faulty...... conditions of the bearing at the rated wind speed and the associated wave condition. Acceleration measurements are utilized to find residuals used to indirectly detect damages in the bearing. Residuals are found to be nonGaussian, following a t-distribution with multivariable characteristic parameters...
Villani, N; Gérard, K; Marchesi, V; Huger, S; François, P; Noël, A
2010-06-01
The first purpose of this study was to illustrate the contribution of statistical process control for a better security in intensity modulated radiotherapy (IMRT) treatments. This improvement is possible by controlling the dose delivery process, characterized by pretreatment quality control results. So, it is necessary to put under control portal dosimetry measurements (currently, the ionisation chamber measurements were already monitored by statistical process control thanks to statistical process control tools). The second objective was to state whether it is possible to substitute ionisation chamber with portal dosimetry in order to optimize time devoted to pretreatment quality control. At Alexis-Vautrin center, pretreatment quality controls in IMRT for prostate and head and neck treatments were performed for each beam of each patient. These controls were made with an ionisation chamber, which is the reference detector for the absolute dose measurement, and with portal dosimetry for the verification of dose distribution. Statistical process control is a statistical analysis method, coming from industry, used to control and improve the studied process quality. It uses graphic tools as control maps to follow-up process, warning the operator in case of failure, and quantitative tools to evaluate the process toward its ability to respect guidelines: this is the capability study. The study was performed on 450 head and neck beams and on 100 prostate beams. Control charts, showing drifts, both slow and weak, and also both strong and fast, of mean and standard deviation have been established and have shown special cause introduced (manual shift of the leaf gap of the multileaf collimator). Correlation between dose measured at one point, given with the EPID and the ionisation chamber has been evaluated at more than 97% and disagreement cases between the two measurements were identified. The study allowed to demonstrate the feasibility to reduce the time devoted to
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
Applying Mixed Methods Research at the Synthesis Level: An Overview
Heyvaert, Mieke; Maes, Bea; Onghena, Patrick
2011-01-01
Historically, qualitative and quantitative approaches have been applied relatively separately in synthesizing qualitative and quantitative evidence, respectively, in several research domains. However, mixed methods approaches are becoming increasingly popular nowadays, and practices of combining qualitative and quantitative research components at…
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...
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
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...
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
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.
International Nuclear Information System (INIS)
Pirkle, F.L.; Stablein, N.K.; Howell, J.A.; Wecksung, G.W.; Duran, B.S.
1982-11-01
One objective of the aerial radiometric surveys flown as part of the US Department of Energy's National Uranium Resource Evaluation (NURE) program was to ascertain the regional distribution of near-surface radioelement abundances. Some method for identifying groups of observations with similar radioelement values was therefore required. It is shown in this report that cluster analysis can identify such groups even when no a priori knowledge of the geology of an area exists. A method of convergent k-means cluster analysis coupled with a hierarchical cluster analysis is used to classify 6991 observations (three radiometric variables at each observation location) from the Precambrian rocks of the Copper Mountain, Wyoming, area. Another method, one that combines a principal components analysis with a convergent k-means analysis, is applied to the same data. These two methods are compared with a convergent k-means analysis that utilizes available geologic knowledge. All three methods identify four clusters. Three of the clusters represent background values for the Precambrian rocks of the area, and one represents outliers (anomalously high 214 Bi). A segmentation of the data corresponding to geologic reality as discovered by other methods has been achieved based solely on analysis of aerial radiometric data. The techniques employed are composites of classical clustering methods designed to handle the special problems presented by large data sets. 20 figures, 7 tables
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.
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.
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
Statistical tools applied for the reduction of the defect rate of coffee degassing valves
Directory of Open Access Journals (Sweden)
Giorgio Olmi
2015-04-01
Full Text Available Coffee is a very common beverage exported all over the world: just after roasting, coffee beans are packed in plastic or paper bags, which then experience long transfers with long storage times. Fresh roasted coffee emits large amounts of CO2 for several weeks. This gas must be gradually released, to prevent package over-inflation and to preserve aroma, moreover beans must be protected from oxygen coming from outside. Therefore, one-way degassing valves are applied to each package: their correct functionality is strictly related to the interference coupling between their bodies and covers and to the correct assembly of the other involved parts. This work takes inspiration from an industrial problem: a company that assembles valve components, supplied by different manufacturers, observed a high level of defect rate, affecting its valve production. An integrated approach, consisting in the adoption of quality charts, in an experimental campaign for the dimensional analysis of the mating parts and in the statistical processing of the data, was necessary to tackle the question. In particular, a simple statistical tool was made available to predict the defect rate and to individuate the best strategy for its reduction. The outcome was that requiring a strict protocol, regarding the combinations of parts from different manufacturers for assembly, would have been almost ineffective. Conversely, this study led to the individuation of the weak point in the manufacturing process of the mating components and to the suggestion of a slight improvement to be performed, with the final result of a significant (one order of magnitude decrease of the defect rate.
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.
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.
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
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...
Murphy, Thomas; Schwedock, Julie; Nguyen, Kham; Mills, Anna; Jones, David
2015-01-01
New recommendations for the validation of rapid microbiological methods have been included in the revised Technical Report 33 release from the PDA. The changes include a more comprehensive review of the statistical methods to be used to analyze data obtained during validation. This case study applies those statistical methods to accuracy, precision, ruggedness, and equivalence data obtained using a rapid microbiological methods system being evaluated for water bioburden testing. Results presented demonstrate that the statistical methods described in the PDA Technical Report 33 chapter can all be successfully applied to the rapid microbiological method data sets and gave the same interpretation for equivalence to the standard method. The rapid microbiological method was in general able to pass the requirements of PDA Technical Report 33, though the study shows that there can be occasional outlying results and that caution should be used when applying statistical methods to low average colony-forming unit values. Prior to use in a quality-controlled environment, any new method or technology has to be shown to work as designed by the manufacturer for the purpose required. For new rapid microbiological methods that detect and enumerate contaminating microorganisms, additional recommendations have been provided in the revised PDA Technical Report No. 33. The changes include a more comprehensive review of the statistical methods to be used to analyze data obtained during validation. This paper applies those statistical methods to analyze accuracy, precision, ruggedness, and equivalence data obtained using a rapid microbiological method system being validated for water bioburden testing. The case study demonstrates that the statistical methods described in the PDA Technical Report No. 33 chapter can be successfully applied to rapid microbiological method data sets and give the same comparability results for similarity or difference as the standard method. © PDA, Inc
Statistical Methods for Comparative Phenomics Using High-Throughput Phenotype Microarrays
Sturino, Joseph
2010-01-24
We propose statistical methods for comparing phenomics data generated by the Biolog Phenotype Microarray (PM) platform for high-throughput phenotyping. Instead of the routinely used visual inspection of data with no sound inferential basis, we develop two approaches. The first approach is based on quantifying the distance between mean or median curves from two treatments and then applying a permutation test; we also consider a permutation test applied to areas under mean curves. The second approach employs functional principal component analysis. Properties of the proposed methods are investigated on both simulated data and data sets from the PM platform.
Electronic-projecting Moire method applying CBR-technology
Kuzyakov, O. N.; Lapteva, U. V.; Andreeva, M. A.
2018-01-01
Electronic-projecting method based on Moire effect for examining surface topology is suggested. Conditions of forming Moire fringes and their parameters’ dependence on reference parameters of object and virtual grids are analyzed. Control system structure and decision-making subsystem are elaborated. Subsystem execution includes CBR-technology, based on applying case base. The approach related to analysing and forming decision for each separate local area with consequent formation of common topology map is applied.
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
Palazón, L; Navas, A
2017-06-01
Information on sediment contribution and transport dynamics from the contributing catchments is needed to develop management plans to tackle environmental problems related with effects of fine sediment as reservoir siltation. In this respect, the fingerprinting technique is an indirect technique known to be valuable and effective for sediment source identification in river catchments. Large variability in sediment delivery was found in previous studies in the Barasona catchment (1509 km 2 , Central Spanish Pyrenees). Simulation results with SWAT and fingerprinting approaches identified badlands and agricultural uses as the main contributors to sediment supply in the reservoir. In this study the Kruskal-Wallis H-test and (3) principal components analysis. Source contribution results were different between assessed options with the greatest differences observed for option using #3, including the two step process: principal components analysis and discriminant function analysis. The characteristics of the solutions by the applied mixing model and the conceptual understanding of the catchment showed that the most reliable solution was achieved using #2, the two step process of Kruskal-Wallis H-test and discriminant function analysis. The assessment showed the importance of the statistical procedure used to define the optimum composite fingerprint for sediment fingerprinting applications. Copyright © 2016 Elsevier Ltd. All rights reserved.
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.
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.
A Lagrangian meshfree method applied to linear and nonlinear elasticity.
Walker, Wade A
2017-01-01
The repeated replacement method (RRM) is a Lagrangian meshfree method which we have previously applied to the Euler equations for compressible fluid flow. In this paper we present new enhancements to RRM, and we apply the enhanced method to both linear and nonlinear elasticity. We compare the results of ten test problems to those of analytic solvers, to demonstrate that RRM can successfully simulate these elastic systems without many of the requirements of traditional numerical methods such as numerical derivatives, equation system solvers, or Riemann solvers. We also show the relationship between error and computational effort for RRM on these systems, and compare RRM to other methods to highlight its strengths and weaknesses. And to further explain the two elastic equations used in the paper, we demonstrate the mathematical procedure used to create Riemann and Sedov-Taylor solvers for them, and detail the numerical techniques needed to embody those solvers in code.
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
McKinley, C. C.; Scudder, R.; Thomas, D. J.
2016-12-01
The Neodymium Isotopic composition (Nd IC) of oxide coatings has been applied as a tracer of water mass composition and used to address fundamental questions about past ocean conditions. The leached authigenic oxide coating from marine sediment is widely assumed to reflect the dissolved trace metal composition of the bottom water interacting with sediment at the seafloor. However, recent studies have shown that readily reducible sediment components, in addition to trace metal fluxes from the pore water, are incorporated into the bottom water, influencing the trace metal composition of leached oxide coatings. This challenges the prevailing application of the authigenic oxide Nd IC as a proxy of seawater composition. Therefore, it is important to identify the component end-members that create sediments of different lithology and determine if, or how they might contribute to the Nd IC of oxide coatings. To investigate lithologic influence on the results of sequential leaching, we selected two sites with complete bulk sediment statistical characterization. Site U1370 in the South Pacific Gyre, is predominantly composed of Rhyolite ( 60%) and has a distinguishable ( 10%) Fe-Mn Oxyhydroxide component (Dunlea et al., 2015). Site 1149 near the Izu-Bonin-Arc is predominantly composed of dispersed ash ( 20-50%) and eolian dust from Asia ( 50-80%) (Scudder et al., 2014). We perform a two-step leaching procedure: a 14 mL of 0.02 M hydroxylamine hydrochloride (HH) in 20% acetic acid buffered to a pH 4 for one hour, targeting metals bound to Fe- and Mn- oxides fractions, and a second HH leach for 12 hours, designed to remove any remaining oxides from the residual component. We analyze all three resulting fractions for a large suite of major, trace and rare earth elements, a sub-set of the samples are also analyzed for Nd IC. We use multivariate statistical analyses of the resulting geochemical data to identify how each component of the sediment partitions across the sequential
Directory of Open Access Journals (Sweden)
Land Walker H
2011-01-01
Full Text Available Abstract Background When investigating covariate interactions and group associations with standard regression analyses, the relationship between the response variable and exposure may be difficult to characterize. When the relationship is nonlinear, linear modeling techniques do not capture the nonlinear information content. Statistical learning (SL techniques with kernels are capable of addressing nonlinear problems without making parametric assumptions. However, these techniques do not produce findings relevant for epidemiologic interpretations. A simulated case-control study was used to contrast the information embedding characteristics and separation boundaries produced by a specific SL technique with logistic regression (LR modeling representing a parametric approach. The SL technique was comprised of a kernel mapping in combination with a perceptron neural network. Because the LR model has an important epidemiologic interpretation, the SL method was modified to produce the analogous interpretation and generate odds ratios for comparison. Results The SL approach is capable of generating odds ratios for main effects and risk factor interactions that better capture nonlinear relationships between exposure variables and outcome in comparison with LR. Conclusions The integration of SL methods in epidemiology may improve both the understanding and interpretation of complex exposure/disease relationships.
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
Gene flow analysis method, the D-statistic, is robust in a wide parameter space.
Zheng, Yichen; Janke, Axel
2018-01-08
We evaluated the sensitivity of the D-statistic, a parsimony-like method widely used to detect gene flow between closely related species. This method has been applied to a variety of taxa with a wide range of divergence times. However, its parameter space and thus its applicability to a wide taxonomic range has not been systematically studied. Divergence time, population size, time of gene flow, distance of outgroup and number of loci were examined in a sensitivity analysis. The sensitivity study shows that the primary determinant of the D-statistic is the relative population size, i.e. the population size scaled by the number of generations since divergence. This is consistent with the fact that the main confounding factor in gene flow detection is incomplete lineage sorting by diluting the signal. The sensitivity of the D-statistic is also affected by the direction of gene flow, size and number of loci. In addition, we examined the ability of the f-statistics, [Formula: see text] and [Formula: see text], to estimate the fraction of a genome affected by gene flow; while these statistics are difficult to implement to practical questions in biology due to lack of knowledge of when the gene flow happened, they can be used to compare datasets with identical or similar demographic background. The D-statistic, as a method to detect gene flow, is robust against a wide range of genetic distances (divergence times) but it is sensitive to population size. The D-statistic should only be applied with critical reservation to taxa where population sizes are large relative to branch lengths in generations.
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
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
Applying the Taguchi method for optimized fabrication of bovine ...
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2008-02-19
Feb 19, 2008 ... Nanobiotechnology Research Lab., School of Chemical Engineering, Babol University of Technology, Po.Box: 484, ... nanoparticle by applying the Taguchi method with characterization of the ... of BSA/ethanol and organic solvent adding rate. ... Sodium aside and all other chemicals were purchased from.
Yakunin, A. G.; Hussein, H. M.
2018-01-01
The article shows how the known statistical methods, which are widely used in solving financial problems and a number of other fields of science and technology, can be effectively applied after minor modification for solving such problems in climate and environment monitoring systems, as the detection of anomalies in the form of abrupt changes in signal levels, the occurrence of positive and negative outliers and the violation of the cycle form in periodic processes.
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
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.
Statistical fault diagnosis of wind turbine drivetrain applied to a 5MW floating wind turbine
Ghane, Mahdi; Nejad, Amir R.; Blanke, Mogens; Gao, Zhen; Moan, Torgeir
2016-09-01
Deployment of large scale wind turbine parks, in particular offshore, requires well organized operation and maintenance strategies to make it as competitive as the classical electric power stations. It is important to ensure systems are safe, profitable, and cost-effective. In this regards, the ability to detect, isolate, estimate, and prognose faults plays an important role. One of the critical wind turbine components is the gearbox. Failures in the gearbox are costly both due to the cost of the gearbox itself and also due to high repair downtime. In order to detect faults as fast as possible to prevent them to develop into failure, statistical change detection is used in this paper. The Cumulative Sum Method (CUSUM) is employed to detect possible defects in the downwind main bearing. A high fidelity gearbox model on a 5-MW spar-type wind turbine is used to generate data for fault-free and faulty conditions of the bearing at the rated wind speed and the associated wave condition. Acceleration measurements are utilized to find residuals used to indirectly detect damages in the bearing. Residuals are found to be nonGaussian, following a t-distribution with multivariable characteristic parameters. The results in this paper show how the diagnostic scheme can detect change with desired false alarm and detection probabilities.
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.
Aircraft operability methods applied to space launch vehicles
Young, Douglas
1997-01-01
The commercial space launch market requirement for low vehicle operations costs necessitates the application of methods and technologies developed and proven for complex aircraft systems. The ``building in'' of reliability and maintainability, which is applied extensively in the aircraft industry, has yet to be applied to the maximum extent possible on launch vehicles. Use of vehicle system and structural health monitoring, automated ground systems and diagnostic design methods derived from aircraft applications support the goal of achieving low cost launch vehicle operations. Transforming these operability techniques to space applications where diagnostic effectiveness has significantly different metrics is critical to the success of future launch systems. These concepts will be discussed with reference to broad launch vehicle applicability. Lessons learned and techniques used in the adaptation of these methods will be outlined drawing from recent aircraft programs and implementation on phase 1 of the X-33/RLV technology development program.
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.
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
Magnetic stirring welding method applied to nuclear power plant
International Nuclear Information System (INIS)
Hirano, Kenji; Watando, Masayuki; Morishige, Norio; Enoo, Kazuhide; Yasuda, Yuuji
2002-01-01
In construction of a new nuclear power plant, carbon steel and stainless steel are used as base materials for the bottom linear plate of Reinforced Concrete Containment Vessel (RCCV) to achieve maintenance-free requirement, securing sufficient strength of structure. However, welding such different metals is difficult by ordinary method. To overcome the difficulty, the automated Magnetic Stirring Welding (MSW) method that can demonstrate good welding performance was studied for practical use, and weldability tests showed the good results. Based on the study, a new welding device for the MSW method was developed to apply it weld joints of different materials, and it practically used in part of a nuclear power plant. (author)
The Storm of the Century! Promoting Student Enthusiasm for Applied Statistics
Fawcett, Lee; Newman, Keith
2017-01-01
This article describes a hands-on activity that has been used with students aged 12-18 years to promote the study of Statistics. We believe there is evidence to suggest an increase in student enthusiasm for Statistics at school, within the Mathematics curriculum, but also within other subjects such as Geography. We also believe that the use of…
Linear algebraic methods applied to intensity modulated radiation therapy.
Crooks, S M; Xing, L
2001-10-01
Methods of linear algebra are applied to the choice of beam weights for intensity modulated radiation therapy (IMRT). It is shown that the physical interpretation of the beam weights, target homogeneity and ratios of deposited energy can be given in terms of matrix equations and quadratic forms. The methodology of fitting using linear algebra as applied to IMRT is examined. Results are compared with IMRT plans that had been prepared using a commercially available IMRT treatment planning system and previously delivered to cancer patients.
Directory of Open Access Journals (Sweden)
A. R. Rote
2010-01-01
Full Text Available Three new simple, economic spectrophotometric methods were developed and validated for the estimation of nabumetone in bulk and tablet dosage form. First method includes determination of nabumetone at absorption maxima 330 nm, second method applied was area under curve for analysis of nabumetone in the wavelength range of 326-334 nm and third method was First order derivative spectra with scaling factor 4. Beer law obeyed in the concentration range of 10-30 μg/mL for all three methods. The correlation coefficients were found to be 0.9997, 0.9998 and 0.9998 by absorption maxima, area under curve and first order derivative spectra. Results of analysis were validated statistically and by performing recovery studies. The mean percent recoveries were found satisfactory for all three methods. The developed methods were also compared statistically using one way ANOVA. The proposed methods have been successfully applied for the estimation of nabumetone in bulk and pharmaceutical tablet dosage form.
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.
Methods of applied mathematics with a software overview
Davis, Jon H
2016-01-01
This textbook, now in its second edition, provides students with a firm grasp of the fundamental notions and techniques of applied mathematics as well as the software skills to implement them. The text emphasizes the computational aspects of problem solving as well as the limitations and implicit assumptions inherent in the formal methods. Readers are also given a sense of the wide variety of problems in which the presented techniques are useful. Broadly organized around the theme of applied Fourier analysis, the treatment covers classical applications in partial differential equations and boundary value problems, and a substantial number of topics associated with Laplace, Fourier, and discrete transform theories. Some advanced topics are explored in the final chapters such as short-time Fourier analysis and geometrically based transforms applicable to boundary value problems. The topics covered are useful in a variety of applied fields such as continuum mechanics, mathematical physics, control theory, and si...
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
Simulating European wind power generation applying statistical downscaling to reanalysis data
International Nuclear Information System (INIS)
González-Aparicio, I.; Monforti, F.; Volker, P.; Zucker, A.; Careri, F.; Huld, T.; Badger, J.
2017-01-01
Highlights: •Wind speed spatial resolution highly influences calculated wind power peaks and ramps. •Reduction of wind power generation uncertainties using statistical downscaling. •Publicly available dataset of wind power generation hourly time series at NUTS2. -- Abstract: The growing share of electricity production from solar and mainly wind resources constantly increases the stochastic nature of the power system. Modelling the high share of renewable energy sources – and in particular wind power – crucially depends on the adequate representation of the intermittency and characteristics of the wind resource which is related to the accuracy of the approach in converting wind speed data into power values. One of the main factors contributing to the uncertainty in these conversion methods is the selection of the spatial resolution. Although numerical weather prediction models can simulate wind speeds at higher spatial resolution (up to 1 × 1 km) than a reanalysis (generally, ranging from about 25 km to 70 km), they require high computational resources and massive storage systems: therefore, the most common alternative is to use the reanalysis data. However, local wind features could not be captured by the use of a reanalysis technique and could be translated into misinterpretations of the wind power peaks, ramping capacities, the behaviour of power prices, as well as bidding strategies for the electricity market. This study contributes to the understanding what is captured by different wind speeds spatial resolution datasets, the importance of using high resolution data for the conversion into power and the implications in power system analyses. It is proposed a methodology to increase the spatial resolution from a reanalysis. This study presents an open access renewable generation time series dataset for the EU-28 and neighbouring countries at hourly intervals and at different geographical aggregation levels (country, bidding zone and administrative
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.
A method for statistical steady state thermal analysis of reactor cores
International Nuclear Information System (INIS)
Whetton, P.A.
1980-01-01
This paper presents a method for performing a statistical steady state thermal analysis of a reactor core. The technique is only outlined here since detailed thermal equations are dependent on the core geometry. The method has been applied to a pressurised water reactor core and the results are presented for illustration purposes. Random hypothetical cores are generated using the Monte-Carlo method. The technique shows that by splitting the parameters into two types, denoted core-wise and in-core, the Monte Carlo method may be used inexpensively. The idea of using extremal statistics to characterise the low probability events (i.e. the tails of a distribution) is introduced together with a method of forming the final probability distribution. After establishing an acceptable probability of exceeding a thermal design criterion, the final probability distribution may be used to determine the corresponding thermal response value. If statistical and deterministic (i.e. conservative) thermal response values are compared, information on the degree of pessimism in the deterministic method of analysis may be inferred and the restrictive performance limitations imposed by this method relieved. (orig.)
Which DTW Method Applied to Marine Univariate Time Series Imputation
Phan , Thi-Thu-Hong; Caillault , Émilie; Lefebvre , Alain; Bigand , André
2017-01-01
International audience; Missing data are ubiquitous in any domains of applied sciences. Processing datasets containing missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Therefore, the aim of this paper is to build a framework for filling missing values in univariate time series and to perform a comparison of different similarity metrics used for the imputation task. This allows to suggest the most suitable methods for the imp...
Applying Qualitative Research Methods to Narrative Knowledge Engineering
O'Neill, Brian; Riedl, Mark
2014-01-01
We propose a methodology for knowledge engineering for narrative intelligence systems, based on techniques used to elicit themes in qualitative methods research. Our methodology uses coding techniques to identify actions in natural language corpora, and uses these actions to create planning operators and procedural knowledge, such as scripts. In an iterative process, coders create a taxonomy of codes relevant to the corpus, and apply those codes to each element of that corpus. These codes can...
APPLYING SPECTROSCOPIC METHODS ON ANALYSES OF HAZARDOUS WASTE
Dobrinić, Julijan; Kunić, Marija; Ciganj, Zlatko
2000-01-01
Abstract The paper presents results of measuring the content of heavy and other metals in waste samples from the hazardous waste disposal site of Sovjak near Rijeka. The preliminary design elaboration and the choice of the waste disposal sanification technology were preceded by the sampling and physico-chemical analyses of disposed waste, enabling its categorization. The following spectroscopic methods were applied on metal content analysis: Atomic absorption spectroscopy (AAS) and plas...
A new method of AHP applied to personal credit evaluation
Institute of Scientific and Technical Information of China (English)
JIANG Ming-hui; XIONG Qi; CAO Jing
2006-01-01
This paper presents a new negative judgment matrix that combines the advantages of the reciprocal judgment matrix and the fuzzy complementary judgment matrix, and then puts forth the properties of this new matrix. In view of these properties, this paper derives a clear sequencing formula for the new negative judgment matrix, which improves the sequencing principle of AHP. Finally, this new method is applied to personal credit evaluation to show its advantages of conciseness and swiftness.
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...
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)
Tips and Tricks for Successful Application of Statistical Methods to Biological Data.
Schlenker, Evelyn
2016-01-01
This chapter discusses experimental design and use of statistics to describe characteristics of data (descriptive statistics) and inferential statistics that test the hypothesis posed by the investigator. Inferential statistics, based on probability distributions, depend upon the type and distribution of the data. For data that are continuous, randomly and independently selected, as well as normally distributed more powerful parametric tests such as Student's t test and analysis of variance (ANOVA) can be used. For non-normally distributed or skewed data, transformation of the data (using logarithms) may normalize the data allowing use of parametric tests. Alternatively, with skewed data nonparametric tests can be utilized, some of which rely on data that are ranked prior to statistical analysis. Experimental designs and analyses need to balance between committing type 1 errors (false positives) and type 2 errors (false negatives). For a variety of clinical studies that determine risk or benefit, relative risk ratios (random clinical trials and cohort studies) or odds ratios (case-control studies) are utilized. Although both use 2 × 2 tables, their premise and calculations differ. Finally, special statistical methods are applied to microarray and proteomics data, since the large number of genes or proteins evaluated increase the likelihood of false discoveries. Additional studies in separate samples are used to verify microarray and proteomic data. Examples in this chapter and references are available to help continued investigation of experimental designs and appropriate data analysis.
Novel biodosimetry methods applied to victims of the Goiania accident
International Nuclear Information System (INIS)
Straume, T.; Langlois, R.G.; Lucas, J.; Jensen, R.H.; Bigbee, W.L.; Ramalho, A.T.; Brandao-Mello, C.E.
1991-01-01
Two biodosimetric methods under development at the Lawrence Livermore National Laboratory were applied to five persons accidentally exposed to a 137Cs source in Goiania, Brazil. The methods used were somatic null mutations at the glycophorin A locus detected as missing proteins on the surface of blood erythrocytes and chromosome translocations in blood lymphocytes detected using fluorescence in-situ hybridization. Biodosimetric results obtained approximately 1 y after the accident using these new and largely unvalidated methods are in general agreement with results obtained immediately after the accident using dicentric chromosome aberrations. Additional follow-up of Goiania accident victims will (1) help provide the information needed to validate these new methods for use in biodosimetry and (2) provide independent estimates of dose
Newton-Krylov methods applied to nonequilibrium radiation diffusion
International Nuclear Information System (INIS)
Knoll, D.A.; Rider, W.J.; Olsen, G.L.
1998-01-01
The authors present results of applying a matrix-free Newton-Krylov method to a nonequilibrium radiation diffusion problem. Here, there is no use of operator splitting, and Newton's method is used to convert the nonlinearities within a time step. Since the nonlinear residual is formed, it is used to monitor convergence. It is demonstrated that a simple Picard-based linearization produces a sufficient preconditioning matrix for the Krylov method, thus elevating the need to form or store a Jacobian matrix for Newton's method. They discuss the possibility that the Newton-Krylov approach may allow larger time steps, without loss of accuracy, as compared to an operator split approach where nonlinearities are not converged within a time step
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.
Statistical process control methods allow the analysis and improvement of anesthesia care.
Fasting, Sigurd; Gisvold, Sven E
2003-10-01
Quality aspects of the anesthetic process are reflected in the rate of intraoperative adverse events. The purpose of this report is to illustrate how the quality of the anesthesia process can be analyzed using statistical process control methods, and exemplify how this analysis can be used for quality improvement. We prospectively recorded anesthesia-related data from all anesthetics for five years. The data included intraoperative adverse events, which were graded into four levels, according to severity. We selected four adverse events, representing important quality and safety aspects, for statistical process control analysis. These were: inadequate regional anesthesia, difficult emergence from general anesthesia, intubation difficulties and drug errors. We analyzed the underlying process using 'p-charts' for statistical process control. In 65,170 anesthetics we recorded adverse events in 18.3%; mostly of lesser severity. Control charts were used to define statistically the predictable normal variation in problem rate, and then used as a basis for analysis of the selected problems with the following results: Inadequate plexus anesthesia: stable process, but unacceptably high failure rate; Difficult emergence: unstable process, because of quality improvement efforts; Intubation difficulties: stable process, rate acceptable; Medication errors: methodology not suited because of low rate of errors. By applying statistical process control methods to the analysis of adverse events, we have exemplified how this allows us to determine if a process is stable, whether an intervention is required, and if quality improvement efforts have the desired effect.
Virial-statistic method for calculation of atom and molecule energies
International Nuclear Information System (INIS)
Borisov, Yu.A.
1977-01-01
A virial-statistical method has been applied to the calculation of the atomization energies of the following molecules: Mo(CO) 6 , Cr(CO) 6 , Fe(CO) 5 , MnH(CO) 5 , CoH(CO) 4 , Ni(CO) 4 . The principles of this method are briefly presented. Calculation results are given for the individual contributions to the atomization energies together with the calculated and experimental atomization energies (D). For the Mo(CO) 6 complex Dsub(calc) = 1759 and Dsub(exp) = 1763 kcal/mole. Calculated and experimental combination heat values for carbonyl complexes are presented. These values are shown to be adequately consistent [ru
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 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...
A comparison of statistical methods for identifying out-of-date systematic reviews.
Directory of Open Access Journals (Sweden)
Porjai Pattanittum
Full Text Available BACKGROUND: Systematic reviews (SRs can provide accurate and reliable evidence, typically about the effectiveness of health interventions. Evidence is dynamic, and if SRs are out-of-date this information may not be useful; it may even be harmful. This study aimed to compare five statistical methods to identify out-of-date SRs. METHODS: A retrospective cohort of SRs registered in the Cochrane Pregnancy and Childbirth Group (CPCG, published between 2008 and 2010, were considered for inclusion. For each eligible CPCG review, data were extracted and "3-years previous" meta-analyses were assessed for the need to update, given the data from the most recent 3 years. Each of the five statistical methods was used, with random effects analyses throughout the study. RESULTS: Eighty reviews were included in this study; most were in the area of induction of labour. The numbers of reviews identified as being out-of-date using the Ottawa, recursive cumulative meta-analysis (CMA, and Barrowman methods were 34, 7, and 7 respectively. No reviews were identified as being out-of-date using the simulation-based power method, or the CMA for sufficiency and stability method. The overall agreement among the three discriminating statistical methods was slight (Kappa = 0.14; 95% CI 0.05 to 0.23. The recursive cumulative meta-analysis, Ottawa, and Barrowman methods were practical according to the study criteria. CONCLUSION: Our study shows that three practical statistical methods could be applied to examine the need to update SRs.
Laepple, Thomas; Jewson, Stephen; Meagher, Jonathan; O'Shay, Adam; Penzer, Jeremy
2007-01-01
We are developing schemes that predict future hurricane numbers by first predicting future sea surface temperatures (SSTs), and then apply the observed statistical relationship between SST and hurricane numbers. As part of this overall goal, in this study we compare the historical performance of three simple statistical methods for making five-year SST forecasts. We also present SST forecasts for 2006-2010 using these methods and compare them to forecasts made from two structural time series ...
Apply of torque method at rationalization of work
Directory of Open Access Journals (Sweden)
Bandurová Miriam
2001-03-01
Full Text Available Aim of the study was to analyse consumption of time for profession - cylinder grinder, by torque method.Method of torque following is used for detection of sorts and size of time slope, on detection of portion of individual sorts of time consumption and cause of time slope. By this way it is possible to find out coefficient of employment and recovery of workers in organizational unit. Advantage of torque survey is low costs on informations acquirement, non-fastidiousness per worker and observer, which is easy trained. It is mentally acceptable method for objects of survey.Finding and detection of reserves in activity of cylinders grinder result of torque was surveys. Loss of time presents till 8% of working time. In 5 - shift service and average occupiying of shift by 4,4 grinder ( from statistic information of service , loss at grinder of cylinders are for whole centre 1,48 worker.According presented information it was recommended to cancel one job place - grinder of cylinders - and reduce state about one grinder. Next job place isn't possible cancel, because grindery of cylinders must to adapt to the grind line by number of polished cylinders in shift and semi - finishing of polished cylinders can not be high for often changes in area of grinding and sortiment changes.By this contribution we confirmed convenience of exploitation of torque method as one of the methods using during the job rationalization.
GPS surveying method applied to terminal area navigation flight experiments
Energy Technology Data Exchange (ETDEWEB)
Murata, M; Shingu, H; Satsushima, K; Tsuji, T; Ishikawa, K; Miyazawa, Y; Uchida, T [National Aerospace Laboratory, Tokyo (Japan)
1993-03-01
With an objective of evaluating accuracy of new landing and navigation systems such as microwave landing guidance system and global positioning satellite (GPS) system, flight experiments are being carried out using experimental aircraft. This aircraft mounts a GPS and evaluates its accuracy by comparing the standard orbits spotted by a Kalman filter from the laser tracing data on the aircraft with the navigation results. The GPS outputs position and speed information from an earth-centered-earth-fixed system called the World Geodetic System, 1984 (WGS84). However, in order to compare the navigation results with output from a reference orbit sensor or other navigation sensor, it is necessary to structure a high-precision reference coordinates system based on the WGS84. A method that applies the GPS phase interference measurement for this problem was proposed, and used actually in analyzing a flight experiment data. As referred to a case of the method having been applied to evaluating an independent navigation accuracy, the method was verified sufficiently effective and reliable not only in navigation method analysis, but also in the aspect of navigational operations. 12 refs., 10 figs., 5 tabs.
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
Methods for model selection in applied science and engineering.
Energy Technology Data Exchange (ETDEWEB)
Field, Richard V., Jr.
2004-10-01
Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be
Analysis of concrete beams using applied element method
Lincy Christy, D.; Madhavan Pillai, T. M.; Nagarajan, Praveen
2018-03-01
The Applied Element Method (AEM) is a displacement based method of structural analysis. Some of its features are similar to that of Finite Element Method (FEM). In AEM, the structure is analysed by dividing it into several elements similar to FEM. But, in AEM, elements are connected by springs instead of nodes as in the case of FEM. In this paper, background to AEM is discussed and necessary equations are derived. For illustrating the application of AEM, it has been used to analyse plain concrete beam of fixed support condition. The analysis is limited to the analysis of 2-dimensional structures. It was found that the number of springs has no much influence on the results. AEM could predict deflection and reactions with reasonable degree of accuracy.
The Lattice Boltzmann Method applied to neutron transport
International Nuclear Information System (INIS)
Erasmus, B.; Van Heerden, F. A.
2013-01-01
In this paper the applicability of the Lattice Boltzmann Method to neutron transport is investigated. One of the main features of the Lattice Boltzmann method is the simultaneous discretization of the phase space of the problem, whereby particles are restricted to move on a lattice. An iterative solution of the operator form of the neutron transport equation is presented here, with the first collision source as the starting point of the iteration scheme. A full description of the discretization scheme is given, along with the quadrature set used for the angular discretization. An angular refinement scheme is introduced to increase the angular coverage of the problem phase space and to mitigate lattice ray effects. The method is applied to a model problem to investigate its applicability to neutron transport and the results are compared to a reference solution calculated, using MCNP. (authors)
Advanced methods for image registration applied to JET videos
Energy Technology Data Exchange (ETDEWEB)
Craciunescu, Teddy, E-mail: teddy.craciunescu@jet.uk [EURATOM-MEdC Association, NILPRP, Bucharest (Romania); Murari, Andrea [Consorzio RFX, Associazione EURATOM-ENEA per la Fusione, Padova (Italy); Gelfusa, Michela [Associazione EURATOM-ENEA – University of Rome “Tor Vergata”, Roma (Italy); Tiseanu, Ion; Zoita, Vasile [EURATOM-MEdC Association, NILPRP, Bucharest (Romania); Arnoux, Gilles [EURATOM/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon (United Kingdom)
2015-10-15
Graphical abstract: - Highlights: • Development of an image registration method for JET IR and fast visible cameras. • Method based on SIFT descriptors and coherent point drift points set registration technique. • Method able to deal with extremely noisy images and very low luminosity images. • Computation time compatible with the inter-shot analysis. - Abstract: The last years have witnessed a significant increase in the use of digital cameras on JET. They are routinely applied for imaging in the IR and visible spectral regions. One of the main technical difficulties in interpreting the data of camera based diagnostics is the presence of movements of the field of view. Small movements occur due to machine shaking during normal pulses while large ones may arise during disruptions. Some cameras show a correlation of image movement with change of magnetic field strength. For deriving unaltered information from the videos and for allowing correct interpretation an image registration method, based on highly distinctive scale invariant feature transform (SIFT) descriptors and on the coherent point drift (CPD) points set registration technique, has been developed. The algorithm incorporates a complex procedure for rejecting outliers. The method has been applied for vibrations correction to videos collected by the JET wide angle infrared camera and for the correction of spurious rotations in the case of the JET fast visible camera (which is equipped with an image intensifier). The method has proved to be able to deal with the images provided by this camera frequently characterized by low contrast and a high level of blurring and noise.
Hamaker, H.C.
1962-01-01
In many fields of inquiry, especially those concerned with living beings, "exact" observations are not possible and it is necessary to investigate the effect of several factors at the same time. This has led to the design of experiments on a statistical basis, in which several factors may be varied
Cheng, P.W.; Kuik, van G.A.M.; Bussel, van G.J.W.; Vrouwenvelder, A.C.W.M.
2002-01-01
Extreme response is an important design variable for wind turbines. The statistical uncertainties concerning the extreme response distribution are simulated here with data concerning physical characteristics obtained from measurements. The extreme responses are the flap moment at the blade root and
An approach to build knowledge base for reactor accident diagnostic system using statistical method
International Nuclear Information System (INIS)
Kohsaka, Atsuo; Yokobayashi, Masao; Matsumoto, Kiyoshi; Fujii, Minoru
1988-01-01
In the development of a rule based expert system, one of key issues is how to build a knowledge base (KB). A systematic approach has been attempted for building an objective KB efficiently. The approach is based on the concept that a prototype KB should first be generated in a systematic way and then it is to be modified and/or improved by expert for practical use. The statistical method, Factor Analysis, was applied to build a prototype KB for the JAERI expert system DISKET using source information obtained from a PWR simulator. The prototype KB was obtained and the inference with this KB was performed against several types of transients. In each diagnosis, the transient type was well identified. From this study, it is concluded that the statistical method used is useful for building a prototype knowledge base. (author)
Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry
2013-08-01
Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.
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...
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...
Jerez, José M; Molina, Ignacio; García-Laencina, Pedro J; Alba, Emilio; Ribelles, Nuria; Martín, Miguel; Franco, Leonardo
2010-10-01
Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. This work evaluates the performance of several statistical and machine learning imputation methods that were used to predict recurrence in patients in an extensive real breast cancer data set. Imputation methods based on statistical techniques, e.g., mean, hot-deck and multiple imputation, and machine learning techniques, e.g., multi-layer perceptron (MLP), self-organisation maps (SOM) and k-nearest neighbour (KNN), were applied to data collected through the "El Álamo-I" project, and the results were then compared to those obtained from the listwise deletion (LD) imputation method. The database includes demographic, therapeutic and recurrence-survival information from 3679 women with operable invasive breast cancer diagnosed in 32 different hospitals belonging to the Spanish Breast Cancer Research Group (GEICAM). The accuracies of predictions on early cancer relapse were measured using artificial neural networks (ANNs), in which different ANNs were estimated using the data sets with imputed missing values. The imputation methods based on machine learning algorithms outperformed imputation statistical methods in the prediction of patient outcome. Friedman's test revealed a significant difference (p=0.0091) in the observed area under the ROC curve (AUC) values, and the pairwise comparison test showed that the AUCs for MLP, KNN and SOM were significantly higher (p=0.0053, p=0.0048 and p=0.0071, respectively) than the AUC from the LD-based prognosis model. The methods based on machine learning techniques were the most suited for the imputation of missing values and led to a significant enhancement of prognosis accuracy compared to imputation methods based on statistical procedures. Copyright © 2010 Elsevier B.V. All rights reserved.
Nuclear method applied in archaeological sites at the Amazon basin
International Nuclear Information System (INIS)
Nicoli, Ieda Gomes; Bernedo, Alfredo Victor Bellido; Latini, Rose Mary
2002-01-01
The aim of this work was to use the nuclear methodology to character pottery discovered inside archaeological sites recognized with circular earth structure in Acre State - Brazil which may contribute to the research in the reconstruction of part of the pre-history of the Amazonic Basin. The sites are located mainly in the Hydrographic Basin of High Purus River. Three of them were strategic chosen to collect the ceramics: Lobao, in Sena Madureira County at north; Alto Alegre in Rio Branco County at east and Xipamanu I, in Xapuri County at south. Neutron Activation Analysis in conjunction with multivariate statistical methods were used for the ceramic characterization and classification. An homogeneous group was established by all the sherds collected from Alto Alegre and was distinct from the other two groups analyzed. Some of the sherds collected from Xipamunu I appeared in Lobao's urns, probably because they had the same fabrication process. (author)
Metrological evaluation of characterization methods applied to nuclear fuels
International Nuclear Information System (INIS)
Faeda, Kelly Cristina Martins; Lameiras, Fernando Soares; Camarano, Denise das Merces; Ferreira, Ricardo Alberto Neto; Migliorini, Fabricio Lima; Carneiro, Luciana Capanema Silva; Silva, Egonn Hendrigo Carvalho
2010-01-01
In manufacturing the nuclear fuel, characterizations are performed in order to assure the minimization of harmful effects. The uranium dioxide is the most used substance as nuclear reactor fuel because of many advantages, such as: high stability even when it is in contact with water at high temperatures, high fusion point, and high capacity to retain fission products. Several methods are used for characterization of nuclear fuels, such as thermogravimetric analysis for the ratio O / U, penetration-immersion method, helium pycnometer and mercury porosimetry for the density and porosity, BET method for the specific surface, chemical analyses for relevant impurities, and the laser flash method for thermophysical properties. Specific tools are needed to control the diameter and the sphericity of the microspheres and the properties of the coating layers (thickness, density, and degree of anisotropy). Other methods can also give information, such as scanning and transmission electron microscopy, X-ray diffraction, microanalysis, and mass spectroscopy of secondary ions for chemical analysis. The accuracy of measurement and level of uncertainty of the resulting data are important. This work describes a general metrological characterization of some techniques applied to the characterization of nuclear fuel. Sources of measurement uncertainty were analyzed. The purpose is to summarize selected properties of UO 2 that have been studied by CDTN in a program of fuel development for Pressurized Water Reactors (PWR). The selected properties are crucial for thermalhydraulic codes to study basic design accidents. The thermal characterization (thermal diffusivity and thermal conductivity) and the penetration immersion method (density and open porosity) of UO 2 samples were focused. The thermal characterization of UO 2 samples was determined by the laser flash method between room temperature and 448 K. The adaptive Monte Carlo Method was used to obtain the endpoints of the
Analysis of Brick Masonry Wall using Applied Element Method
Lincy Christy, D.; Madhavan Pillai, T. M.; Nagarajan, Praveen
2018-03-01
The Applied Element Method (AEM) is a versatile tool for structural analysis. Analysis is done by discretising the structure as in the case of Finite Element Method (FEM). In AEM, elements are connected by a set of normal and shear springs instead of nodes. AEM is extensively used for the analysis of brittle materials. Brick masonry wall can be effectively analyzed in the frame of AEM. The composite nature of masonry wall can be easily modelled using springs. The brick springs and mortar springs are assumed to be connected in series. The brick masonry wall is analyzed and failure load is determined for different loading cases. The results were used to find the best aspect ratio of brick to strengthen brick masonry wall.
Thermally stimulated current method applied to highly irradiated silicon diodes
Pintilie, I; Pintilie, I; Moll, Michael; Fretwurst, E; Lindström, G
2002-01-01
We propose an improved method for the analysis of Thermally Stimulated Currents (TSC) measured on highly irradiated silicon diodes. The proposed TSC formula for the evaluation of a set of TSC spectra obtained with different reverse biases leads not only to the concentration of electron and hole traps visible in the spectra but also gives an estimation for the concentration of defects which not give rise to a peak in the 30-220 K TSC temperature range (very shallow or very deep levels). The method is applied to a diode irradiated with a neutron fluence of phi sub n =1.82x10 sup 1 sup 3 n/cm sup 2.
The large break LOCA evaluation method with the simplified statistic approach
International Nuclear Information System (INIS)
Kamata, Shinya; Kubo, Kazuo
2004-01-01
USNRC published the Code Scaling, Applicability and Uncertainty (CSAU) evaluation methodology to large break LOCA which supported the revised rule for Emergency Core Cooling System performance in 1989. In USNRC regulatory guide 1.157, it is required that the peak cladding temperature (PCT) cannot exceed 2200deg F with high probability 95th percentile. In recent years, overseas countries have developed statistical methodology and best estimate code with the model which can provide more realistic simulation for the phenomena based on the CSAU evaluation methodology. In order to calculate PCT probability distribution by Monte Carlo trials, there are approaches such as the response surface technique using polynomials, the order statistics method, etc. For the purpose of performing rational statistic analysis, Mitsubishi Heavy Industries, LTD (MHI) tried to develop the statistic LOCA method using the best estimate LOCA code MCOBRA/TRAC and the simplified code HOTSPOT. HOTSPOT is a Monte Carlo heat conduction solver to evaluate the uncertainties of the significant fuel parameters at the PCT positions of the hot rod. The direct uncertainty sensitivity studies can be performed without the response surface because the Monte Carlo simulation for key parameters can be performed in short time using HOTSPOT. With regard to the parameter uncertainties, MHI established the treatment that the bounding conditions are given for LOCA boundary and plant initial conditions, the Monte Carlo simulation using HOTSPOT is applied to the significant fuel parameters. The paper describes the large break LOCA evaluation method with the simplified statistic approach and the results of the application of the method to the representative four-loop nuclear power plant. (author)
Hybrid electrokinetic method applied to mix contaminated soil
Energy Technology Data Exchange (ETDEWEB)
Mansour, H.; Maria, E. [Dept. of Building Civil and Environmental Engineering, Concordia Univ., Montreal (Canada)
2001-07-01
Several industrials and municipal areas in North America are contaminated with heavy metals and petroleum products. This mix contamination presents a particularly difficult task for remediation when is exposed in clayey soil. The objective of this research was to find a method to cleanup mix contaminated clayey soils. Finally, a multifunctional hybrid electrokinetic method was investigated. Clayey soil was contaminated with lead and nickel (heavy metals) at the level of 1000 ppm and phenanthrene (PAH) of 600 ppm. Electrokinetic surfactant supply system was applied to mobilize, transport and removal of phenanthrene. A chelation agent (EDTA) was also electrokinetically supplied to mobilize heavy metals. The studies were performed on 8 lab scale electrokinetic cells. The mix contaminated clayey soil was subjected to DC total voltage gradient of 0.3 V/cm. Supplied liquids (surfactant and EDTA) were introduced in different periods of time (22 days, 42 days) in order to optimize the most excessive removal of contaminants. The ph, electrical parameters, volume supplied, and volume discharged was monitored continuously during each experiment. At the end of these tests soil and cathalyte were subjected to physico-chemical analysis. The paper discusses results of experiments including the optimal energy use, removal efficiency of phenanthrene, as well, transport and removal of heavy metals. The results of this study can be applied for in-situ hybrid electrokinetic technology to remediate clayey sites contaminated with petroleum product mixed with heavy metals (e.g. manufacture Gas Plant Sites). (orig.)
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.
Kim, Yoonsang; Emery, Sherry
2013-01-01
Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415
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.
Directory of Open Access Journals (Sweden)
Chien-Chou Chen
2016-11-01
Full Text Available Abstract Background Cases of dengue fever have increased in areas of Southeast Asia in recent years. Taiwan hit a record-high 42,856 cases in 2015, with the majority in southern Tainan and Kaohsiung Cities. Leveraging spatial statistics and geo-visualization techniques, we aim to design an online analytical tool for local public health workers to prospectively identify ongoing hot spots of dengue fever weekly at the village level. Methods A total of 57,516 confirmed cases of dengue fever in 2014 and 2015 were obtained from the Taiwan Centers for Disease Control (TCDC. Incorporating demographic information as covariates with cumulative cases (365 days in a discrete Poisson model, we iteratively applied space–time scan statistics by SaTScan software to detect the currently active cluster of dengue fever (reported as relative risk in each village of Tainan and Kaohsiung every week. A village with a relative risk >1 and p value <0.05 was identified as a dengue-epidemic area. Assuming an ongoing transmission might continuously spread for two consecutive weeks, we estimated the sensitivity and specificity for detecting outbreaks by comparing the scan-based classification (dengue-epidemic vs. dengue-free village with the true cumulative case numbers from the TCDC’s surveillance statistics. Results Among the 1648 villages in Tainan and Kaohsiung, the overall sensitivity for detecting outbreaks increases as case numbers grow in a total of 92 weekly simulations. The specificity for detecting outbreaks behaves inversely, compared to the sensitivity. On average, the mean sensitivity and specificity of 2-week hot spot detection were 0.615 and 0.891 respectively (p value <0.001 for the covariate adjustment model, as the maximum spatial and temporal windows were specified as 50% of the total population at risk and 28 days. Dengue-epidemic villages were visualized and explored in an interactive map. Conclusions We designed an online analytical tool for
A Multifactorial Analysis of Reconstruction Methods Applied After Total Gastrectomy
Directory of Open Access Journals (Sweden)
Oktay Büyükaşık
2010-12-01
Full Text Available Aim: The aim of this study was to evaluate the reconstruction methods applied after total gastrectomy in terms of postoperative symptomology and nutrition. Methods: This retrospective study was conducted on 31 patients who underwent total gastrectomy due to gastric cancer in 2. Clinic of General Surgery, SSK Ankara Training Hospital. 6 different reconstruction methods were used and analyzed in terms of age, sex and postoperative complications. One from esophagus and two biopsy specimens from jejunum were taken through upper gastrointestinal endoscopy from all cases, and late period morphological and microbiological changes were examined. Postoperative weight change, dumping symptoms, reflux esophagitis, solid/liquid dysphagia, early satiety, postprandial pain, diarrhea and anorexia were assessed. Results: Of 31 patients,18 were males and 13 females; the youngest one was 33 years old, while the oldest- 69 years old. It was found that reconstruction without pouch was performed in 22 cases and with pouch in 9 cases. Early satiety, postprandial pain, dumping symptoms, diarrhea and anemia were found most commonly in cases with reconstruction without pouch. The rate of bacterial colonization of the jejunal mucosa was identical in both groups. Reflux esophagitis was most commonly seen in omega esophagojejunostomy (EJ, while the least-in Roux-en-Y, Tooley and Tanner 19 EJ. Conclusion: Reconstruction with pouch performed after total gastrectomy is still a preferable method. (The Medical Bulletin of Haseki 2010; 48:126-31
Artificial Intelligence Methods Applied to Parameter Detection of Atrial Fibrillation
Arotaritei, D.; Rotariu, C.
2015-09-01
In this paper we present a novel method to develop an atrial fibrillation (AF) based on statistical descriptors and hybrid neuro-fuzzy and crisp system. The inference of system produce rules of type if-then-else that care extracted to construct a binary decision system: normal of atrial fibrillation. We use TPR (Turning Point Ratio), SE (Shannon Entropy) and RMSSD (Root Mean Square of Successive Differences) along with a new descriptor, Teager- Kaiser energy, in order to improve the accuracy of detection. The descriptors are calculated over a sliding window that produce very large number of vectors (massive dataset) used by classifier. The length of window is a crisp descriptor meanwhile the rest of descriptors are interval-valued type. The parameters of hybrid system are adapted using Genetic Algorithm (GA) algorithm with fitness single objective target: highest values for sensibility and sensitivity. The rules are extracted and they are part of the decision system. The proposed method was tested using the Physionet MIT-BIH Atrial Fibrillation Database and the experimental results revealed a good accuracy of AF detection in terms of sensitivity and specificity (above 90%).
Marimon, Maria Paula C; Roisenberg, Ari; Suhogusoff, Alexandra V; Viero, Antonio Pedro
2013-06-01
High fluoride concentrations (up to 11 mg/L) have been reported in the groundwater of the Guarani Aquifer System (Santa Maria Formation) in the central region of the state of Rio Grande do Sul, Southern Brazil. In this area, dental fluorosis is an endemic disease. This paper presents the geochemical data and the combination of statistical analysis (Principal components and cluster analyses) and geochemical modeling to achieve the hydrogeochemistry of the groundwater and discusses the possible fluoride origin. The groundwater from the Santa Maria Formation is comprised of four different geochemical groups. The first group corresponds to a sodium chloride groundwater which evolves to sodium bicarbonate, the second one, both containing fluoride anomalies. The third group is represented by calcium bicarbonate groundwater, and in the fourth, magnesium is the distinctive parameter. The statistical and geochemical analyses supported by isotopic measurements indicated that groundwater may have originated from mixtures of deeper aquifers and the fluoride concentrations could be derived from rock/water interactions (e.g., desorption from clay minerals).
Principle of maximum Fisher information from Hardy's axioms applied to statistical systems.
Frieden, B Roy; Gatenby, Robert A
2013-10-01
Consider a finite-sized, multidimensional system in parameter state a. The system is either at statistical equilibrium or general nonequilibrium, and may obey either classical or quantum physics. L. Hardy's mathematical axioms provide a basis for the physics obeyed by any such system. One axiom is that the number N of distinguishable states a in the system obeys N=max. This assumes that N is known as deterministic prior knowledge. However, most observed systems suffer statistical fluctuations, for which N is therefore only known approximately. Then what happens if the scope of the axiom N=max is extended to include such observed systems? It is found that the state a of the system must obey a principle of maximum Fisher information, I=I(max). This is important because many physical laws have been derived, assuming as a working hypothesis that I=I(max). These derivations include uses of the principle of extreme physical information (EPI). Examples of such derivations were of the De Broglie wave hypothesis, quantum wave equations, Maxwell's equations, new laws of biology (e.g., of Coulomb force-directed cell development and of in situ cancer growth), and new laws of economic fluctuation and investment. That the principle I=I(max) itself derives from suitably extended Hardy axioms thereby eliminates its need to be assumed in these derivations. Thus, uses of I=I(max) and EPI express physics at its most fundamental level, its axiomatic basis in math.
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
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)
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…
CHF predictor derived from a 3D thermal-hydraulic code and an advanced statistical method
International Nuclear Information System (INIS)
Banner, D.; Aubry, S.
2004-01-01
A rod bundle CHF predictor has been determined by using a 3D code (THYC) to compute local thermal-hydraulic conditions at the boiling crisis location. These local parameters have been correlated to the critical heat flux by using an advanced statistical method based on spline functions. The main characteristics of the predictor are presented in conjunction with a detailed analysis of predictions (P/M ratio) in order to prove that the usual safety methodology can be applied with such a predictor. A thermal-hydraulic design criterion is obtained (1.13) and the predictor is compared with the WRB-1 correlation. (author)
Methods for Clustering Variables and the Use of them in Statistical Packages
Czech Academy of Sciences Publication Activity Database
Řezanková, H.; Húsek, Dušan
2002-01-01
Roč. 10, - (2002), s. 153-160 ISSN 1210-809X. [Applications of Mathematics and Statistics in Economy. Zadov, 13.09.2001-14.09.2001] R&D Projects: GA ČR GA201/01/1192 Institutional research plan: AV0Z1030915 Keywords : factor analysis * cluster analysis * multidimensional * statistical packages Subject RIV: BB - Applied Statistics, Operational Research
Multicriterial Hierarchy Methods Applied in Consumption Demand Analysis. The Case of Romania
Directory of Open Access Journals (Sweden)
Constantin Bob
2008-03-01
Full Text Available The basic information for computing the quantitative statistical indicators, that characterize the demand of industrial products and services are collected by the national statistics organizations, through a series of statistical surveys (most of them periodical and partial. The source for data we used in the present paper is an statistical investigation organized by the National Institute of Statistics, "Family budgets survey" that allows to collect information regarding the households composition, income, expenditure, consumption and other aspects of population living standard. In 2005, in Romania, a person spent monthly in average 391,2 RON, meaning about 115,1 Euros for purchasing the consumed food products and beverage, as well as non-foods products, services, investments and other taxes. 23% of this sum was spent for purchasing the consumed food products and beverages, 21.6% of the total sum was spent for purchasing non-food goods and 18,1% for payment of different services. There is a discrepancy between the different development regions in Romania, regarding total households expenditure composition. For this reason, in the present paper we applied statistical methods for ranking the various development regions in Romania, using the share of householdsí expenditure on categories of products and services as ranking criteria.
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 elimination of guarantee-time bias in cohort studies: a simulation study
Directory of Open Access Journals (Sweden)
In Sung Cho
2017-08-01
Full Text Available Abstract Background Aspirin has been considered to be beneficial in preventing cardiovascular diseases and cancer. Several pharmaco-epidemiology cohort studies have shown protective effects of aspirin on diseases using various statistical methods, with the Cox regression model being the most commonly used approach. However, there are some inherent limitations to the conventional Cox regression approach such as guarantee-time bias, resulting in an overestimation of the drug effect. To overcome such limitations, alternative approaches, such as the time-dependent Cox model and landmark methods have been proposed. This study aimed to compare the performance of three methods: Cox regression, time-dependent Cox model and landmark method with different landmark times in order to address the problem of guarantee-time bias. Methods Through statistical modeling and simulation studies, the performance of the above three methods were assessed in terms of type I error, bias, power, and mean squared error (MSE. In addition, the three statistical approaches were applied to a real data example from the Korean National Health Insurance Database. Effect of cumulative rosiglitazone dose on the risk of hepatocellular carcinoma was used as an example for illustration. Results In the simulated data, time-dependent Cox regression outperformed the landmark method in terms of bias and mean squared error but the type I error rates were similar. The results from real-data example showed the same patterns as the simulation findings. Conclusions While both time-dependent Cox regression model and landmark analysis are useful in resolving the problem of guarantee-time bias, time-dependent Cox regression is the most appropriate method for analyzing cumulative dose effects in pharmaco-epidemiological studies.
Directory of Open Access Journals (Sweden)
Miquel Porta
Full Text Available BACKGROUND: There are no analyses of citations to books on epidemiological and statistical methods in the biomedical literature. Such analyses may shed light on how concepts and methods changed while biomedical research evolved. Our aim was to analyze the number and time trends of citations received from biomedical articles by books on epidemiological and statistical methods, and related disciplines. METHODS AND FINDINGS: The data source was the Web of Science. The study books were published between 1957 and 2010. The first year of publication of the citing articles was 1945. We identified 125 books that received at least 25 citations. Books first published in 1980-1989 had the highest total and median number of citations per year. Nine of the 10 most cited texts focused on statistical methods. Hosmer & Lemeshow's Applied logistic regression received the highest number of citations and highest average annual rate. It was followed by books by Fleiss, Armitage, et al., Rothman, et al., and Kalbfleisch and Prentice. Fifth in citations per year was Sackett, et al., Evidence-based medicine. The rise of multivariate methods, clinical epidemiology, or nutritional epidemiology was reflected in the citation trends. Educational textbooks, practice-oriented books, books on epidemiological substantive knowledge, and on theory and health policies were much less cited. None of the 25 top-cited books had the theoretical or sociopolitical scope of works by Cochrane, McKeown, Rose, or Morris. CONCLUSIONS: Books were mainly cited to reference methods. Books first published in the 1980s continue to be most influential. Older books on theory and policies were rooted in societal and general medical concerns, while the most modern books are almost purely on methods.
Single-Case Designs and Qualitative Methods: Applying a Mixed Methods Research Perspective
Hitchcock, John H.; Nastasi, Bonnie K.; Summerville, Meredith
2010-01-01
The purpose of this conceptual paper is to describe a design that mixes single-case (sometimes referred to as single-subject) and qualitative methods, hereafter referred to as a single-case mixed methods design (SCD-MM). Minimal attention has been given to the topic of applying qualitative methods to SCD work in the literature. These two…
Analytical methods applied to diverse types of Brazilian propolis
Directory of Open Access Journals (Sweden)
Marcucci Maria
2011-06-01
Full Text Available Abstract Propolis is a bee product, composed mainly of plant resins and beeswax, therefore its chemical composition varies due to the geographic and plant origins of these resins, as well as the species of bee. Brazil is an important supplier of propolis on the world market and, although green colored propolis from the southeast is the most known and studied, several other types of propolis from Apis mellifera and native stingless bees (also called cerumen can be found. Propolis is usually consumed as an extract, so the type of solvent and extractive procedures employed further affect its composition. Methods used for the extraction; analysis the percentage of resins, wax and insoluble material in crude propolis; determination of phenolic, flavonoid, amino acid and heavy metal contents are reviewed herein. Different chromatographic methods applied to the separation, identification and quantification of Brazilian propolis components and their relative strengths are discussed; as well as direct insertion mass spectrometry fingerprinting. Propolis has been used as a popular remedy for several centuries for a wide array of ailments. Its antimicrobial properties, present in propolis from different origins, have been extensively studied. But, more recently, anti-parasitic, anti-viral/immune stimulating, healing, anti-tumor, anti-inflammatory, antioxidant and analgesic activities of diverse types of Brazilian propolis have been evaluated. The most common methods employed and overviews of their relative results are presented.
Teaching organization theory for healthcare management: three applied learning methods.
Olden, Peter C
2006-01-01
Organization theory (OT) provides a way of seeing, describing, analyzing, understanding, and improving organizations based on patterns of organizational design and behavior (Daft 2004). It gives managers models, principles, and methods with which to diagnose and fix organization structure, design, and process problems. Health care organizations (HCOs) face serious problems such as fatal medical errors, harmful treatment delays, misuse of scarce nurses, costly inefficiency, and service failures. Some of health care managers' most critical work involves designing and structuring their organizations so their missions, visions, and goals can be achieved-and in some cases so their organizations can survive. Thus, it is imperative that graduate healthcare management programs develop effective approaches for teaching OT to students who will manage HCOs. Guided by principles of education, three applied teaching/learning activities/assignments were created to teach OT in a graduate healthcare management program. These educationalmethods develop students' competency with OT applied to HCOs. The teaching techniques in this article may be useful to faculty teaching graduate courses in organization theory and related subjects such as leadership, quality, and operation management.
Ingber, Lester
1991-09-01
A series of papers has developed a statistical mechanics of neocortical interactions (SMNI), deriving aggregate behavior of experimentally observed columns of neurons from statistical electrical-chemical properties of synaptic interactions. While not useful to yield insights at the single-neuron level, SMNI has demonstrated its capability in describing large-scale properties of short-term memory and electroencephalographic (EEG) systematics. The necessity of including nonlinear and stochastic structures in this development has been stressed. In this paper, a more stringent test is placed on SMNI: The algebraic and numerical algorithms previously developed in this and similar systems are brought to bear to fit large sets of EEG and evoked-potential data being collected to investigate genetic predispositions to alcoholism and to extract brain ``signatures'' of short-term memory. Using the numerical algorithm of very fast simulated reannealing, it is demonstrated that SMNI can indeed fit these data within experimentally observed ranges of its underlying neuronal-synaptic parameters, and the quantitative modeling results are used to examine physical neocortical mechanisms to discriminate high-risk and low-risk populations genetically predisposed to alcoholism. Since this study is a control to span relatively long time epochs, similar to earlier attempts to establish such correlations, this discrimination is inconclusive because of other neuronal activity which can mask such effects. However, the SMNI model is shown to be consistent with EEG data during selective attention tasks and with neocortical mechanisms describing short-term memory previously published using this approach. This paper explicitly identifies similar nonlinear stochastic mechanisms of interaction at the microscopic-neuronal, mesoscopic-columnar, and macroscopic-regional scales of neocortical interactions. These results give strong quantitative support for an accurate intuitive picture, portraying
Metrological evaluation of characterization methods applied to nuclear fuels
Energy Technology Data Exchange (ETDEWEB)
Faeda, Kelly Cristina Martins; Lameiras, Fernando Soares; Camarano, Denise das Merces; Ferreira, Ricardo Alberto Neto; Migliorini, Fabricio Lima; Carneiro, Luciana Capanema Silva; Silva, Egonn Hendrigo Carvalho, E-mail: kellyfisica@gmail.co, E-mail: fernando.lameiras@pq.cnpq.b, E-mail: dmc@cdtn.b, E-mail: ranf@cdtn.b, E-mail: flmigliorini@hotmail.co, E-mail: lucsc@hotmail.co, E-mail: egonn@ufmg.b [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2010-07-01
In manufacturing the nuclear fuel, characterizations are performed in order to assure the minimization of harmful effects. The uranium dioxide is the most used substance as nuclear reactor fuel because of many advantages, such as: high stability even when it is in contact with water at high temperatures, high fusion point, and high capacity to retain fission products. Several methods are used for characterization of nuclear fuels, such as thermogravimetric analysis for the ratio O / U, penetration-immersion method, helium pycnometer and mercury porosimetry for the density and porosity, BET method for the specific surface, chemical analyses for relevant impurities, and the laser flash method for thermophysical properties. Specific tools are needed to control the diameter and the sphericity of the microspheres and the properties of the coating layers (thickness, density, and degree of anisotropy). Other methods can also give information, such as scanning and transmission electron microscopy, X-ray diffraction, microanalysis, and mass spectroscopy of secondary ions for chemical analysis. The accuracy of measurement and level of uncertainty of the resulting data are important. This work describes a general metrological characterization of some techniques applied to the characterization of nuclear fuel. Sources of measurement uncertainty were analyzed. The purpose is to summarize selected properties of UO{sub 2} that have been studied by CDTN in a program of fuel development for Pressurized Water Reactors (PWR). The selected properties are crucial for thermalhydraulic codes to study basic design accidents. The thermal characterization (thermal diffusivity and thermal conductivity) and the penetration immersion method (density and open porosity) of UO{sub 2} samples were focused. The thermal characterization of UO{sub 2} samples was determined by the laser flash method between room temperature and 448 K. The adaptive Monte Carlo Method was used to obtain the endpoints of
Glaz, Joseph
2009-01-01
Suitable for graduate students and researchers in applied probability and statistics, as well as for scientists in biology, computer science, pharmaceutical science and medicine, this title brings together a collection of chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics.
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
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.
Applying systems ergonomics methods in sport: A systematic review.
Hulme, Adam; Thompson, Jason; Plant, Katherine L; Read, Gemma J M; Mclean, Scott; Clacy, Amanda; Salmon, Paul M
2018-04-16
As sports systems become increasingly more complex, competitive, and technology-centric, there is a greater need for systems ergonomics methods to consider the performance, health, and safety of athletes in context with the wider settings in which they operate. Therefore, the purpose of this systematic review was to identify and critically evaluate studies which have applied a systems ergonomics research approach in the context of sports performance and injury management. Five databases (PubMed, Scopus, ScienceDirect, Web of Science, and SPORTDiscus) were searched for the dates 01 January 1990 to 01 August 2017, inclusive, for original peer-reviewed journal articles and conference papers. Reported analyses were underpinned by a recognised systems ergonomics method, and study aims were related to the optimisation of sports performance (e.g. communication, playing style, technique, tactics, or equipment), and/or the management of sports injury (i.e. identification, prevention, or treatment). A total of seven articles were identified. Two articles were focussed on understanding and optimising sports performance, whereas five examined sports injury management. The methods used were the Event Analysis of Systemic Teamwork, Cognitive Work Analysis (the Work Domain Analysis Abstraction Hierarchy), Rasmussen's Risk Management Framework, and the Systems Theoretic Accident Model and Processes method. The individual sport application was distance running, whereas the team sports contexts examined were cycling, football, Australian Football League, and rugby union. The included systems ergonomics applications were highly flexible, covering both amateur and elite sports contexts. The studies were rated as valuable, providing descriptions of injury controls and causation, the factors influencing injury management, the allocation of responsibilities for injury prevention, as well as the factors and their interactions underpinning sports performance. Implications and future
The virtual fields method applied to spalling tests on concrete
Directory of Open Access Journals (Sweden)
Forquin P.
2012-08-01
Full Text Available For one decade spalling techniques based on the use of a metallic Hopkinson bar put in contact with a concrete sample have been widely employed to characterize the dynamic tensile strength of concrete at strain-rates ranging from a few tens to two hundreds of s−1. However, the processing method mainly based on the use of the velocity profile measured on the rear free surface of the sample (Novikov formula remains quite basic and an identification of the whole softening behaviour of the concrete is out of reach. In the present paper a new processing method is proposed based on the use of the Virtual Fields Method (VFM. First, a digital high speed camera is used to record the pictures of a grid glued on the specimen. Next, full-field measurements are used to obtain the axial displacement field at the surface of the specimen. Finally, a specific virtual field has been defined in the VFM equation to use the acceleration map as an alternative ‘load cell’. This method applied to three spalling tests allowed to identify Young’s modulus during the test. It was shown that this modulus is constant during the initial compressive part of the test and decreases in the tensile part when micro-damage exists. It was also shown that in such a simple inertial test, it was possible to reconstruct average axial stress profiles using only the acceleration data. Then, it was possible to construct local stress-strain curves and derive a tensile strength value.
Porta, Miquel; Vandenbroucke, Jan P; Ioannidis, John P A; Sanz, Sergio; Fernandez, Esteve; Bhopal, Raj; Morabia, Alfredo; Victora, Cesar; Lopez, Tomàs
2013-01-01
There are no analyses of citations to books on epidemiological and statistical methods in the biomedical literature. Such analyses may shed light on how concepts and methods changed while biomedical research evolved. Our aim was to analyze the number and time trends of citations received from biomedical articles by books on epidemiological and statistical methods, and related disciplines. The data source was the Web of Science. The study books were published between 1957 and 2010. The first year of publication of the citing articles was 1945. We identified 125 books that received at least 25 citations. Books first published in 1980-1989 had the highest total and median number of citations per year. Nine of the 10 most cited texts focused on statistical methods. Hosmer & Lemeshow's Applied logistic regression received the highest number of citations and highest average annual rate. It was followed by books by Fleiss, Armitage, et al., Rothman, et al., and Kalbfleisch and Prentice. Fifth in citations per year was Sackett, et al., Evidence-based medicine. The rise of multivariate methods, clinical epidemiology, or nutritional epidemiology was reflected in the citation trends. Educational textbooks, practice-oriented books, books on epidemiological substantive knowledge, and on theory and health policies were much less cited. None of the 25 top-cited books had the theoretical or sociopolitical scope of works by Cochrane, McKeown, Rose, or Morris. Books were mainly cited to reference methods. Books first published in the 1980s continue to be most influential. Older books on theory and policies were rooted in societal and general medical concerns, while the most modern books are almost purely on methods.
Estimation of In Situ Stresses with Hydro-Fracturing Tests and a Statistical Method
Lee, Hikweon; Ong, See Hong
2018-03-01
At great depths, where borehole-based field stress measurements such as hydraulic fracturing are challenging due to difficult downhole conditions or prohibitive costs, in situ stresses can be indirectly estimated using wellbore failures such as borehole breakouts and/or drilling-induced tensile failures detected by an image log. As part of such efforts, a statistical method has been developed in which borehole breakouts detected on an image log are used for this purpose (Song et al. in Proceedings on the 7th international symposium on in situ rock stress, 2016; Song and Chang in J Geophys Res Solid Earth 122:4033-4052, 2017). The method employs a grid-searching algorithm in which the least and maximum horizontal principal stresses ( S h and S H) are varied, and the corresponding simulated depth-related breakout width distribution as a function of the breakout angle ( θ B = 90° - half of breakout width) is compared to that observed along the borehole to determine a set of S h and S H having the lowest misfit between them. An important advantage of the method is that S h and S H can be estimated simultaneously in vertical wells. To validate the statistical approach, the method is applied to a vertical hole where a set of field hydraulic fracturing tests have been carried out. The stress estimations using the proposed method were found to be in good agreement with the results interpreted from the hydraulic fracturing test measurements.
International Nuclear Information System (INIS)
Kang, Won-Hee; Kliese, Alyce
2014-01-01
Lifeline networks, such as transportation, water supply, sewers, telecommunications, and electrical and gas networks, are essential elements for the economic and societal functions of urban areas, but their components are highly susceptible to natural or man-made hazards. In this context, it is essential to provide effective pre-disaster hazard mitigation strategies and prompt post-disaster risk management efforts based on rapid system reliability assessment. This paper proposes a rapid reliability estimation method for node-pair connectivity analysis of lifeline networks especially when the network components are statistically correlated. Recursive procedures are proposed to compound all network nodes until they become a single super node representing the connectivity between the origin and destination nodes. The proposed method is applied to numerical network examples and benchmark interconnected power and water networks in Memphis, Shelby County. The connectivity analysis results show the proposed method's reasonable accuracy and remarkable efficiency as compared to the Monte Carlo simulations
The application of non-parametric statistical method for an ALARA implementation
International Nuclear Information System (INIS)
Cho, Young Ho; Herr, Young Hoi
2003-01-01
The cost-effective reduction of Occupational Radiation Dose (ORD) at a nuclear power plant could not be achieved without going through an extensive analysis of accumulated ORD data of existing plants. Through the data analysis, it is required to identify what are the jobs of repetitive high ORD at the nuclear power plant. In this study, Percentile Rank Sum Method (PRSM) is proposed to identify repetitive high ORD jobs, which is based on non-parametric statistical theory. As a case study, the method is applied to ORD data of maintenance and repair jobs at Kori units 3 and 4 that are pressurized water reactors with 950 MWe capacity and have been operated since 1986 and 1987, respectively in Korea. The results was verified and validated, and PRSM has been demonstrated to be an efficient method of analyzing the data
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...
Statistical analysis of global surface temperature and sea level using cointegration methods
DEFF Research Database (Denmark)
Schmidt, Torben; Johansen, Søren; Thejll, Peter
2012-01-01
Global sea levels are rising which is widely understood as a consequence of thermal expansion and melting of glaciers and land-based ice caps. Due to the lack of representation of ice-sheet dynamics in present-day physically-based climate models being unable to simulate observed sea level trends......, semi-empirical models have been applied as an alternative for projecting of future sea levels. There is in this, however, potential pitfalls due to the trending nature of the time series. We apply a statistical method called cointegration analysis to observed global sea level and land-ocean surface air...... temperature, capable of handling such peculiarities. We find a relationship between sea level and temperature and find that temperature causally depends on the sea level, which can be understood as a consequence of the large heat capacity of the ocean. We further find that the warming episode in the 1940s...
Statistical analysis of global surface air temperature and sea level using cointegration methods
DEFF Research Database (Denmark)
Schmith, Torben; Johansen, Søren; Thejll, Peter
Global sea levels are rising which is widely understood as a consequence of thermal expansion and melting of glaciers and land-based ice caps. Due to physically-based models being unable to simulate observed sea level trends, semi-empirical models have been applied as an alternative for projecting...... of future sea levels. There is in this, however, potential pitfalls due to the trending nature of the time series. We apply a statistical method called cointegration analysis to observed global sea level and surface air temperature, capable of handling such peculiarities. We find a relationship between sea...... level and temperature and find that temperature causally depends on the sea level, which can be understood as a consequence of the large heat capacity of the ocean. We further find that the warming episode in the 1940s is exceptional in the sense that sea level and warming deviates from the expected...
Statistical method application to knowledge base building for reactor accident diagnostic system
International Nuclear Information System (INIS)
Yoshida, Kazuo; Yokobayashi, Masao; Matsumoto, Kiyoshi; Kohsaka, Atsuo
1989-01-01
In the development of a knowledge based expert system, one of key issues is how to build the knowledge base (KB) in an efficient way with keeping the objectivity of KB. In order to solve this issue, an approach has been proposed to build a prototype KB systematically by a statistical method, factor analysis. For the verification of this approach, factor analysis was applied to build a prototype KB for the JAERI expert system DISKET. To this end, alarm and process information was generated by a PWR simulator and the factor analysis was applied to this information to define taxonomy of accident hypotheses and to extract rules for each hypothesis. The prototype KB thus built was tested through inferring against several types of transients including double-failures. In each diagnosis, the transient type was well identified. Furthermore, newly introduced standards for rule extraction showed good effects on the enhancement of the performance of prototype KB. (author)
Applying Clustering to Statistical Analysis of Student Reasoning about Two-Dimensional Kinematics
Springuel, R. Padraic; Wittman, Michael C.; Thompson, John R.
2007-01-01
We use clustering, an analysis method not presently common to the physics education research community, to group and characterize student responses to written questions about two-dimensional kinematics. Previously, clustering has been used to analyze multiple-choice data; we analyze free-response data that includes both sketches of vectors and…
Statistics for Time-Series Spatial Data: Applying Survival Analysis to Study Land-Use Change
Wang, Ninghua Nathan
2013-01-01
Traditional spatial analysis and data mining methods fall short of extracting temporal information from data. This inability makes their use difficult to study changes and the associated mechanisms of many geographic phenomena of interest, for example, land-use. On the other hand, the growing availability of land-change data over multiple time…
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
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
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.
Flood Hazard Mapping by Applying Fuzzy TOPSIS Method
Han, K. Y.; Lee, J. Y.; Keum, H.; Kim, B. J.; Kim, T. H.
2017-12-01
There are lots of technical methods to integrate various factors for flood hazard mapping. The purpose of this study is to suggest the methodology of integrated flood hazard mapping using MCDM(Multi Criteria Decision Making). MCDM problems involve a set of alternatives that are evaluated on the basis of conflicting and incommensurate criteria. In this study, to apply MCDM to assessing flood risk, maximum flood depth, maximum velocity, and maximum travel time are considered as criterion, and each applied elements are considered as alternatives. The scheme to find the efficient alternative closest to a ideal value is appropriate way to assess flood risk of a lot of element units(alternatives) based on various flood indices. Therefore, TOPSIS which is most commonly used MCDM scheme is adopted to create flood hazard map. The indices for flood hazard mapping(maximum flood depth, maximum velocity, and maximum travel time) have uncertainty concerning simulation results due to various values according to flood scenario and topographical condition. These kind of ambiguity of indices can cause uncertainty of flood hazard map. To consider ambiguity and uncertainty of criterion, fuzzy logic is introduced which is able to handle ambiguous expression. In this paper, we made Flood Hazard Map according to levee breach overflow using the Fuzzy TOPSIS Technique. We confirmed the areas where the highest grade of hazard was recorded through the drawn-up integrated flood hazard map, and then produced flood hazard map can be compared them with those indicated in the existing flood risk maps. Also, we expect that if we can apply the flood hazard map methodology suggested in this paper even to manufacturing the current flood risk maps, we will be able to make a new flood hazard map to even consider the priorities for hazard areas, including more varied and important information than ever before. Keywords : Flood hazard map; levee break analysis; 2D analysis; MCDM; Fuzzy TOPSIS
Applying clustering to statistical analysis of student reasoning about two-dimensional kinematics
Directory of Open Access Journals (Sweden)
R. Padraic Springuel
2007-12-01
Full Text Available We use clustering, an analysis method not presently common to the physics education research community, to group and characterize student responses to written questions about two-dimensional kinematics. Previously, clustering has been used to analyze multiple-choice data; we analyze free-response data that includes both sketches of vectors and written elements. The primary goal of this paper is to describe the methodology itself; we include a brief overview of relevant results.
Bayesian statistics applied to the location of the source of explosions at Stromboli Volcano, Italy
Saccorotti, G.; Chouet, B.; Martini, M.; Scarpa, R.
1998-01-01
We present a method for determining the location and spatial extent of the source of explosions at Stromboli Volcano, Italy, based on a Bayesian inversion of the slowness vector derived from frequency-slowness analyses of array data. The method searches for source locations that minimize the error between the expected and observed slowness vectors. For a given set of model parameters, the conditional probability density function of slowness vectors is approximated by a Gaussian distribution of expected errors. The method is tested with synthetics using a five-layer velocity model derived for the north flank of Stromboli and a smoothed velocity model derived from a power-law approximation of the layered structure. Application to data from Stromboli allows for a detailed examination of uncertainties in source location due to experimental errors and incomplete knowledge of the Earth model. Although the solutions are not constrained in the radial direction, excellent resolution is achieved in both transverse and depth directions. Under the assumption that the horizontal extent of the source does not exceed the crater dimension, the 90% confidence region in the estimate of the explosive source location corresponds to a small volume extending from a depth of about 100 m to a maximum depth of about 300 m beneath the active vents, with a maximum likelihood source region located in the 120- to 180-m-depth interval.
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...
Statistical homogeneity tests applied to large data sets from high energy physics experiments
Trusina, J.; Franc, J.; Kůs, V.
2017-12-01
Homogeneity tests are used in high energy physics for the verification of simulated Monte Carlo samples, it means if they have the same distribution as a measured data from particle detector. Kolmogorov-Smirnov, χ 2, and Anderson-Darling tests are the most used techniques to assess the samples’ homogeneity. Since MC generators produce plenty of entries from different models, each entry has to be re-weighted to obtain the same sample size as the measured data has. One way of the homogeneity testing is through the binning. If we do not want to lose any information, we can apply generalized tests based on weighted empirical distribution functions. In this paper, we propose such generalized weighted homogeneity tests and introduce some of their asymptotic properties. We present the results based on numerical analysis which focuses on estimations of the type-I error and power of the test. Finally, we present application of our homogeneity tests to data from the experiment DØ in Fermilab.
The intervals method: a new approach to analyse finite element outputs using multivariate statistics
Directory of Open Access Journals (Sweden)
Jordi Marcé-Nogué
2017-10-01
Full Text Available Background In this paper, we propose a new method, named the intervals’ method, to analyse data from finite element models in a comparative multivariate framework. As a case study, several armadillo mandibles are analysed, showing that the proposed method is useful to distinguish and characterise biomechanical differences related to diet/ecomorphology. Methods The intervals’ method consists of generating a set of variables, each one defined by an interval of stress values. Each variable is expressed as a percentage of the area of the mandible occupied by those stress values. Afterwards these newly generated variables can be analysed using multivariate methods. Results Applying this novel method to the biological case study of whether armadillo mandibles differ according to dietary groups, we show that the intervals’ method is a powerful tool to characterize biomechanical performance and how this relates to different diets. This allows us to positively discriminate between specialist and generalist species. Discussion We show that the proposed approach is a useful methodology not affected by the characteristics of the finite element mesh. Additionally, the positive discriminating results obtained when analysing a difficult case study suggest that the proposed method could be a very useful tool for comparative studies in finite element analysis using multivariate statistical approaches.
The intervals method: a new approach to analyse finite element outputs using multivariate statistics
De Esteban-Trivigno, Soledad; Püschel, Thomas A.; Fortuny, Josep
2017-01-01
Background In this paper, we propose a new method, named the intervals’ method, to analyse data from finite element models in a comparative multivariate framework. As a case study, several armadillo mandibles are analysed, showing that the proposed method is useful to distinguish and characterise biomechanical differences related to diet/ecomorphology. Methods The intervals’ method consists of generating a set of variables, each one defined by an interval of stress values. Each variable is expressed as a percentage of the area of the mandible occupied by those stress values. Afterwards these newly generated variables can be analysed using multivariate methods. Results Applying this novel method to the biological case study of whether armadillo mandibles differ according to dietary groups, we show that the intervals’ method is a powerful tool to characterize biomechanical performance and how this relates to different diets. This allows us to positively discriminate between specialist and generalist species. Discussion We show that the proposed approach is a useful methodology not affected by the characteristics of the finite element mesh. Additionally, the positive discriminating results obtained when analysing a difficult case study suggest that the proposed method could be a very useful tool for comparative studies in finite element analysis using multivariate statistical approaches. PMID:29043107
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)
Statistical analysis to assess automated level of suspicion scoring methods in breast ultrasound
Galperin, Michael
2003-05-01
A well-defined rule-based system has been developed for scoring 0-5 the Level of Suspicion (LOS) based on qualitative lexicon describing the ultrasound appearance of breast lesion. The purposes of the research are to asses and select one of the automated LOS scoring quantitative methods developed during preliminary studies in benign biopsies reduction. The study has used Computer Aided Imaging System (CAIS) to improve the uniformity and accuracy of applying the LOS scheme by automatically detecting, analyzing and comparing breast masses. The overall goal is to reduce biopsies on the masses with lower levels of suspicion, rather that increasing the accuracy of diagnosis of cancers (will require biopsy anyway). On complex cysts and fibroadenoma cases experienced radiologists were up to 50% less certain in true negatives than CAIS. Full correlation analysis was applied to determine which of the proposed LOS quantification methods serves CAIS accuracy the best. This paper presents current results of applying statistical analysis for automated LOS scoring quantification for breast masses with known biopsy results. It was found that First Order Ranking method yielded most the accurate results. The CAIS system (Image Companion, Data Companion software) is developed by Almen Laboratories and was used to achieve the results.
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...
Statistical methods for detecting differentially abundant features in clinical metagenomic samples.
Directory of Open Access Journals (Sweden)
James Robert White
2009-04-01
Full Text Available Numerous studies are currently underway to characterize the microbial communities inhabiting our world. These studies aim to dramatically expand our understanding of the microbial biosphere and, more importantly, hope to reveal the secrets of the complex symbiotic relationship between us and our commensal bacterial microflora. An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them.We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data (e.g. as obtained through sequencing to detect differentially abundant features. Our method, Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fisher's exact test. Under a variety of simulations, we show that Metastats performs well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random sequencing of 85 metagenomes. The application of our method to the obesity dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations. The methods described in this paper are the first to address clinical metagenomic datasets comprising samples from multiple subjects. Our methods are robust across datasets of varied complexity and sampling level. While designed for metagenomic applications, our software
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).
Calkins, D. S.
1998-01-01
When the dependent (or response) variable response variable in an experiment has direction and magnitude, one approach that has been used for statistical analysis involves splitting magnitude and direction and applying univariate statistical techniques to the components. However, such treatment of quantities with direction and magnitude is not justifiable mathematically and can lead to incorrect conclusions about relationships among variables and, as a result, to flawed interpretations. This note discusses a problem with that practice and recommends mathematically correct procedures to be used with dependent variables that have direction and magnitude for 1) computation of mean values, 2) statistical contrasts of and confidence intervals for means, and 3) correlation methods.
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.
Applying sociodramatic methods in teaching transition to palliative care.
Baile, Walter F; Walters, Rebecca
2013-03-01
We introduce the technique of sociodrama, describe its key components, and illustrate how this simulation method was applied in a workshop format to address the challenge of discussing transition to palliative care. We describe how warm-up exercises prepared 15 learners who provide direct clinical care to patients with cancer for a dramatic portrayal of this dilemma. We then show how small-group brainstorming led to the creation of a challenging scenario wherein highly optimistic family members of a 20-year-old young man with terminal acute lymphocytic leukemia responded to information about the lack of further anticancer treatment with anger and blame toward the staff. We illustrate how the facilitators, using sociodramatic techniques of doubling and role reversal, helped learners to understand and articulate the hidden feelings of fear and loss behind the family's emotional reactions. By modeling effective communication skills, the facilitators demonstrated how key communication skills, such as empathic responses to anger and blame and using "wish" statements, could transform the conversation from one of conflict to one of problem solving with the family. We also describe how we set up practice dyads to give the learners an opportunity to try out new skills with each other. An evaluation of the workshop and similar workshops we conducted is presented. Copyright © 2013 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.
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.
Simulating European wind power generation applying statistical downscaling to reanalysis data
DEFF Research Database (Denmark)
Gonzalez-Aparicio, I.; Monforti, F.; Volker, Patrick
2017-01-01
generation time series dataset for the EU-28 and neighbouring countries at hourly intervals and at different geographical aggregation levels (country, bidding zone and administrative territorial unit), for a 30 year period taking into account the wind generating fleet at the end of 2015. (C) 2017 The Authors...... and characteristics of the wind resource which is related to the accuracy of the approach in converting wind speed data into power values. One of the main factors contributing to the uncertainty in these conversion methods is the selection of the spatial resolution. Although numerical weather prediction models can...... could not be captured by the use of a reanalysis technique and could be translated into misinterpretations of the wind power peaks, ramping capacities, the behaviour of power prices, as well as bidding strategies for the electricity market. This study contributes to the understanding what is captured...
Statistical process control applied to the liquid-fed ceramic melter process
International Nuclear Information System (INIS)
Pulsipher, B.A.; Kuhn, W.L.
1987-09-01
In this report, an application of control charts to the apparent feed composition of a Liquid-Fed Ceramic Melter (LFCM) is demonstrated by using results from a simulation of the LFCM system. Usual applications of control charts require the assumption of uncorrelated observations over time. This assumption is violated in the LFCM system because of the heels left in tanks from previous batches. Methods for dealing with this problem have been developed to create control charts for individual batches sent to the feed preparation tank (FPT). These control charts are capable of detecting changes in the process average as well as changes in the process variation. All numbers reported in this document were derived from a simulated demonstration of a plausible LFCM system. In practice, site-specific data must be used as input to a simulation tailored to that site. These data directly affect all variance estimates used to develop control charts. 64 refs., 3 figs., 2 tabs
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...
Applying multi-resolution numerical methods to geodynamics
Davies, David Rhodri
Computational models yield inaccurate results if the underlying numerical grid fails to provide the necessary resolution to capture a simulation's important features. For the large-scale problems regularly encountered in geodynamics, inadequate grid resolution is a major concern. The majority of models involve multi-scale dynamics, being characterized by fine-scale upwelling and downwelling activity in a more passive, large-scale background flow. Such configurations, when coupled to the complex geometries involved, present a serious challenge for computational methods. Current techniques are unable to resolve localized features and, hence, such models cannot be solved efficiently. This thesis demonstrates, through a series of papers and closely-coupled appendices, how multi-resolution finite-element methods from the forefront of computational engineering can provide a means to address these issues. The problems examined achieve multi-resolution through one of two methods. In two-dimensions (2-D), automatic, unstructured mesh refinement procedures are utilized. Such methods improve the solution quality of convection dominated problems by adapting the grid automatically around regions of high solution gradient, yielding enhanced resolution of the associated flow features. Thermal and thermo-chemical validation tests illustrate that the technique is robust and highly successful, improving solution accuracy whilst increasing computational efficiency. These points are reinforced when the technique is applied to geophysical simulations of mid-ocean ridge and subduction zone magmatism. To date, successful goal-orientated/error-guided grid adaptation techniques have not been utilized within the field of geodynamics. The work included herein is therefore the first geodynamical application of such methods. In view of the existing three-dimensional (3-D) spherical mantle dynamics codes, which are built upon a quasi-uniform discretization of the sphere and closely coupled
Analytic methods in applied probability in memory of Fridrikh Karpelevich
Suhov, Yu M
2002-01-01
This volume is dedicated to F. I. Karpelevich, an outstanding Russian mathematician who made important contributions to applied probability theory. The book contains original papers focusing on several areas of applied probability and its uses in modern industrial processes, telecommunications, computing, mathematical economics, and finance. It opens with a review of Karpelevich's contributions to applied probability theory and includes a bibliography of his works. Other articles discuss queueing network theory, in particular, in heavy traffic approximation (fluid models). The book is suitable
Reactor calculation in coarse mesh by finite element method applied to matrix response method
International Nuclear Information System (INIS)
Nakata, H.
1982-01-01
The finite element method is applied to the solution of the modified formulation of the matrix-response method aiming to do reactor calculations in coarse mesh. Good results are obtained with a short running time. The method is applicable to problems where the heterogeneity is predominant and to problems of evolution in coarse meshes where the burnup is variable in one same coarse mesh, making the cross section vary spatially with the evolution. (E.G.) [pt
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...
Testing statistical significance scores of sequence comparison methods with structure similarity
Directory of Open Access Journals (Sweden)
Leunissen Jack AM
2006-10-01
Full Text Available Abstract Background In the past years the Smith-Waterman sequence comparison algorithm has gained popularity due to improved implementations and rapidly increasing computing power. However, the quality and sensitivity of a database search is not only determined by the algorithm but also by the statistical significance testing for an alignment. The e-value is the most commonly used statistical validation method for sequence database searching. The CluSTr database and the Protein World database have been created using an alternative statistical significance test: a Z-score based on Monte-Carlo statistics. Several papers have described the superiority of the Z-score as compared to the e-value, using simulated data. We were interested if this could be validated when applied to existing, evolutionary related protein sequences. Results All experiments are performed on the ASTRAL SCOP database. The Smith-Waterman sequence comparison algorithm with both e-value and Z-score statistics is evaluated, using ROC, CVE and AP measures. The BLAST and FASTA algorithms are used as reference. We find that two out of three Smith-Waterman implementations with e-value are better at predicting structural similarities between proteins than the Smith-Waterman implementation with Z-score. SSEARCH especially has very high scores. Conclusion The compute intensive Z-score does not have a clear advantage over the e-value. The Smith-Waterman implementations give generally better results than their heuristic counterparts. We recommend using the SSEARCH algorithm combined with e-values for pairwise sequence comparisons.
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