Morphological representation of order-statistics filters.

Science.gov (United States)

Charif-Chefchaouni, M; Schonfeld, D

1995-01-01

We propose a comprehensive theory for the morphological bounds on order-statistics filters (and their repeated iterations). Conditions are derived for morphological openings and closings to serve as bounds (lower and upper, respectively) on order-statistics filters (and their repeated iterations). Under various assumptions, morphological open-closings and close-openings are also shown to serve as (tighter) bounds (lower and upper, respectively) on iterations of order-statistics filters. Simulations of the application of the results presented to image restoration are finally provided.

How Much Math Do Students Need to Succeed in Business and Economics Statistics? An Ordered Probit Analysis

OpenAIRE

Jeffrey J. Green; Courtenay C. Stone; Abera Zegeye; Thomas A. Charles

2008-01-01

Because statistical analysis requires both familiarity with and the ability to use mathematics, students typically are required to take one or more prerequisite math courses prior to enrolling in the business statistics course. Despite these math prerequisites, however, students find it extremely difficult to learn business statistics. In this study, we use an ordered probit model to examine the effect of alternative prerequisite math course sequences on the grade performance of 1,684 busines...

Penultimate modeling of spatial extremes: statistical inference for max-infinitely divisible processes

KAUST Repository

Huser, Raphaë l; Opitz, Thomas; Thibaud, Emeric

2018-01-01

Extreme-value theory for stochastic processes has motivated the statistical use of max-stable models for spatial extremes. However, fitting such asymptotic models to maxima observed over finite blocks is problematic when the asymptotic stability

Δim-lacunary statistical convergence of order α

Science.gov (United States)

Altınok, Hıfsı; Et, Mikail; Işık, Mahmut

2018-01-01

The purpose of this work is to introduce the concepts of Δim-lacunary statistical convergence of order α and lacunary strongly (Δim,p )-convergence of order α. We establish some connections between lacunary strongly (Δim,p )-convergence of order α and Δim-lacunary statistical convergence of order α. It is shown that if a sequence is lacunary strongly (Δim,p )-summable of order α then it is Δim-lacunary statistically convergent of order α.

Evaluation of stochastic weather generators for capturing the statistics of extreme precipitation events in the Catskill Mountain watersheds, New York State

Science.gov (United States)

Acharya, N.; Frei, A.; Owens, E. M.; Chen, J.

2015-12-01

Watersheds located in the Catskill Mountains area, part of the eastern plateau climate region of New York, contributes about 90% of New York City's municipal water supply, serving 9 million New Yorkers with about 1.2 billion gallons of clean drinking water each day. The New York City Department of Environmental Protection has an ongoing series of studies to assess the potential impacts of climate change on the availability of high quality water in this water supply system. Recent studies identify increasing trends in total precipitation and in the frequency of extreme precipitation events in this region. The objectives of the present study are: to analyze the proba­bilistic structure of extreme precipitation based on historical observations: and to evaluate the abilities of stochastic weather generators (WG), statistical models that produce synthetic weather time series based on observed statistical properties at a particular location, to simulate the statistical properties of extreme precipitation events over this region. The generalized extreme value distribution (GEV) has been applied to the annual block maxima of precipitation for 60 years (1950 to 2009) observed data in order to estimate the events with return periods of 50, 75, and 100 years. These results were then used to evaluate a total of 13 WGs were : 12 parametric WGs including all combinations of three different orders of Markov chain (MC) models (1st , 2nd and 3rd) and four different probability distributions (exponential, gamma, skewed normal and mixed exponential); and one semi parametric WG based on k-nearest neighbor bootstrapping. Preliminary results suggest that three-parameter (skewed normal and mixed exponential distribution) and semi-parametric (k-nearest neighbor bootstrapping) WGs are more consistent with observations. It is also found that first order MC models perform as well as second or third order MC models.

Statistical uncertainty of extreme wind storms over Europe derived from a probabilistic clustering technique

Science.gov (United States)

Walz, Michael; Leckebusch, Gregor C.

2016-04-01

Extratropical wind storms pose one of the most dangerous and loss intensive natural hazards for Europe. However, due to only 50 years of high quality observational data, it is difficult to assess the statistical uncertainty of these sparse events just based on observations. Over the last decade seasonal ensemble forecasts have become indispensable in quantifying the uncertainty of weather prediction on seasonal timescales. In this study seasonal forecasts are used in a climatological context: By making use of the up to 51 ensemble members, a broad and physically consistent statistical base can be created. This base can then be used to assess the statistical uncertainty of extreme wind storm occurrence more accurately. In order to determine the statistical uncertainty of storms with different paths of progression, a probabilistic clustering approach using regression mixture models is used to objectively assign storm tracks (either based on core pressure or on extreme wind speeds) to different clusters. The advantage of this technique is that the entire lifetime of a storm is considered for the clustering algorithm. Quadratic curves are found to describe the storm tracks most accurately. Three main clusters (diagonal, horizontal or vertical progression of the storm track) can be identified, each of which have their own particulate features. Basic storm features like average velocity and duration are calculated and compared for each cluster. The main benefit of this clustering technique, however, is to evaluate if the clusters show different degrees of uncertainty, e.g. more (less) spread for tracks approaching Europe horizontally (diagonally). This statistical uncertainty is compared for different seasonal forecast products.

Distributional Properties of Order Statistics and Record Statistics

Directory of Open Access Journals (Sweden)

Abdul Hamid Khan

2012-07-01

Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} Distributional properties of the order statistics, upper and lower records have been utilized to characterize distributions of interest. Further, one sided random dilation and contraction are utilized to obtain the distribution of non-adjacent ordered statistics and also their important deductions are discussed.

Wave-mixing with high-order harmonics in extreme ultraviolet region

International Nuclear Information System (INIS)

Dao, Lap Van; Dinh, Khuong Ba; Le, Hoang Vu; Gaffney, Naylyn; Hannaford, Peter

2015-01-01

We report studies of the wave-mixing process in the extreme ultraviolet region with two near-infrared driving and controlling pulses with incommensurate frequencies (at 1400 nm and 800 nm). A non-collinear scheme for the two beams is used in order to spatially separate and to characterise the properties of the high-order wave-mixing field. We show that the extreme ultraviolet frequency mixing can be treated by perturbative, very high-order nonlinear optics; the modification of the wave-packet of the free electron needs to be considered in this process

Statistical lamb wave localization based on extreme value theory

Science.gov (United States)

Harley, Joel B.

2018-04-01

Guided wave localization methods based on delay-and-sum imaging, matched field processing, and other techniques have been designed and researched to create images that locate and describe structural damage. The maximum value of these images typically represent an estimated damage location. Yet, it is often unclear if this maximum value, or any other value in the image, is a statistically significant indicator of damage. Furthermore, there are currently few, if any, approaches to assess the statistical significance of guided wave localization images. As a result, we present statistical delay-and-sum and statistical matched field processing localization methods to create statistically significant images of damage. Our framework uses constant rate of false alarm statistics and extreme value theory to detect damage with little prior information. We demonstrate our methods with in situ guided wave data from an aluminum plate to detect two 0.75 cm diameter holes. Our results show an expected improvement in statistical significance as the number of sensors increase. With seventeen sensors, both methods successfully detect damage with statistical significance.

Bayesian analysis applied to statistical uncertainties of extreme response distributions of offshore wind turbines

NARCIS (Netherlands)

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

Analysis of laser-induced breakdown spectroscopy spectra: The case for extreme value statistics

International Nuclear Information System (INIS)

Michel, Anna P.M.; Chave, Alan D.

2007-01-01

In most instances, laser-induced breakdown spectroscopy (LIBS) spectra are obtained through analog accumulation of multiple shots in the spectrometer CCD. The average acquired in the CCD at a given wavelength is assumed to be a good representation of the population mean, which in turn is implicitly regarded to be the best estimator for the central value of the distribution of the spectrum at the same wavelength. Multiple analog accumulated spectra are taken and then in turn averaged wavelength-by-wavelength to represent the final spectrum. In this paper, the statistics of single-shot and analog accumulated LIBS spectra of both solids and liquids were examined to evaluate whether the spectrum averaging approach is statistically defensible. At a given wavelength, LIBS spectra are typically drawn from a Frechet extreme value distribution, and hence the mean of an ensemble of LIBS spectra is not necessarily an optimal summary statistic. Under circumstances that are broadly general, the sample mean for LIBS data is statistically inconsistent and the central limit theorem does not apply. This result appears to be due to very high shot-to-shot plasma variability in which a very small number of spectra are high in intensity while the majority are very weak, yielding the extreme value form of the distribution. The extreme value behavior persists when individual shots are analog accumulated. An optimal estimator in a well-defined sense for the spectral average at a given wavelength follows from the maximum likelihood method for the extreme value distribution. Example spectra taken with both an Echelle and a Czerny-Turner spectrometer are processed with this scheme to create smooth, high signal-to-noise summary spectra. Plasma imaging was used in an attempt to visually understand the observed variability and to validate the use of extreme value statistics. The data processing approach presented in this paper is statistically reliable and should be used for accurate

A statistical methodology for the estimation of extreme wave conditions for offshore renewable applications

DEFF Research Database (Denmark)

Larsén, Xiaoli Guo; Kalogeri, Christina; Galanis, George

2015-01-01

and post-process outputs from a high resolution numerical wave modeling system for extreme wave estimation based on the significant wave height. This approach is demonstrated through the data analysis at a relatively deep water site, FINO 1, as well as a relatively shallow water area, coastal site Horns...... as a characteristic index of extreme wave conditions. The results from the proposed methodology seem to be in a good agreement with the measurements at both the relatively deep, open water and the shallow, coastal water sites, providing a potentially useful tool for offshore renewable energy applications. © 2015...... Rev, which is located in the North Sea, west of Denmark. The post-processing targets at correcting the modeled time series of the significant wave height, in order to match the statistics of the corresponding measurements, including not only the conventional parameters such as the mean and standard...

λ (Δim) -statistical convergence of order α

Science.gov (United States)

Colak, Rifat; Et, Mikail; Altin, Yavuz

2017-09-01

In this study, using the generalized difference operator Δim and a sequence λ = (λn) which is a non-decreasing sequence of positive numbers tending to ∞ such that λn+1 ≤ λn+1, λ1 = 1, we introduce the concepts of λ (Δim) -statistical convergence of order α (α ∈ (0, 1]) and strong λ (Δim) -Cesàro summablility of order α (α > 0). We establish some connections between λ (Δim) -statistical convergence of order α and strong λ (Δim) -Cesàro summablility of order α. It is shown that if a sequence is strongly λ (Δim) -Cesàro summable of order α, then it is λ (Δim) -statistically convergent of order β in case 0 < α ≤ β ≤ 1.

The German Birth Order Register - order-specific data generated from perinatal statistics and statistics on out-of-hospital births 2001-2008

OpenAIRE

Michaela Kreyenfeld; Rembrandt D. Scholz; Frederik Peters; Ines Wlosnewski

2010-01-01

Until 2008, Germany’s vital statistics did not include information on the biological order of each birth. This resulted in a dearth of important demographic indicators, such as the mean age at first birth and the level of childlessness. Researchers have tried to fill this gap by generating order-specific birth rates from survey data, and by combining survey data with vital statistics. This paper takes a different approach by using hospital statistics on births to generate birth order-specific...

Robust Combining of Disparate Classifiers Through Order Statistics

Science.gov (United States)

Tumer, Kagan; Ghosh, Joydeep

2001-01-01

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

A laboratory evaluation of the influence of weighing gauges performance on extreme events statistics

Science.gov (United States)

Colli, Matteo; Lanza, Luca

2014-05-01

The effects of inaccurate ground based rainfall measurements on the information derived from rain records is yet not much documented in the literature. La Barbera et al. (2002) investigated the propagation of the systematic mechanic errors of tipping bucket type rain gauges (TBR) into the most common statistics of rainfall extremes, e.g. in the assessment of the return period T (or the related non-exceedance probability) of short-duration/high intensity events. Colli et al. (2012) and Lanza et al. (2012) extended the analysis to a 22-years long precipitation data set obtained from a virtual weighing type gauge (WG). The artificial WG time series was obtained basing on real precipitation data measured at the meteo-station of the University of Genova and modelling the weighing gauge output as a linear dynamic system. This approximation was previously validated with dedicated laboratory experiments and is based on the evidence that the accuracy of WG measurements under real world/time varying rainfall conditions is mainly affected by the dynamic response of the gauge (as revealed during the last WMO Field Intercomparison of Rainfall Intensity Gauges). The investigation is now completed by analyzing actual measurements performed by two common weighing gauges, the OTT Pluvio2 load-cell gauge and the GEONOR T-200 vibrating-wire gauge, since both these instruments demonstrated very good performance under previous constant flow rate calibration efforts. A laboratory dynamic rainfall generation system has been arranged and validated in order to simulate a number of precipitation events with variable reference intensities. Such artificial events were generated basing on real world rainfall intensity (RI) records obtained from the meteo-station of the University of Genova so that the statistical structure of the time series is preserved. The influence of the WG RI measurements accuracy on the associated extreme events statistics is analyzed by comparing the original intensity

Statistical distributions of extreme dry spell in Peninsular Malaysia

Science.gov (United States)

Zin, Wan Zawiah Wan; Jemain, Abdul Aziz

2010-11-01

Statistical distributions of annual extreme (AE) series and partial duration (PD) series for dry-spell event are analyzed for a database of daily rainfall records of 50 rain-gauge stations in Peninsular Malaysia, with recording period extending from 1975 to 2004. The three-parameter generalized extreme value (GEV) and generalized Pareto (GP) distributions are considered to model both series. In both cases, the parameters of these two distributions are fitted by means of the L-moments method, which provides a robust estimation of them. The goodness-of-fit (GOF) between empirical data and theoretical distributions are then evaluated by means of the L-moment ratio diagram and several goodness-of-fit tests for each of the 50 stations. It is found that for the majority of stations, the AE and PD series are well fitted by the GEV and GP models, respectively. Based on the models that have been identified, we can reasonably predict the risks associated with extreme dry spells for various return periods.

Statistical and dynamical downscaling assessments of precipitation extremes in the Mediterranean area

Energy Technology Data Exchange (ETDEWEB)

Hertig, Elke; Seubert, Stefanie; Jacobeit, Jucundus [Augsburg Univ. (Germany). Inst. of Geography; Paxian, Andreas; Vogt, Gernot; Paeth, Heiko [Wuerzburg Univ. (Germany). Inst. of Geography and Geology

2012-02-15

Extreme precipitation events in the Mediterranean area have been defined by different percentile-based indices of extreme precipitation for autumn and winter: the number of events exceeding the 95{sup th} percentile of daily precipitation, percentage, total amount, and mean daily intensity of precipitation from these events. Results from statistical downscaling applying canonical correlation analysis as well as from dynamical downscaling using the regional climate model REMO are mapped for the 1961-1990 baseline period as well as for the magnitude of change for the future time slice 2021-2050 in relation to the former period. Direct output of the coupled global circulation model ECHAM5 is used as an additional source of information. A qualitative comparison of the two different downscaling techniques indicates that under the present climate both the dynamical and the statistical techniques have skill to reproduce extreme precipitation in the Mediterranean area. A good representation of the frequency of extreme precipitation events arises from the statistical downscaling approach, whereas the intensity of such events is adequately modelled by the dynamical downscaling. Concerning the change of extreme precipitation in the Mediterranean area until the mid-21{sup st} century, it is projected that the frequency of extreme precipitation events will decrease in most parts of the Mediterranean area in autumn and winter. The change of the mean intensity of such events shows a rather heterogeneous pattern with intensity increases in winter most likely at topographical elevations exposed to the West, where the uplift of humid air profits by the increase of atmospheric moisture under climate change conditions. For the precipitation total from events exceeding the 95{sup th} percentile of daily precipitation, widespread decreases are indicated in autumn, whereas in winter increases occur over the western part of the Iberian Peninsula and southern France, and reductions over

Ordered random variables theory and applications

CERN Document Server

Shahbaz, Muhammad Qaiser; Hanif Shahbaz, Saman; Al-Zahrani, Bander M

2016-01-01

Ordered Random Variables have attracted several authors. The basic building block of Ordered Random Variables is Order Statistics which has several applications in extreme value theory and ordered estimation. The general model for ordered random variables, known as Generalized Order Statistics has been introduced relatively recently by Kamps (1995).

Order-specific fertility estimates based on perinatal statistics and statistics on out-of-hospital births

OpenAIRE

Kreyenfeld, Michaela; Peters, Frederik; Scholz, Rembrandt; Wlosnewski, Ines

2014-01-01

Until 2008, German vital statistics has not provided information on biological birth order. We have tried to close part of this gap by providing order-specific fertility rates generated from Perinatal Statistics and statistics on out-of-hospital births for the period 2001-2008. This investigation has been published in Comparative Population Studies (CPoS) (see Kreyenfeld, Scholz, Peters and Wlosnewski 2010). The CPoS-paper describes how data from the Perinatal Statistics and statistics on out...

Improving the Statistical Modeling of the TRMM Extreme Precipitation Monitoring System

Science.gov (United States)

Demirdjian, L.; Zhou, Y.; Huffman, G. J.

2016-12-01

This project improves upon an existing extreme precipitation monitoring system based on the Tropical Rainfall Measuring Mission (TRMM) daily product (3B42) using new statistical models. The proposed system utilizes a regional modeling approach, where data from similar grid locations are pooled to increase the quality and stability of the resulting model parameter estimates to compensate for the short data record. The regional frequency analysis is divided into two stages. In the first stage, the region defined by the TRMM measurements is partitioned into approximately 27,000 non-overlapping clusters using a recursive k-means clustering scheme. In the second stage, a statistical model is used to characterize the extreme precipitation events occurring in each cluster. Instead of utilizing the block-maxima approach used in the existing system, where annual maxima are fit to the Generalized Extreme Value (GEV) probability distribution at each cluster separately, the present work adopts the peak-over-threshold (POT) method of classifying points as extreme if they exceed a pre-specified threshold. Theoretical considerations motivate the use of the Generalized-Pareto (GP) distribution for fitting threshold exceedances. The fitted parameters can be used to construct simple and intuitive average recurrence interval (ARI) maps which reveal how rare a particular precipitation event is given its spatial location. The new methodology eliminates much of the random noise that was produced by the existing models due to a short data record, producing more reasonable ARI maps when compared with NOAA's long-term Climate Prediction Center (CPC) ground based observations. The resulting ARI maps can be useful for disaster preparation, warning, and management, as well as increased public awareness of the severity of precipitation events. Furthermore, the proposed methodology can be applied to various other extreme climate records.

Order, disorder and generalized statistics

International Nuclear Information System (INIS)

Marino, E.C.; Swieca, J.A.

1980-06-01

We generalize the prescription of Kadanoff and Ceva for the computation of disorder variables correlation functions in the Ising model for continuous field theories with U(1) symmetry. By considering the product of order and disorder variables, we obtain a path integral representation for fields with generalized statistics. We discuss in detail the cases of massless Thirring and Schwinger models. (Author) [pt

Order, disorder and generalized statistics

International Nuclear Information System (INIS)

Marino, E.C.; Swieca, J.A.; Pontificia Universidade Catolica do Rio de Janeiro

1980-01-01

We generalize the prescription of Kadanoff and Ceva for the computation of disorder variable correlation functions in the Ising model for continuous field theories with U(1) symmetry. By considering the product of order and disorder variables, we obtain a path integral representation for fields with generalized statistics. We discuss in detail the cases of massless Thirring and Schwinger models. (orig.)

Analysis of stress corrosion data by means of the statistic of extreme values

International Nuclear Information System (INIS)

Imarisio, G.; Lanza, F.

1978-01-01

The possibility of examining stress corosion by means of extreme statistic was proposed. A series of test in boiling MgCl 2 of samples made on AISI 304 have been performed. Evolution of cracks dimension and time of life of samples was followed. It has been shown that the dimensions of the maximum cracks on the sample corroded for different times can be organized following the extreme values statistic. Also the life time of sample can be treated in the same way. A confirmation has been obtained using data taken from literature. Possible uses of predictions obtained with this type of analysis have been underlined. An extension of the toward less corrosive media and samples of several volumes is suggested to check the validity of the method

Neurodevelopmental outcomes of triplets or higher-order extremely low birth weight infants.

Science.gov (United States)

Wadhawan, Rajan; Oh, William; Vohr, Betty R; Wrage, Lisa; Das, Abhik; Bell, Edward F; Laptook, Abbot R; Shankaran, Seetha; Stoll, Barbara J; Walsh, Michele C; Higgins, Rosemary D

2011-03-01

Extremely low birth weight twins have a higher rate of death or neurodevelopmental impairment than singletons. Higher-order extremely low birth weight multiple births may have an even higher rate of death or neurodevelopmental impairment. Extremely low birth weight (birth weight 401-1000 g) multiple births born in participating centers of the Neonatal Research Network between 1996 and 2005 were assessed for death or neurodevelopmental impairment at 18 to 22 months' corrected age. Neurodevelopmental impairment was defined by the presence of 1 or more of the following: moderate to severe cerebral palsy; mental developmental index score or psychomotor developmental index score less than 70; severe bilateral deafness; or blindness. Infants who died within 12 hours of birth were excluded. Maternal and infant demographic and clinical variables were compared among singleton, twin, and triplet or higher-order infants. Logistic regression analysis was performed to establish the association between singletons, twins, and triplet or higher-order multiples and death or neurodevelopmental impairment, controlling for confounding variables that may affect death or neurodevelopmental impairment. Our cohort consisted of 8296 singleton, 2164 twin, and 521 triplet or higher-order infants. The risk of death or neurodevelopmental impairment was increased in triplets or higher-order multiples when compared with singletons (adjusted odds ratio: 1.7 [95% confidence interval: 1.29-2.24]), and there was a trend toward an increased risk when compared with twins (adjusted odds ratio: 1.27 [95% confidence: 0.95-1.71]). Triplet or higher-order births are associated with an increased risk of death or neurodevelopmental impairment at 18 to 22 months' corrected age when compared with extremely low birth weight singleton infants, and there was a trend toward an increased risk when compared with twins.

Methodology for featuring and assessing extreme climatic events

International Nuclear Information System (INIS)

Malleron, N.; Bernardara, P.; Benoit, M.; Parey, S.; Perret, C.

2013-01-01

The setting up of a nuclear power plant on a particular site requires the assessment of risks linked to extreme natural events like flooding or earthquakes. As a consequence of the Fukushima accident EDF proposes to take into account even rarer events in order to improve the robustness of the facility all over its operating life. This article presents the methodology used by EDF to analyse a set of data in a statistical way in order to extract extreme values. This analysis is based on the theory of extreme values and is applied to the extreme values of the flow rate in the case of a river overflowing. This methodology is made of 6 steps: 1) selection of the event, of its featuring parameter and of its probability, for instance the question is what is the flow rate of a flooding that has a probability of 10 -3 to happen, 2) to collect data over a long period of time (or to recover data from past periods), 3) to extract extreme values from the data, 4) to find an adequate statistical law that fits the spreading of the extreme values, 5) the selected statistical law must be validated through visual or statistical tests, and 6) the computation of the flow rate of the event itself. (A.C.)

Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

Science.gov (United States)

Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

2015-05-01

The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events. Copyright © 2015 Elsevier Ltd. All rights reserved.

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Science.gov (United States)

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Directory of Open Access Journals (Sweden)

Zhong Yi Wan

Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more

Sensitivity analysis of ranked data: from order statistics to quantiles

NARCIS (Netherlands)

Heidergott, B.F.; Volk-Makarewicz, W.

2015-01-01

In this paper we provide the mathematical theory for sensitivity analysis of order statistics of continuous random variables, where the sensitivity is with respect to a distributional parameter. Sensitivity analysis of order statistics over a finite number of observations is discussed before

Extreme value statistics and thermodynamics of earthquakes. Large earthquakes

Energy Technology Data Exchange (ETDEWEB)

Lavenda, B. [Camerino Univ., Camerino, MC (Italy); Cipollone, E. [ENEA, Centro Ricerche Casaccia, S. Maria di Galeria, RM (Italy). National Centre for Research on Thermodynamics

2000-06-01

A compound Poisson process is used to derive a new shape parameter which can be used to discriminate between large earthquakes and aftershocks sequences. Sample exceedance distributions of large earthquakes are fitted to the Pareto tail and the actual distribution of the maximum to the Frechet distribution, while the sample distribution of aftershocks are fitted to a Beta distribution and the distribution of the minimum to the Weibull distribution for the smallest value. The transition between initial sample distributions and asymptotic extreme value distributions show that self-similar power laws are transformed into non scaling exponential distributions so that neither self-similarity nor the Gutenberg-Richter law can be considered universal. The energy-magnitude transformation converts the Frechet distribution into the Gumbel distribution, originally proposed by Epstein and Lomnitz, and not the Gompertz distribution as in the Lomnitz-Adler and Lomnitz generalization of the Gutenberg-Richter law. Numerical comparison is made with the Lomnitz-Adler and Lomnitz analysis using the same catalogue of Chinese earthquakes. An analogy is drawn between large earthquakes and high energy particle physics. A generalized equation of state is used to transform the Gamma density into the order-statistic Frechet distribution. Earthquake temperature and volume are determined as functions of the energy. Large insurance claims based on the Pareto distribution, which does not have a right endpoint, show why there cannot be a maximum earthquake energy.

Inter-comparison of statistical downscaling methods for projection of extreme flow indices across Europe

DEFF Research Database (Denmark)

Hundecha, Yeshewatesfa; Sunyer Pinya, Maria Antonia; Lawrence, Deborah

2016-01-01

The effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171km2 in size...... catchments to simulate daily runoff. A set of flood indices were derived from daily flows and their changes have been evaluated by comparing their values derived from simulations corresponding to the current and future climate. Most of the implemented downscaling methods project an increase in the extreme...... flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall-dominated flood regime. In these catchments, the downscaling methods also project an increase in the extreme precipitation in the seasons when the extreme flows occur. In catchments where...

f-lacunary statistical convergence of order (α, β)

Science.gov (United States)

Sengul, Hacer; Isik, Mahmut; Et, Mikail

2017-09-01

The main purpose of this paper is to introduce the concepts of f-lacunary statistical convergence of order (α, β) and strong f-lacunary summability of order (α, β) of sequences of real numbers for 0 <α ≤ β ≤ 1, where f is an unbounded modulus.

Order statistics & inference estimation methods

CERN Document Server

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

Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

Science.gov (United States)

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

Extreme value statistics and thermodynamics of earthquakes: large earthquakes

Directory of Open Access Journals (Sweden)

B. H. Lavenda

2000-06-01

Full Text Available A compound Poisson process is used to derive a new shape parameter which can be used to discriminate between large earthquakes and aftershock sequences. Sample exceedance distributions of large earthquakes are fitted to the Pareto tail and the actual distribution of the maximum to the Fréchet distribution, while the sample distribution of aftershocks are fitted to a Beta distribution and the distribution of the minimum to the Weibull distribution for the smallest value. The transition between initial sample distributions and asymptotic extreme value distributions shows that self-similar power laws are transformed into nonscaling exponential distributions so that neither self-similarity nor the Gutenberg-Richter law can be considered universal. The energy-magnitude transformation converts the Fréchet distribution into the Gumbel distribution, originally proposed by Epstein and Lomnitz, and not the Gompertz distribution as in the Lomnitz-Adler and Lomnitz generalization of the Gutenberg-Richter law. Numerical comparison is made with the Lomnitz-Adler and Lomnitz analysis using the same Catalogue of Chinese Earthquakes. An analogy is drawn between large earthquakes and high energy particle physics. A generalized equation of state is used to transform the Gamma density into the order-statistic Fréchet distribution. Earthquaketemperature and volume are determined as functions of the energy. Large insurance claims based on the Pareto distribution, which does not have a right endpoint, show why there cannot be a maximum earthquake energy.

Statistical inference for the lifetime performance index based on generalised order statistics from exponential distribution

Science.gov (United States)

Vali Ahmadi, Mohammad; Doostparast, Mahdi; Ahmadi, Jafar

2015-04-01

In manufacturing industries, the lifetime of an item is usually characterised by a random variable X and considered to be satisfactory if X exceeds a given lower lifetime limit L. The probability of a satisfactory item is then ηL := P(X ≥ L), called conforming rate. In industrial companies, however, the lifetime performance index, proposed by Montgomery and denoted by CL, is widely used as a process capability index instead of the conforming rate. Assuming a parametric model for the random variable X, we show that there is a connection between the conforming rate and the lifetime performance index. Consequently, the statistical inferences about ηL and CL are equivalent. Hence, we restrict ourselves to statistical inference for CL based on generalised order statistics, which contains several ordered data models such as usual order statistics, progressively Type-II censored data and records. Various point and interval estimators for the parameter CL are obtained and optimal critical regions for the hypothesis testing problems concerning CL are proposed. Finally, two real data-sets on the lifetimes of insulating fluid and ball bearings, due to Nelson (1982) and Caroni (2002), respectively, and a simulated sample are analysed.

Synchronization from Second Order Network Connectivity Statistics

Science.gov (United States)

Zhao, Liqiong; Beverlin, Bryce; Netoff, Theoden; Nykamp, Duane Q.

2011-01-01

We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections, and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by their increasing the effective coupling strength. The decrease of synchrony with convergent connections is primarily due to the resulting heterogeneity in firing rates. PMID:21779239

Intensity changes in future extreme precipitation: A statistical event-based approach.

Science.gov (United States)

Manola, Iris; van den Hurk, Bart; de Moel, Hans; Aerts, Jeroen

2017-04-01

Short-lived precipitation extremes are often responsible for hazards in urban and rural environments with economic and environmental consequences. The precipitation intensity is expected to increase about 7% per degree of warming, according to the Clausius-Clapeyron (CC) relation. However, the observations often show a much stronger increase in the sub-daily values. In particular, the behavior of the hourly summer precipitation from radar observations with the dew point temperature (the Pi-Td relation) for the Netherlands suggests that for moderate to warm days the intensification of the precipitation can be even higher than 21% per degree of warming, that is 3 times higher than the expected CC relation. The rate of change depends on the initial precipitation intensity, as low percentiles increase with a rate below CC, the medium percentiles with 2CC and the moderate-high and high percentiles with 3CC. This non-linear statistical Pi-Td relation is suggested to be used as a delta-transformation to project how a historic extreme precipitation event would intensify under future, warmer conditions. Here, the Pi-Td relation is applied over a selected historic extreme precipitation event to 'up-scale' its intensity to warmer conditions. Additionally, the selected historic event is simulated in the high-resolution, convective-permitting weather model Harmonie. The initial and boundary conditions are alternated to represent future conditions. The comparison between the statistical and the numerical method of projecting the historic event to future conditions showed comparable intensity changes, which depending on the initial percentile intensity, range from below CC to a 3CC rate of change per degree of warming. The model tends to overestimate the future intensities for the low- and the very high percentiles and the clouds are somewhat displaced, due to small wind and convection changes. The total spatial cloud coverage in the model remains, as also in the statistical

Statistical similarities of pre-earthquake electromagnetic emissions to biological and economic extreme events

Science.gov (United States)

Potirakis, Stelios M.; Contoyiannis, Yiannis; Kopanas, John; Kalimeris, Anastasios; Antonopoulos, George; Peratzakis, Athanasios; Eftaxias, Konstantinos; Nomicos, Costantinos

2014-05-01

When one considers a phenomenon that is "complex" refers to a system whose phenomenological laws that describe the global behavior of the system, are not necessarily directly related to the "microscopic" laws that regulate the evolution of its elementary parts. The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe disparate problems ranging from particle physics to economies of societies. Several authors have suggested that earthquake (EQ) dynamics can be analyzed within similar mathematical frameworks with economy dynamics, and neurodynamics. A central property of the EQ preparation process is the occurrence of coherent large-scale collective behavior with a very rich structure, resulting from repeated nonlinear interactions among the constituents of the system. As a result, nonextensive statistics is an appropriate, physically meaningful, tool for the study of EQ dynamics. Since the fracture induced electromagnetic (EM) precursors are observable manifestations of the underlying EQ preparation process, the analysis of a fracture induced EM precursor observed prior to the occurrence of a large EQ can also be conducted within the nonextensive statistics framework. Within the frame of the investigation for universal principles that may hold for different dynamical systems that are related to the genesis of extreme events, we present here statistical similarities of the pre-earthquake EM emissions related to an EQ, with the pre-ictal electrical brain activity related to an epileptic seizure, and with the pre-crisis economic observables related to the collapse of a share. It is demonstrated the all three dynamical systems' observables can be analyzed in the frame of nonextensive statistical mechanics, while the frequency-size relations of appropriately defined "events" that precede the extreme event related to each one of these different systems present striking quantitative

Quantum Statistical Entropy of Non-extreme and Nearly Extreme Black Holes in Higher-Dimensional Space-Time

Institute of Scientific and Technical Information of China (English)

XU Dian-Yan

2003-01-01

The free energy and entropy of Reissner-Nordstrom black holes in higher-dimensional space-time are calculated by the quantum statistic method with a brick wall model. The space-time of the black holes is divided into three regions: region 1, (r > r0); region 2, (r0 > r > n); and region 3, (T-J > r > 0), where r0 is the radius of the outer event horizon, and r, is the radius of the inner event horizon. Detailed calculation shows that the entropy contributed by region 2 is zero, the entropy contributed by region 1 is positive and proportional to the outer event horizon area, the entropy contributed by region 3 is negative and proportional to the inner event horizon area. The total entropy contributed by all the three regions is positive and proportional to the area difference between the outer and inner event horizons. As rt approaches r0 in the nearly extreme case, the total quantum statistical entropy approaches zero.

Sub-Poissonian statistics in order-to-chaos transition

International Nuclear Information System (INIS)

Kryuchkyan, Gagik Yu.; Manvelyan, Suren B.

2003-01-01

We study the phenomena at the overlap of quantum chaos and nonclassical statistics for the time-dependent model of nonlinear oscillator. It is shown in the framework of Mandel Q parameter and Wigner function that the statistics of oscillatory excitation numbers is drastically changed in the order-to-chaos transition. The essential improvement of sub-Poissonian statistics in comparison with an analogous one for the standard model of driven anharmonic oscillator is observed for the regular operational regime. It is shown that in the chaotic regime, the system exhibits the range of sub-Poissonian and super-Poissonian statistics which alternate one to other depending on time intervals. Unusual dependence of the variance of oscillatory number on the external noise level for the chaotic dynamics is observed. The scaling invariance of the quantum statistics is demonstrated and its relation to dissipation and decoherence is studied

Penultimate modeling of spatial extremes: statistical inference for max-infinitely divisible processes

KAUST Repository

Huser, Raphaël

2018-01-09

Extreme-value theory for stochastic processes has motivated the statistical use of max-stable models for spatial extremes. However, fitting such asymptotic models to maxima observed over finite blocks is problematic when the asymptotic stability of the dependence does not prevail in finite samples. This issue is particularly serious when data are asymptotically independent, such that the dependence strength weakens and eventually vanishes as events become more extreme. We here aim to provide flexible sub-asymptotic models for spatially indexed block maxima, which more realistically account for discrepancies between data and asymptotic theory. We develop models pertaining to the wider class of max-infinitely divisible processes, extending the class of max-stable processes while retaining dependence properties that are natural for maxima: max-id models are positively associated, and they yield a self-consistent family of models for block maxima defined over any time unit. We propose two parametric construction principles for max-id models, emphasizing a point process-based generalized spectral representation, that allows for asymptotic independence while keeping the max-stable extremal-$t$ model as a special case. Parameter estimation is efficiently performed by pairwise likelihood, and we illustrate our new modeling framework with an application to Dutch wind gust maxima calculated over different time units.

Models and Inference for Multivariate Spatial Extremes

KAUST Repository

Vettori, Sabrina

2017-01-01

The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing

To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

DEFF Research Database (Denmark)

Schaarup-Jensen, Kjeld; Rasmussen, Michael R.; Thorndahl, Søren

2008-01-01

In urban drainage modeling long term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties concerning long term prediction of maximum water levels and combined sewer...... overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO...... gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity...

To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

DEFF Research Database (Denmark)

Schaarup-Jensen, Kjeld; Rasmussen, Michael R.; Thorndahl, Søren

2009-01-01

In urban drainage modelling long term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties concerning long term prediction of maximum water levels and combined sewer...... overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO...... gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity...

Convergence of Extreme Value Statistics in a Two-Layer Quasi-Geostrophic Atmospheric Model

Directory of Open Access Journals (Sweden)

Vera Melinda Gálfi

2017-01-01

Full Text Available We search for the signature of universal properties of extreme events, theoretically predicted for Axiom A flows, in a chaotic and high-dimensional dynamical system. We study the convergence of GEV (Generalized Extreme Value and GP (Generalized Pareto shape parameter estimates to the theoretical value, which is expressed in terms of the partial information dimensions of the attractor. We consider a two-layer quasi-geostrophic atmospheric model of the mid-latitudes, adopt two levels of forcing, and analyse the extremes of different types of physical observables (local energy, zonally averaged energy, and globally averaged energy. We find good agreement in the shape parameter estimates with the theory only in the case of more intense forcing, corresponding to a strong chaotic behaviour, for some observables (the local energy at every latitude. Due to the limited (though very large data size and to the presence of serial correlations, it is difficult to obtain robust statistics of extremes in the case of the other observables. In the case of weak forcing, which leads to weaker chaotic conditions with regime behaviour, we find, unsurprisingly, worse agreement with the theory developed for Axiom A flows.

Extreme events in total ozone over Arosa – Part 1: Application of extreme value theory

Directory of Open Access Journals (Sweden)

H. E. Rieder

2010-10-01

Full Text Available In this study ideas from extreme value theory are for the first time applied in the field of stratospheric ozone research, because statistical analysis showed that previously used concepts assuming a Gaussian distribution (e.g. fixed deviations from mean values of total ozone data do not adequately address the structure of the extremes. We show that statistical extreme value methods are appropriate to identify ozone extremes and to describe the tails of the Arosa (Switzerland total ozone time series. In order to accommodate the seasonal cycle in total ozone, a daily moving threshold was determined and used, with tools from extreme value theory, to analyse the frequency of days with extreme low (termed ELOs and high (termed EHOs total ozone at Arosa. The analysis shows that the Generalized Pareto Distribution (GPD provides an appropriate model for the frequency distribution of total ozone above or below a mathematically well-defined threshold, thus providing a statistical description of ELOs and EHOs. The results show an increase in ELOs and a decrease in EHOs during the last decades. The fitted model represents the tails of the total ozone data set with high accuracy over the entire range (including absolute monthly minima and maxima, and enables a precise computation of the frequency distribution of ozone mini-holes (using constant thresholds. Analyzing the tails instead of a small fraction of days below constant thresholds provides deeper insight into the time series properties. Fingerprints of dynamical (e.g. ENSO, NAO and chemical features (e.g. strong polar vortex ozone loss, and major volcanic eruptions, can be identified in the observed frequency of extreme events throughout the time series. Overall the new approach to analysis of extremes provides more information on time series properties and variability than previous approaches that use only monthly averages and/or mini-holes and mini-highs.

STATISTICAL STUDY OF STRONG AND EXTREME GEOMAGNETIC DISTURBANCES AND SOLAR CYCLE CHARACTERISTICS

International Nuclear Information System (INIS)

Kilpua, E. K. J.; Olspert, N.; Grigorievskiy, A.; Käpylä, M. J.; Tanskanen, E. I.; Pelt, J.; Miyahara, H.; Kataoka, R.; Liu, Y. D.

2015-01-01

We study the relation between strong and extreme geomagnetic storms and solar cycle characteristics. The analysis uses an extensive geomagnetic index AA data set spanning over 150 yr complemented by the Kakioka magnetometer recordings. We apply Pearson correlation statistics and estimate the significance of the correlation with a bootstrapping technique. We show that the correlation between the storm occurrence and the strength of the solar cycle decreases from a clear positive correlation with increasing storm magnitude toward a negligible relationship. Hence, the quieter Sun can also launch superstorms that may lead to significant societal and economic impact. Our results show that while weaker storms occur most frequently in the declining phase, the stronger storms have the tendency to occur near solar maximum. Our analysis suggests that the most extreme solar eruptions do not have a direct connection between the solar large-scale dynamo-generated magnetic field, but are rather associated with smaller-scale dynamo and resulting turbulent magnetic fields. The phase distributions of sunspots and storms becoming increasingly in phase with increasing storm strength, on the other hand, may indicate that the extreme storms are related to the toroidal component of the solar large-scale field

STATISTICAL STUDY OF STRONG AND EXTREME GEOMAGNETIC DISTURBANCES AND SOLAR CYCLE CHARACTERISTICS

Energy Technology Data Exchange (ETDEWEB)

Kilpua, E. K. J. [Department of Physics, University Helsinki (Finland); Olspert, N.; Grigorievskiy, A.; Käpylä, M. J.; Tanskanen, E. I.; Pelt, J. [ReSoLVE Centre of Excellence, Department of Computer Science, P.O. Box 15400, FI-00076 Aalto Univeristy (Finland); Miyahara, H. [Musashino Art University, 1-736 Ogawa-cho, Kodaira-shi, Tokyo 187-8505 (Japan); Kataoka, R. [National Institute of Polar Research, 10-3 Midori-cho, Tachikawa, Tokyo 190-8518 (Japan); Liu, Y. D. [State Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing 100190 (China)

2015-06-20

We study the relation between strong and extreme geomagnetic storms and solar cycle characteristics. The analysis uses an extensive geomagnetic index AA data set spanning over 150 yr complemented by the Kakioka magnetometer recordings. We apply Pearson correlation statistics and estimate the significance of the correlation with a bootstrapping technique. We show that the correlation between the storm occurrence and the strength of the solar cycle decreases from a clear positive correlation with increasing storm magnitude toward a negligible relationship. Hence, the quieter Sun can also launch superstorms that may lead to significant societal and economic impact. Our results show that while weaker storms occur most frequently in the declining phase, the stronger storms have the tendency to occur near solar maximum. Our analysis suggests that the most extreme solar eruptions do not have a direct connection between the solar large-scale dynamo-generated magnetic field, but are rather associated with smaller-scale dynamo and resulting turbulent magnetic fields. The phase distributions of sunspots and storms becoming increasingly in phase with increasing storm strength, on the other hand, may indicate that the extreme storms are related to the toroidal component of the solar large-scale field.

The probability distribution of extreme precipitation

Science.gov (United States)

Korolev, V. Yu.; Gorshenin, A. K.

2017-12-01

On the basis of the negative binomial distribution of the duration of wet periods calculated per day, an asymptotic model is proposed for distributing the maximum daily rainfall volume during the wet period, having the form of a mixture of Frechet distributions and coinciding with the distribution of the positive degree of a random variable having the Fisher-Snedecor distribution. The method of proving the corresponding result is based on limit theorems for extreme order statistics in samples of a random volume with a mixed Poisson distribution. The adequacy of the models proposed and methods of their statistical analysis is demonstrated by the example of estimating the extreme distribution parameters based on real data.

Capturing rogue waves by multi-point statistics

International Nuclear Information System (INIS)

Hadjihosseini, A; Wächter, Matthias; Peinke, J; Hoffmann, N P

2016-01-01

As an example of a complex system with extreme events, we investigate ocean wave states exhibiting rogue waves. We present a statistical method of data analysis based on multi-point statistics which for the first time allows the grasping of extreme rogue wave events in a highly satisfactory statistical manner. The key to the success of the approach is mapping the complexity of multi-point data onto the statistics of hierarchically ordered height increments for different time scales, for which we can show that a stochastic cascade process with Markov properties is governed by a Fokker–Planck equation. Conditional probabilities as well as the Fokker–Planck equation itself can be estimated directly from the available observational data. With this stochastic description surrogate data sets can in turn be generated, which makes it possible to work out arbitrary statistical features of the complex sea state in general, and extreme rogue wave events in particular. The results also open up new perspectives for forecasting the occurrence probability of extreme rogue wave events, and even for forecasting the occurrence of individual rogue waves based on precursory dynamics. (paper)

Non-Gaussian statistics of extreme events in stimulated Raman scattering: The role of coherent memory and source noise

Science.gov (United States)

Monfared, Yashar E.; Ponomarenko, Sergey A.

2017-10-01

We explore theoretically and numerically extreme event excitation in stimulated Raman scattering in gases. We consider gas-filled hollow-core photonic crystal fibers as a particular system realization. We show that moderate amplitude pump fluctuations obeying Gaussian statistics lead to the emergence of heavy-tailed non-Gaussian statistics as coherent seed Stokes pulses are amplified on propagation along the fiber. We reveal the crucial role that coherent memory effects play in causing non-Gaussian statistics of the system. We discover that extreme events can occur even at the initial stage of stimulated Raman scattering when one can neglect energy depletion of an intense, strongly fluctuating Gaussian pump source. Our analytical results in the undepleted pump approximation explicitly illustrate power-law probability density generation as the input pump noise is transferred to the output Stokes pulses.

Extreme value statistics and finite-size scaling at the ecological extinction/laminar-turbulence transition

Science.gov (United States)

Shih, Hong-Yan; Goldenfeld, Nigel

Experiments on transitional turbulence in pipe flow seem to show that turbulence is a transient metastable state since the measured mean lifetime of turbulence puffs does not diverge asymptotically at a critical Reynolds number. Yet measurements reveal that the lifetime scales with Reynolds number in a super-exponential way reminiscent of extreme value statistics, and simulations and experiments in Couette and channel flow exhibit directed percolation type scaling phenomena near a well-defined transition. This universality class arises from the interplay between small-scale turbulence and a large-scale collective zonal flow, which exhibit predator-prey behavior. Why is asymptotically divergent behavior not observed? Using directed percolation and a stochastic individual level model of predator-prey dynamics related to transitional turbulence, we investigate the relation between extreme value statistics and power law critical behavior, and show that the paradox is resolved by carefully defining what is measured in the experiments. We theoretically derive the super-exponential scaling law, and using finite-size scaling, show how the same data can give both super-exponential behavior and power-law critical scaling.

Statistical Modeling of Extreme Values and Evidence of Presence of Dragon King (DK) in Solar Wind

Science.gov (United States)

Gomes, T.; Ramos, F.; Rempel, E. L.; Silva, S.; C-L Chian, A.

2017-12-01

The solar wind constitutes a nonlinear dynamical system, presenting intermittent turbulence, multifractality and chaotic dynamics. One characteristic shared by many such complex systems is the presence of extreme events, that play an important role in several Geophysical phenomena and their statistical characterization is a problem of great practical relevance. This work investigates the presence of extreme events in time series of the modulus of the interplanetary magnetic field measured by Cluster spacecraft on February 2, 2002. One of the main results is that the solar wind near the Earth's bow shock can be modeled by the Generalized Pareto (GP) and Generalized Extreme Values (GEV) distributions. Both models present a statistically significant positive shape parameter which implyies a heavy tail in the probability distribution functions and an unbounded growth in return values as return periods become too long. There is evidence that current sheets are the main responsible for positive values of the shape parameter. It is also shown that magnetic reconnection at the interface between two interplanetary magnetic flux ropes in the solar wind can be considered as Dragon Kings (DK), a class of extreme events whose formation mechanisms are fundamentally different from others. As long as magnetic reconnection can be classified as a Dragon King, there is the possibility of its identification and even its prediction. Dragon kings had previously been identified in time series of financial crashes, nuclear power generation accidents, stock market and so on. It is believed that they are associated with the occurrence of extreme events in dynamical systems at phase transition, bifurcation, crises or tipping points.

Synchronization from second order network connectivity statistics

Directory of Open Access Journals (Sweden)

Liqiong eZhao

2011-07-01

Full Text Available We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks (SONETs, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by a pool and redistribute mechanism. The pooling of many inputs averages out independent fluctuations, amplifying weak correlations in the inputs. With increased chain connections, neurons with many inputs tend to have many outputs. Hence, chains ensure that the amplified correlations in the neurons with many inputs are redistributed throughout the network, enhancing the development of synchrony across the network.

Drivers and seasonal predictability of extreme wind speeds in the ECMWF System 4 and a statistical model

Science.gov (United States)

Walz, M. A.; Donat, M.; Leckebusch, G. C.

2017-12-01

As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.

Ordering statistics of four random walkers on a line

Science.gov (United States)

Helenbrook, Brian; ben-Avraham, Daniel

2018-05-01

We study the ordering statistics of four random walkers on the line, obtaining a much improved estimate for the long-time decay exponent of the probability that a particle leads to time t , Plead(t ) ˜t-0.91287850 , and that a particle lags to time t (never assumes the lead), Plag(t ) ˜t-0.30763604 . Exponents of several other ordering statistics for N =4 walkers are obtained to eight-digit accuracy as well. The subtle correlations between n walkers that lag jointly, out of a field of N , are discussed: for N =3 there are no correlations and Plead(t ) ˜Plag(t) 2 . In contrast, our results rule out the possibility that Plead(t ) ˜Plag(t) 3 for N =4 , although the correlations in this borderline case are tiny.

Nonparametric Bayesian predictive distributions for future order statistics

Science.gov (United States)

Richard A. Johnson; James W. Evans; David W. Green

1999-01-01

We derive the predictive distribution for a specified order statistic, determined from a future random sample, under a Dirichlet process prior. Two variants of the approach are treated and some limiting cases studied. A practical application to monitoring the strength of lumber is discussed including choices of prior expectation and comparisons made to a Bayesian...

Power-law scaling of extreme dynamics near higher-order exceptional points

Science.gov (United States)

Zhong, Q.; Christodoulides, D. N.; Khajavikhan, M.; Makris, K. G.; El-Ganainy, R.

2018-02-01

We investigate the extreme dynamics of non-Hermitian systems near higher-order exceptional points in photonic networks constructed using the bosonic algebra method. We show that strong power oscillations for certain initial conditions can occur as a result of the peculiar eigenspace geometry and its dimensionality collapse near these singularities. By using complementary numerical and analytical approaches, we show that, in the parity-time (PT ) phase near exceptional points, the logarithm of the maximum optical power amplification scales linearly with the order of the exceptional point. We focus in our discussion on photonic systems, but we note that our results apply to other physical systems as well.

Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

Science.gov (United States)

Sapsis, Themistoklis P; Majda, Andrew J

2013-08-20

A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.

Investigating NARCCAP Precipitation Extremes via Bivariate Extreme Value Theory (Invited)

Science.gov (United States)

Weller, G. B.; Cooley, D. S.; Sain, S. R.; Bukovsky, M. S.; Mearns, L. O.

2013-12-01

We introduce methodology from statistical extreme value theory to examine the ability of reanalysis-drive regional climate models to simulate past daily precipitation extremes. Going beyond a comparison of summary statistics such as 20-year return values, we study whether the most extreme precipitation events produced by climate model simulations exhibit correspondence to the most extreme events seen in observational records. The extent of this correspondence is formulated via the statistical concept of tail dependence. We examine several case studies of extreme precipitation events simulated by the six models of the North American Regional Climate Change Assessment Program (NARCCAP) driven by NCEP reanalysis. It is found that the NARCCAP models generally reproduce daily winter precipitation extremes along the Pacific coast quite well; in contrast, simulation of past daily summer precipitation extremes in a central US region is poor. Some differences in the strength of extremal correspondence are seen in the central region between models which employ spectral nudging and those which do not. We demonstrate how these techniques may be used to draw a link between extreme precipitation events and large-scale atmospheric drivers, as well as to downscale extreme precipitation simulated by a future run of a regional climate model. Specifically, we examine potential future changes in the nature of extreme precipitation along the Pacific coast produced by the pineapple express (PE) phenomenon. A link between extreme precipitation events and a "PE Index" derived from North Pacific sea-surface pressure fields is found. This link is used to study PE-influenced extreme precipitation produced by a future-scenario climate model run.

To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

Science.gov (United States)

Schaarup-Jensen, K; Rasmussen, M R; Thorndahl, S

2009-01-01

In urban drainage modelling long-term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties with regards to long-term prediction of maximum water levels and combined sewer overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO volumes. Traditionally, long-term rainfall series, from a local rain gauge, are unavailable. In the present case study, however, long and local rain series are available. 2 rainfall gauges have recorded events for approximately 9 years at 2 locations within the catchment. Beside these 2 gauges another 7 gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity can be handled, e.g. by introducing an "averaging procedure" based on the variability within the set of statistics. All simulations are performed by means of the MOUSE LTS model.

On Asymptotically Lacunary Statistical Equivalent Sequences of Order α in Probability

Directory of Open Access Journals (Sweden)

Işık Mahmut

2017-01-01

Full Text Available In this study, we introduce and examine the concepts of asymptotically lacunary statistical equivalent of order α in probability and strong asymptotically lacunary equivalent of order α in probability. We give some relations connected to these concepts.

Multivariate Regression Analysis and Statistical Modeling for Summer Extreme Precipitation over the Yangtze River Basin, China

Directory of Open Access Journals (Sweden)

Tao Gao

2014-01-01

Full Text Available Extreme precipitation is likely to be one of the most severe meteorological disasters in China; however, studies on the physical factors affecting precipitation extremes and corresponding prediction models are not accurately available. From a new point of view, the sensible heat flux (SHF and latent heat flux (LHF, which have significant impacts on summer extreme rainfall in Yangtze River basin (YRB, have been quantified and then selections of the impact factors are conducted. Firstly, a regional extreme precipitation index was applied to determine Regions of Significant Correlation (RSC by analyzing spatial distribution of correlation coefficients between this index and SHF, LHF, and sea surface temperature (SST on global ocean scale; then the time series of SHF, LHF, and SST in RSCs during 1967–2010 were selected. Furthermore, other factors that significantly affect variations in precipitation extremes over YRB were also selected. The methods of multiple stepwise regression and leave-one-out cross-validation (LOOCV were utilized to analyze and test influencing factors and statistical prediction model. The correlation coefficient between observed regional extreme index and model simulation result is 0.85, with significant level at 99%. This suggested that the forecast skill was acceptable although many aspects of the prediction model should be improved.

Models and Inference for Multivariate Spatial Extremes

KAUST Repository

Vettori, Sabrina

2017-12-07

The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing to the developing research field of Extreme-Value Theory. We initially study the performance of existing parametric and non-parametric estimators of extremal dependence for multivariate maxima. As the dimensionality increases, non-parametric estimators are more flexible than parametric methods but present some loss in efficiency that we quantify under various scenarios. We introduce a statistical tool which imposes the required shape constraints on non-parametric estimators in high dimensions, significantly improving their performance. Furthermore, by embedding the tree-based max-stable nested logistic distribution in the Bayesian framework, we develop a statistical algorithm that identifies the most likely tree structures representing the data\\'s extremal dependence using the reversible jump Monte Carlo Markov Chain method. A mixture of these trees is then used for uncertainty assessment in prediction through Bayesian model averaging. The computational complexity of full likelihood inference is significantly decreased by deriving a recursive formula for the nested logistic model likelihood. The algorithm performance is verified through simulation experiments which also compare different likelihood procedures. Finally, we extend the nested logistic representation to the spatial framework in order to jointly model multivariate variables collected across a spatial region. This situation emerges often in environmental applications but is not often considered in the current literature. Simulation experiments show that the new class of multivariate max-stable processes is able to detect both the cross and inner spatial dependence of a number of extreme variables at a relatively low computational cost, thanks to its Bayesian hierarchical

Statistical assessment of changes in extreme maximum temperatures over Saudi Arabia, 1985-2014

Science.gov (United States)

Raggad, Bechir

2018-05-01

In this study, two statistical approaches were adopted in the analysis of observed maximum temperature data collected from fifteen stations over Saudi Arabia during the period 1985-2014. In the first step, the behavior of extreme temperatures was analyzed and their changes were quantified with respect to the Expert Team on Climate Change Detection Monitoring indices. The results showed a general warming trend over most stations, in maximum temperature-related indices, during the period of analysis. In the second step, stationary and non-stationary extreme-value analyses were conducted for the temperature data. The results revealed that the non-stationary model with increasing linear trend in its location parameter outperforms the other models for two-thirds of the stations. Additionally, the 10-, 50-, and 100-year return levels were found to change with time considerably and that the maximum temperature could start to reappear in the different T-year return period for most stations. This analysis shows the importance of taking account the change over time in the estimation of return levels and therefore justifies the use of the non-stationary generalized extreme value distribution model to describe most of the data. Furthermore, these last findings are in line with the result of significant warming trends found in climate indices analyses.

Higher order capacity statistics of multi-hop transmission systems over Rayleigh fading channels

KAUST Repository

Yilmaz, Ferkan

2012-03-01

In this paper, we present an exact analytical expression to evaluate the higher order statistics of the channel capacity for amplify and forward (AF) multihop transmission systems operating over Rayleigh fading channels. Furthermore, we present simple and efficient closed-form expression to the higher order moments of the channel capacity of dual hop transmission system with Rayleigh fading channels. In order to analyze the behavior of the higher order capacity statistics and investigate the usefulness of the mathematical analysis, some selected numerical and simulation results are presented. Our results are found to be in perfect agreement. © 2012 IEEE.

Modified Inverse First Order Reliability Method (I-FORM) for Predicting Extreme Sea States.

Energy Technology Data Exchange (ETDEWEB)

Eckert-Gallup, Aubrey Celia; Sallaberry, Cedric Jean-Marie; Dallman, Ann Renee; Neary, Vincent Sinclair

2014-09-01

Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulation s as a part of the stand ard current practice for designing marine structure s to survive extreme sea states. Such environmental contours are characterized by combinations of significant wave height ( ) and energy period ( ) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first - order reliability method (IFORM) i s standard design practice for generating environmental contours. In this paper, the traditional appli cation of the IFORM to generating environmental contours representing extreme sea states is described in detail and its merits and drawbacks are assessed. The application of additional methods for analyzing sea state data including the use of principal component analysis (PCA) to create an uncorrelated representation of the data under consideration is proposed. A reexamination of the components of the IFORM application to the problem at hand including the use of new distribution fitting techniques are shown to contribute to the development of more accurate a nd reasonable representations of extreme sea states for use in survivability analysis for marine struc tures. Keywords: In verse FORM, Principal Component Analysis , Environmental Contours, Extreme Sea State Characteri zation, Wave Energy Converters

Extreme learning machine for reduced order modeling of turbulent geophysical flows

Science.gov (United States)

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

STATISTICAL MODELLING OF FDC AND RETURN PERIODS TO CHARACTERISE QDF AND DESIGN THRESHOLD OF HYDROLOGICAL EXTREMES

Directory of Open Access Journals (Sweden)

Charles Onyutha

2012-12-01

Full Text Available In this paper, firstly, flow duration curves (FDCs for hydrological extremes were calibrated for a range of aggregation levels and seasons to provide compressed statistical information for water resources management at selected temporal scales and seasons. Secondly, instead of the common approach of using return periods, T (years for deriving discharge duration frequency (QDF relationships, the method of using exceedance frequencies, E (% was introduced so as to provide answer to important question like, what is the streamflow at a given aggregation level and selected E (%?. Thirdly, the concept of estimated design threshold (EDT was introduced and proposed for consideration in the risk analysis for design of water resources structures. This study was based on the long daily discharge record for the period 1950 – 2008 at station 1EF01 in Kenya, on the Nzoia river with watershed area of 12,676 km2 located in the North Eastern quadrant of Lake Victoria Nile Sub Basin. In the statistical modeling of FDCs and T (years, suitable extreme value distributions (EVD were selected and calibrated to fit nearly independent high flows and low flows. The FDCs and T-curves were used to determine the EDT. The FDCs were used to model the QDF relationships. To derive QDF relationships of hydrological extremes, for a given range of aggregation levels, extreme value analysis (EVA was carried out and suitable EVD selected. Next was the calibration of parameters of the EVD and analysis of relationship between the model parameters and aggregation levels. Finally, smooth mathematical relationships were derived using little but acceptable modifications to the model parameters. Such constructed QDF relationships can be used for various applications to estimate cumulative volumes of water available during droughts or floods at various aggregation levels or E (% of hydrological extremes. The EDT when obtained for a range of aggregation levels can also be used to

STATISTICAL MODELLING OF FDC AND RETURN PERIODS TO CHARACTERISE QDF AND DESIGN THRESHOLD OF HYDROLOGICAL EXTREMES

Directory of Open Access Journals (Sweden)

Charles Onyutha

2012-01-01

Full Text Available In this paper, firstly, flow duration curves (FDCs for hydrological extremes were calibrated for a range of aggregation levels and seasons to provide compressed statistical information for water resources management at selected temporal scales and seasons. Secondly, instead of the common approach of using return periods, T (years for deriving discharge duration frequency (QDF relationships, the method of using exceedance frequencies, E (% was introduced so as to provide answer to important question like, what is the streamflow at a given aggregation level and selected E (%? Thirdly, the concept of estimated design threshold (EDT was introduced and proposed for consideration in the risk analysis for design of water resources structures. This study was based on the long daily discharge record for the period 1950 - 2008 at station 1EF01 in Kenya, on the Nzoia river with watershed area of 12,676 km² located in the North Eastern quadrant of Lake Victoria Nile Sub Basin. In the statistical modelling of FDCs and T (years, suitable extreme value distributions (EVD were selected and calibrated to fit nearly independent high flows and low flows. The FDCs and T-curves were used to determine the EDT. The FDCs were used to model the QDF relationships. To derive QDF relationships of hydrological extremes, for a given range of aggregation levels, extreme value analysis (EVA was carried out and suitable EVD selected. Next was the calibration of parameters of the EVD and analysis of relationship between the model parameters and aggregation levels. Finally, smooth mathematical relationships were derived using little but acceptable modifications to the model parameters. Such constructed QDF relationships can be used for various applications to estimate cumulative volumes of water available during droughts or floods at various aggregation levels or E (% of hydrological extremes. The EDT when obtained for a range of aggregation levels can also be used to understand

Higher-order scene statistics of breast images

Science.gov (United States)

Abbey, Craig K.; Sohl-Dickstein, Jascha N.; Olshausen, Bruno A.; Eckstein, Miguel P.; Boone, John M.

2009-02-01

Researchers studying human and computer vision have found description and construction of these systems greatly aided by analysis of the statistical properties of naturally occurring scenes. More specifically, it has been found that receptive fields with directional selectivity and bandwidth properties similar to mammalian visual systems are more closely matched to the statistics of natural scenes. It is argued that this allows for sparse representation of the independent components of natural images [Olshausen and Field, Nature, 1996]. These theories have important implications for medical image perception. For example, will a system that is designed to represent the independent components of natural scenes, where objects occlude one another and illumination is typically reflected, be appropriate for X-ray imaging, where features superimpose on one another and illumination is transmissive? In this research we begin to examine these issues by evaluating higher-order statistical properties of breast images from X-ray projection mammography (PM) and dedicated breast computed tomography (bCT). We evaluate kurtosis in responses of octave bandwidth Gabor filters applied to PM and to coronal slices of bCT scans. We find that kurtosis in PM rises and quickly saturates for filter center frequencies with an average value above 0.95. By contrast, kurtosis in bCT peaks near 0.20 cyc/mm with kurtosis of approximately 2. Our findings suggest that the human visual system may be tuned to represent breast tissue more effectively in bCT over a specific range of spatial frequencies.

Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

Science.gov (United States)

Santos, Monica; Fragoso, Marcelo

2010-05-01

Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude

Statistical Downscaling of Gusts During Extreme European Winter Storms Using Radial-Basis-Function Networks

Science.gov (United States)

Voigt, M.; Lorenz, P.; Kruschke, T.; Osinski, R.; Ulbrich, U.; Leckebusch, G. C.

2012-04-01

Winterstorms and related gusts can cause extensive socio-economic damages. Knowledge about the occurrence and the small scale structure of such events may help to make regional estimations of storm losses. For a high spatial and temporal representation, the use of dynamical downscaling methods (RCM) is a cost-intensive and time-consuming option and therefore only applicable for a limited number of events. The current study explores a methodology to provide a statistical downscaling, which offers small scale structured gust fields from an extended large scale structured eventset. Radial-basis-function (RBF) networks in combination with bidirectional Kohonen (BDK) maps are used to generate the gustfields on a spatial resolution of 7 km from the 6-hourly mean sea level pressure field from ECMWF reanalysis data. BDK maps are a kind of neural network which handles supervised classification problems. In this study they are used to provide prototypes for the RBF network and give a first order approximation for the output data. A further interpolation is done by the RBF network. For the training process the 50 most extreme storm events over the North Atlantic area from 1957 to 2011 are used, which have been selected from ECMWF reanalysis datasets ERA40 and ERA-Interim by an objective wind based tracking algorithm. These events were downscaled dynamically by application of the DWD model chain GME → COSMO-EU. Different model parameters and their influence on the quality of the generated high-resolution gustfields are studied. It is shown that the statistical RBF network approach delivers reasonable results in modeling the regional gust fields for untrained events.

Statistical prediction of parametric roll using FORM

DEFF Research Database (Denmark)

Jensen, Jørgen Juncher; Choi, Ju-hyuck; Nielsen, Ulrik Dam

2017-01-01

Previous research has shown that the First Order Reliability Method (FORM) can be an efficient method for estimation of outcrossing rates and extreme value statistics for stationary stochastic processes. This is so also for bifurcation type of processes like parametric roll of ships. The present...

Generalized statistical convergence of order β for sequences of fuzzy numbers

Science.gov (United States)

Altınok, Hıfsı; Karakaş, Abdulkadir; Altın, Yavuz

2018-01-01

In the present paper, we introduce the concepts of Δm-statistical convergence of order β for sequences of fuzzy numbers and strongly Δm-summable of order β for sequences of fuzzy numbers by using a modulus function f and taking supremum on metric d for 0 < β ≤ 1 and give some inclusion relations between them.

High order statistical signatures from source-driven measurements of subcritical fissile systems

International Nuclear Information System (INIS)

Mattingly, J.K.

1998-01-01

This research focuses on the development and application of high order statistical analyses applied to measurements performed with subcritical fissile systems driven by an introduced neutron source. The signatures presented are derived from counting statistics of the introduced source and radiation detectors that observe the response of the fissile system. It is demonstrated that successively higher order counting statistics possess progressively higher sensitivity to reactivity. Consequently, these signatures are more sensitive to changes in the composition, fissile mass, and configuration of the fissile assembly. Furthermore, it is shown that these techniques are capable of distinguishing the response of the fissile system to the introduced source from its response to any internal or inherent sources. This ability combined with the enhanced sensitivity of higher order signatures indicates that these techniques will be of significant utility in a variety of applications. Potential applications include enhanced radiation signature identification of weapons components for nuclear disarmament and safeguards applications and augmented nondestructive analysis of spent nuclear fuel. In general, these techniques expand present capabilities in the analysis of subcritical measurements

Entanglement and local extremes at an infinite-order quantum phase transition

International Nuclear Information System (INIS)

Rulli, C. C.; Sarandy, M. S.

2010-01-01

The characterization of an infinite-order quantum phase transition (QPT) by entanglement measures is analyzed. To this aim, we consider two closely related solvable spin-1/2 chains, namely, the Ashkin-Teller and the staggered XXZ models. These systems display a distinct pattern of eigenstates but exhibit the same thermodynamics, that is, the same energy spectrum. By performing exact diagonalization, we investigate the behavior of pairwise and block entanglement in the ground state of both models. In contrast with the XXZ chain, we show that pairwise entanglement fails in the characterization of the infinite-order QPT in the Ashkin-Teller model, although it can be achieved by analyzing the distance of the pair state from the separability boundary. Concerning block entanglement, we show that both XXZ and Ashkin-Teller models exhibit identical von Neumann entropies as long as a suitable choice of blocks is performed. Entanglement entropy is then shown to be able to identify the quantum phase diagram, even though its local extremes (either maximum or minimum) may also appear in the absence of any infinite-order QPT.

High-order harmonics measured by the photon statistics of the infrared driving-field exiting the atomic medium.

Science.gov (United States)

Tsatrafyllis, N; Kominis, I K; Gonoskov, I A; Tzallas, P

2017-04-27

High-order harmonics in the extreme-ultraviolet spectral range, resulting from the strong-field laser-atom interaction, have been used in a broad range of fascinating applications in all states of matter. In the majority of these studies the harmonic generation process is described using semi-classical theories which treat the electromagnetic field of the driving laser pulse classically without taking into account its quantum nature. In addition, for the measurement of the generated harmonics, all the experiments require diagnostics in the extreme-ultraviolet spectral region. Here by treating the driving laser field quantum mechanically we reveal the quantum-optical nature of the high-order harmonic generation process by measuring the photon number distribution of the infrared light exiting the harmonic generation medium. It is found that the high-order harmonics are imprinted in the photon number distribution of the infrared light and can be recorded without the need of a spectrometer in the extreme-ultraviolet.

The use of Monte-Carlo simulation and order statistics for uncertainty analysis of a LBLOCA transient (LOFT-L2-5)

International Nuclear Information System (INIS)

Chojnacki, E.; Benoit, J.P.

2007-01-01

Best estimate computer codes are increasingly used in nuclear industry for the accident management procedures and have been planned to be used for the licensing procedures. Contrary to conservative codes which are supposed to give penalizing results, best estimate codes attempt to calculate accidental transients in a realistic way. It becomes therefore of prime importance, in particular for technical organization as IRSN in charge of safety assessment, to know the uncertainty on the results of such codes. Thus, CSNI has sponsored few years ago (published in 1998) the Uncertainty Methods Study (UMS) program on uncertainty methodologies used for a SBLOCA transient (LSTF-CL-18) and is now supporting the BEMUSE program for a LBLOCA transient (LOFT-L2-5). The large majority of BEMUSE participants (9 out of 10) use uncertainty methodologies based on a probabilistic modelling and all of them use Monte-Carlo simulations to propagate the uncertainties through their computer codes. Also, all of 'probabilistic participants' intend to use order statistics to determine the sampling size of the Monte-Carlo simulation and to derive the uncertainty ranges associated to their computer calculations. The first aim of this paper is to remind the advantages and also the assumptions of the probabilistic modelling and more specifically of order statistics (as Wilks' formula) in uncertainty methodologies. Indeed Monte-Carlo methods provide flexible and extremely powerful techniques for solving many of the uncertainty propagation problems encountered in nuclear safety analysis. However it is important to keep in mind that probabilistic methods are data intensive. That means, probabilistic methods cannot produce robust results unless a considerable body of information has been collected. A main interest of the use of order statistics results is to allow to take into account an unlimited number of uncertain parameters and, from a restricted number of code calculations to provide statistical

Further outlooks: extremely uncomfortable; Die weiteren Aussichten: extrem ungemuetlich

Energy Technology Data Exchange (ETDEWEB)

Resenhoeft, T.

2006-07-01

Climate is changing extremely in the last decades. Scientists dealing with extreme weather, should not only stare at computer simulations. They have also to turn towards psyche, seriously personal experiences, knowing statistics, relativise supposed sensational reports and last not least collecting more data. (GL)

Novel asymptotic results on the high-order statistics of the channel capacity over generalized fading channels

KAUST Repository

Yilmaz, Ferkan

2012-06-01

The exact analysis of the higher-order statistics of the channel capacity (i.e., higher-order ergodic capacity) often leads to complicated expressions involving advanced special functions. In this paper, we provide a generic framework for the computation of the higher-order statistics of the channel capacity over generalized fading channels. As such, this novel framework for the higher-order statistics results in simple, closed-form expressions which are shown to be asymptotically tight bounds in the high signal-to-noise ratio (SNR) regime of a variety of fading environment. In addition, it reveals the existence of differences (i.e., constant capacity gaps in log-domain) among different fading environments. By asymptotically tight bound we mean that the high SNR limit of the difference between the actual higher-order statistics of the channel capacity and its asymptotic bound (i.e., lower bound) tends to zero. The mathematical formalism is illustrated with some selected numerical examples that validate the correctness of our newly derived results. © 2012 IEEE.

Low-frequency variability of the atmospheric circulation: a comparison of statistical properties in both hemispheres and extreme seasons

International Nuclear Information System (INIS)

Buzzi, A.; Tosi, E.

1988-01-01

A statistical investigation is presented of the main variables characterizing the tropospheric general circulation in both hemispheres and extreme season, Winter and Summer. This gives up the opportunity of comparing four distinct realizations of the planetary circulation, as function of different orographic and thermal forcing conditions. Our approach is made possible by the availability of 6 years of global daily analyses prepared by ECMWF (European Centre for Medium-range Weather Forecast). The variables taken into account are the zonal geostrophic wind, the zonal thermal wind and various large-scala wave components, averaged over the tropospheric depth between 1000 and 200 hPa. The mean properties of the analysed quantities in each hemisphere and season are compared and their principal characteristics are discussed. The probability density estimates for the same variables, filtered in order to eliminate the seasonal cycle and the high frequency 'noise', are then presented. The distributions are examined, in particular, with respect of their unimodal or multimodal nature and with reference to the recent discussion in the literature on the bimodality which has been found for some indicators of planetary wave activity in the Nothern Hemisphere Winter. Our results indicate the presence of nonunimodally distributed wave and zonal flow components in both hemispheres and extreme season. The most frequent occurrence of nonunimodal behaviour is found for those wave components which exhibit an almost vanishing zonal phase speed and a larger 'response' to orographic forcing

Extreme eigenvalues of sample covariance and correlation matrices

DEFF Research Database (Denmark)

Heiny, Johannes

This thesis is concerned with asymptotic properties of the eigenvalues of high-dimensional sample covariance and correlation matrices under an infinite fourth moment of the entries. In the first part, we study the joint distributional convergence of the largest eigenvalues of the sample covariance...... matrix of a p-dimensional heavy-tailed time series when p converges to infinity together with the sample size n. We generalize the growth rates of p existing in the literature. Assuming a regular variation condition with tail index ... eigenvalues are essentially determined by the extreme order statistics from an array of iid random variables. The asymptotic behavior of the extreme eigenvalues is then derived routinely from classical extreme value theory. The resulting approximations are strikingly simple considering the high dimension...

Handbook of tables for order statistics from lognormal distributions with applications

CERN Document Server

Balakrishnan, N

1999-01-01

Lognormal distributions are one of the most commonly studied models in the sta­ tistical literature while being most frequently used in the applied literature. The lognormal distributions have been used in problems arising from such diverse fields as hydrology, biology, communication engineering, environmental science, reliability, agriculture, medical science, mechanical engineering, material science, and pharma­ cology. Though the lognormal distributions have been around from the beginning of this century (see Chapter 1), much of the work concerning inferential methods for the parameters of lognormal distributions has been done in the recent past. Most of these methods of inference, particUlarly those based on censored samples, involve extensive use of numerical methods to solve some nonlinear equations. Order statistics and their moments have been discussed quite extensively in the literature for many distributions. It is very well known that the moments of order statistics can be derived explicitly only...

Studies in the statistical and thermal properties of hadronic matter under some extreme conditions

International Nuclear Information System (INIS)

Chase, K.C.; Mekjian, A.Z.; Bhattacharyya, P.

1997-01-01

The thermal and statistical properties of hadronic matter under some extreme conditions are investigated using an exactly solvable canonical ensemble model. A unified model describing both the fragmentation of nuclei and the thermal properties of hadronic matter is developed. Simple expressions are obtained for quantities such as the hadronic equation of state, specific heat, compressibility, entropy, and excitation energy as a function of temperature and density. These expressions encompass the fermionic aspect of nucleons, such as degeneracy pressure and Fermi energy at low temperatures and the ideal gas laws at high temperatures and low density. Expressions are developed which connect these two extremes with behavior that resembles an ideal Bose gas with its associated Bose condensation. In the thermodynamic limit, an infinite cluster exists below a certain critical condition in a manner similar to the sudden appearance of the infinite cluster in percolation theory. The importance of multiplicity fluctuations is discussed and some recent data from the EOS collaboration on critical point behavior of nuclei can be accounted for using simple expressions obtained from the model. copyright 1997 The American Physical Society

Efficient nonrigid registration using ranked order statistics

DEFF Research Database (Denmark)

Tennakoon, Ruwan B.; Bab-Hadiashar, Alireza; de Bruijne, Marleen

2013-01-01

of research. In this paper we propose a fast and accurate non-rigid registration method for intra-modality volumetric images. Our approach exploits the information provided by an order statistics based segmentation method, to find the important regions for registration and use an appropriate sampling scheme......Non-rigid image registration techniques are widely used in medical imaging applications. Due to high computational complexities of these techniques, finding appropriate registration method to both reduce the computation burden and increase the registration accuracy has become an intense area...... to target those areas and reduce the registration computation time. A unique advantage of the proposed method is its ability to identify the point of diminishing returns and stop the registration process. Our experiments on registration of real lung CT images, with expert annotated landmarks, show...

Connection between weighted LPC and higher-order statistics for AR model estimation

NARCIS (Netherlands)

Kamp, Y.; Ma, C.

1993-01-01

This paper establishes the relationship between a weighted linear prediction method used for robust analysis of voiced speech and the autoregressive modelling based on higher-order statistics, known as cumulants

Impacts of climate change on precipitation and discharge extremes through the use of statistical downscaling approaches in a Mediterranean basin.

Science.gov (United States)

Piras, Monica; Mascaro, Giuseppe; Deidda, Roberto; Vivoni, Enrique R

2016-02-01

Mediterranean region is characterized by high precipitation variability often enhanced by orography, with strong seasonality and large inter-annual fluctuations, and by high heterogeneity of terrain and land surface properties. As a consequence, catchments in this area are often prone to the occurrence of hydrometeorological extremes, including storms, floods and flash-floods. A number of climate studies focused in the Mediterranean region predict that extreme events will occur with higher intensity and frequency, thus requiring further analyses to assess their effect at the land surface, particularly in small- and medium-sized watersheds. In this study, climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) EU FP7 research project were used to analyze how precipitation extremes propagate into discharge extremes in the Rio Mannu basin (472.5km(2)), located in Sardinia, Italy. The basin hydrologic response to climate forcings in a reference (1971-2000) and a future (2041-2070) period was simulated through the combined use of a set of global and regional climate models, statistical downscaling techniques, and a process based distributed hydrologic model. We analyzed and compared the distribution of annual maxima extracted from hourly and daily precipitation and peak discharge time series, simulated by the hydrologic model under climate forcing. For this aim, yearly maxima were fit by the Generalized Extreme Value (GEV) distribution using a regional approach. Next, we discussed commonality and contrasting behaviors of precipitation and discharge maxima distributions to better understand how hydrological transformations impact propagation of extremes. Finally, we show how rainfall statistical downscaling algorithms produce more reliable forcings for hydrological models than coarse climate model outputs. Copyright © 2015 Elsevier B.V. All rights reserved.

Statistical Modelling of Extreme Rainfall in Taiwan

NARCIS (Netherlands)

L-F. Chu (Lan-Fen); M.J. McAleer (Michael); C-C. Chang (Ching-Chung)

2012-01-01

textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.

Statistical Modelling of Extreme Rainfall in Taiwan

NARCIS (Netherlands)

L. Chu (LanFen); M.J. McAleer (Michael); C-H. Chang (Chu-Hsiang)

2013-01-01

textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.

An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables

KAUST Repository

Nam, Sungsik

2010-11-01

Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs). With the proposed approach, we can systematically derive the joint statistics of any partial sums of ordered statistics, in terms of the moment generating function (MGF) and the probability density function (PDF). Our MGF-based approach applies not only when all the K ordered RVs are involved but also when only the Ks(Ks < K) best RVs are considered. In addition, we present the closed-form expressions for the exponential RV special case. These results apply to the performance analysis of various wireless communication systems over fading channels. © 2006 IEEE.

Order-Specific Fertility Rates for Germany
Estimates from Perinatal Statistics for the Period 2001-2008

OpenAIRE

Michaela Kreyenfeld; Rembrandt Scholz; Frederik Peters; Ines Wlosnewski

2011-01-01

Until 2008, Germany’s vital statistics did not include information on the biological order of each birth. This resulted in a dearth of important demographic indicators, such as the mean age at first birth and the level of childlessness. Researchers have tried to fill this gap by generating order-specific birth rates from survey data, and by combining survey data with vital statistics. This paper takes a different approach by using Perinatal Statistics to generate birth order-specific fertilit...

Changing world extreme temperature statistics

Science.gov (United States)

Finkel, J. M.; Katz, J. I.

2018-04-01

We use the Global Historical Climatology Network--daily database to calculate a nonparametric statistic that describes the rate at which all-time daily high and low temperature records have been set in nine geographic regions (continents or major portions of continents) during periods mostly from the mid-20th Century to the present. This statistic was defined in our earlier work on temperature records in the 48 contiguous United States. In contrast to this earlier work, we find that in every region except North America all-time high records were set at a rate significantly (at least $3\\sigma$) higher than in the null hypothesis of a stationary climate. Except in Antarctica, all-time low records were set at a rate significantly lower than in the null hypothesis. In Europe, North Africa and North Asia the rate of setting new all-time highs increased suddenly in the 1990's, suggesting a change in regional climate regime; in most other regions there was a steadier increase.

Effect of higher order nonlinearity, directionality and finite water depth on wave statistics: Comparison of field data and numerical simulations

Science.gov (United States)

Fernández, Leandro; Monbaliu, Jaak; Onorato, Miguel; Toffoli, Alessandro

2014-05-01

This research is focused on the study of nonlinear evolution of irregular wave fields in water of arbitrary depth by comparing field measurements and numerical simulations.It is now well accepted that modulational instability, known as one of the main mechanisms for the formation of rogue waves, induces strong departures from Gaussian statistics. However, whereas non-Gaussian properties are remarkable when wave fields follow one direction of propagation over an infinite water depth, wave statistics only weakly deviate from Gaussianity when waves spread over a range of different directions. Over finite water depth, furthermore, wave instability attenuates overall and eventually vanishes for relative water depths as low as kh=1.36 (where k is the wavenumber of the dominant waves and h the water depth). Recent experimental results, nonetheless, seem to indicate that oblique perturbations are capable of triggering and sustaining modulational instability even if khthe aim of this research is to understand whether the combined effect of directionality and finite water depth has a significant effect on wave statistics and particularly on the occurrence of extremes. For this purpose, numerical experiments have been performed solving the Euler equation of motion with the Higher Order Spectral Method (HOSM) and compared with data of short crested wave fields for different sea states observed at the Lake George (Australia). A comparative analysis of the statistical properties (i.e. density function of the surface elevation and its statistical moments skewness and kurtosis) between simulations and in-situ data provides a confrontation between the numerical developments and real observations in field conditions.

An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables

KAUST Repository

Nam, Sungsik; Alouini, Mohamed-Slim; Yang, Hongchuan

2010-01-01

Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs

Analyzing phenological extreme events over the past five decades in Germany

Science.gov (United States)

Schleip, Christoph; Menzel, Annette; Estrella, Nicole; Graeser, Philipp

2010-05-01

As climate change may alter the frequency and intensity of extreme temperatures, we analysed whether warming of the last 5 decades has already changed the statistics of phenological extreme events. In this context, two extreme value statistical concepts are discussed and applied to existing phenological datasets of German Weather Service (DWD) in order to derive probabilities of occurrence for extreme early or late phenological events. We analyse four phenological groups; "begin of flowering, "leaf foliation", "fruit ripening" and "leaf colouring" as well as DWD indicator phases of the "phenological year". Additionally we put an emphasis on a between-species analysis; a comparison of differences in extreme onsets between three common northern conifers. Furthermore we conducted a within-species analysis with different phases of horse chestnut throughout a year. The first statistical approach fits data to a Gaussian model using traditional statistical techniques, and then analyses the extreme quantile. The key point of this approach is the adoption of an appropriate probability density function (PDF) to the observed data and the assessment of the PDF parameters change in time. The full analytical description in terms of the estimated PDF for defined time steps of the observation period allows probability assessments of extreme values for e.g. annual or decadal time steps. Related with this approach is the possibility of counting out the onsets which fall in our defined extreme percentiles. The estimation of the probability of extreme events on the basis of the whole data set is in contrast to analyses with the generalized extreme value distribution (GEV). The second approach deals with the extreme PDFs itself and fits the GEV distribution to annual minima of phenological series to provide useful estimates about return levels. For flowering and leaf unfolding phases exceptionally early extremes are seen since the mid 1980s and especially for the single years 1961

Perspectives on the application of order-statistics in best-estimate plus uncertainty nuclear safety analysis

International Nuclear Information System (INIS)

Martin, Robert P.; Nutt, William T.

2011-01-01

Research highlights: → Historical recitation on application of order-statistics models to nuclear power plant thermal-hydraulics safety analysis. → Interpretation of regulatory language regarding 10 CFR 50.46 reference to a 'high level of probability'. → Derivation and explanation of order-statistics-based evaluation methodologies considering multi-variate acceptance criteria. → Summary of order-statistics models and recommendations to the nuclear power plant thermal-hydraulics safety analysis community. - Abstract: The application of order-statistics in best-estimate plus uncertainty nuclear safety analysis has received a considerable amount of attention from methodology practitioners, regulators, and academia. At the root of the debate are two questions: (1) what is an appropriate quantitative interpretation of 'high level of probability' in regulatory language appearing in the LOCA rule, 10 CFR 50.46 and (2) how best to mathematically characterize the multi-variate case. An original derivation is offered to provide a quantitative basis for 'high level of probability.' At root of the second question is whether one should recognize a probability statement based on the tolerance region method of Wald and Guba, et al., for multi-variate problems, one explicitly based on the regulatory limits, best articulated in the Wallis-Nutt 'Testing Method', or something else entirely. This paper reviews the origins of the different positions, key assumptions, limitations, and relationship to addressing acceptance criteria. It presents a mathematical interpretation of the regulatory language, including a complete derivation of uni-variate order-statistics (as credited in AREVA's Realistic Large Break LOCA methodology) and extension to multi-variate situations. Lastly, it provides recommendations for LOCA applications, endorsing the 'Testing Method' and addressing acceptance methods allowing for limited sample failures.

Adaptive statistical iterative reconstruction use for radiation dose reduction in pediatric lower-extremity CT: impact on diagnostic image quality.

Science.gov (United States)

Shah, Amisha; Rees, Mitchell; Kar, Erica; Bolton, Kimberly; Lee, Vincent; Panigrahy, Ashok

2018-06-01

For the past several years, increased levels of imaging radiation and cumulative radiation to children has been a significant concern. Although several measures have been taken to reduce radiation dose during computed tomography (CT) scan, the newer dose reduction software adaptive statistical iterative reconstruction (ASIR) has been an effective technique in reducing radiation dose. To our knowledge, no studies are published that assess the effect of ASIR on extremity CT scans in children. To compare radiation dose, image noise, and subjective image quality in pediatric lower extremity CT scans acquired with and without ASIR. The study group consisted of 53 patients imaged on a CT scanner equipped with ASIR software. The control group consisted of 37 patients whose CT images were acquired without ASIR. Image noise, Computed Tomography Dose Index (CTDI) and dose length product (DLP) were measured. Two pediatric radiologists rated the studies in subjective categories: image sharpness, noise, diagnostic acceptability, and artifacts. The CTDI (p value = 0.0184) and DLP (p value ASIR compared with non-ASIR studies. However, the subjective ratings for sharpness (p ASIR images (p ASIR CT studies. Adaptive statistical iterative reconstruction reduces radiation dose for lower extremity CTs in children, but at the expense of diagnostic imaging quality. Further studies are warranted to determine the specific utility of ASIR for pediatric musculoskeletal CT imaging.

Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method

Directory of Open Access Journals (Sweden)

Huan Wang

2017-10-01

Full Text Available Fractional order proportional-integral-derivative(FOPID controllers have attracted increasing attentions recently due to their better control performance than the traditional integer-order proportional-integral-derivative (PID controllers. However, there are only few studies concerning the fractional order control of microgrids based on evolutionary algorithms. From the perspective of multi-objective optimization, this paper presents an effective FOPID based frequency controller design method called MOEO-FOPID for an islanded microgrid by using a Multi-objective extremal optimization (MOEO algorithm to minimize frequency deviation and controller output signal simultaneously in order to improve finally the efficient operation of distributed generations and energy storage devices. Its superiority to nondominated sorting genetic algorithm-II (NSGA-II based FOPID/PID controllers and other recently reported single-objective evolutionary algorithms such as Kriging-based surrogate modeling and real-coded population extremal optimization-based FOPID controllers is demonstrated by the simulation studies on a typical islanded microgrid in terms of the control performance including frequency deviation, deficit grid power, controller output signal and robustness.

Introducing Switching Ordered Statistic CFAR Type I in Different Radar Environments

Directory of Open Access Journals (Sweden)

Saeed Erfanian

2009-01-01

Full Text Available In this paper, a new CFAR detector based on a switching algorithm and OS-CFAR for nonhomogeneous background environments is introduced. The new detector is named Switching Ordered Statistic CFAR type I (SOS CFAR I. The SOS CFAR I selects a set of suitable cells and then with the help of the ordering method, estimates the unknown background noise level. The proposed detector does not require any prior information about the background environment and uses cells with similar statistical specifications to estimate the background noise. The performance of SOS CFAR I is evaluated and compared with other detectors such as CA-CFAR, GO-CFAR, SO-CFAR, and OS-CFAR for the Swerling I target model in homogeneous and nonhomogeneous noise environments such as those with multiple interference and clutter edges. The results show that SOS CFAR I detectors considerably reduce the problem of excessive false alarm probability near clutter edges while maintaining good performance in other environments. Also, simulation results confirm the achievement of an optimum detection threshold in homogenous and nonhomogeneous radar environments by the mentioned processor.

Uncertainties Related to Extreme Event Statistics of Sewer System Surcharge and Overflow

DEFF Research Database (Denmark)

Schaarup-Jensen, Kjeld; Johansen, C.; Thorndahl, Søren Liedtke

2005-01-01

Today it is common practice - in the major part of Europe - to base design of sewer systems in urban areas on recommended minimum values of flooding frequencies related to either pipe top level, basement level in buildings or level of road surfaces. Thus storm water runoff in sewer systems is only...... proceeding in an acceptable manner, if flooding of these levels is having an average return period bigger than a predefined value. This practice is also often used in functional analysis of existing sewer systems. If a sewer system can fulfil recommended flooding frequencies or not, can only be verified...... by performing long term simulations - using a sewer flow simulation model - and draw up extreme event statistics from the model simulations. In this context it is important to realize that uncertainties related to the input parameters of rainfall runoff models will give rise to uncertainties related...

Spreadsheets as tools for statistical computing and statistics education

OpenAIRE

Neuwirth, Erich

2000-01-01

Spreadsheets are an ubiquitous program category, and we will discuss their use in statistics and statistics education on various levels, ranging from very basic examples to extremely powerful methods. Since the spreadsheet paradigm is very familiar to many potential users, using it as the interface to statistical methods can make statistics more easily accessible.

A statistical-thermodynamic model for ordering phenomena in thin film intermetallic structures

International Nuclear Information System (INIS)

Semenova, Olga; Krachler, Regina

2008-01-01

Ordering phenomena in bcc (110) binary thin film intermetallics are studied by a statistical-thermodynamic model. The system is modeled by an Ising approach that includes only nearest-neighbor chemical interactions and is solved in a mean-field approximation. Vacancies and anti-structure atoms are considered on both sublattices. The model describes long-range ordering and simultaneously short-range ordering in the thin film. It is applied to NiAl thin films with B2 structure. Vacancy concentrations, thermodynamic activity profiles and the virtual critical temperature of order-disorder as a function of film composition and thickness are presented. The results point to an important role of vacancies in near-stoichiometric and Ni-rich NiAl thin films

A Modified Jonckheere Test Statistic for Ordered Alternatives in Repeated Measures Design

Directory of Open Access Journals (Sweden)

Hatice Tül Kübra AKDUR

2016-09-01

Full Text Available In this article, a new test based on Jonckheere test [1] for  randomized blocks which have dependent observations within block is presented. A weighted sum for each block statistic rather than the unweighted sum proposed by Jonckheereis included. For Jonckheere type statistics, the main assumption is independency of observations within block. In the case of repeated measures design, the assumption of independence is violated. The weighted Jonckheere type statistic for the situation of dependence for different variance-covariance structure and the situation based on ordered alternative hypothesis structure of each block on the design is used. Also, the proposed statistic is compared to the existing test based on Jonckheere in terms of type I error rates by performing Monte Carlo simulation. For the strong correlations, circular bootstrap version of the proposed Jonckheere test provides lower rates of type I error.

The Statistical Distribution of Turbulence Driven Velocity Extremes in the Atmosperic Boundary Layer cartwright/Longuet-Higgins Revised

DEFF Research Database (Denmark)

Hansen, Kurt Schaldemose

2007-01-01

The statistical distribution of extreme wind excursions above a mean level, for a specified recurrence period, is of crucial importance in relation to design of wind sensitive structures. This is particularly true for wind turbine structures. Based on an assumption of a Gaussian "mother......" distribution, Cartwright and Longuet-Higgens [1] derived an asymptotic expression for the distribution of the largest excursion from the mean level during an arbitrary recurrence period. From its inception, this celebrated expression has been widely used in wind engineering (as well as in off-shore engineering...... associated with large excursions from the mean [2]. Thus, the more extreme turbulence excursions (i.e. the upper tail of the turbulence PDF) seem to follow an Exponential-like distribution rather than a Gaussian distribution, and a Gaussian estimate may under-predict the probability of large turbulence...

Statistical Entropy of Four-Dimensional Extremal Black Holes

International Nuclear Information System (INIS)

Maldacena, J.M.; Strominger, A.

1996-01-01

String theory is used to count microstates of four-dimensional extremal black holes in compactifications with N=4 and N=8 supersymmetry. The result agrees for large charges with the Bekenstein-Hawking entropy. copyright 1996 The American Physical Society

Higher-Order Statistical Correlations and Mutual Information Among Particles in a Quantum Well

Science.gov (United States)

Yépez, V. S.; Sagar, R. P.; Laguna, H. G.

2017-12-01

The influence of wave function symmetry on statistical correlation is studied for the case of three non-interacting spin-free quantum particles in a unidimensional box, in position and in momentum space. Higher-order statistical correlations occurring among the three particles in this quantum system is quantified via higher-order mutual information and compared to the correlation between pairs of variables in this model, and to the correlation in the two-particle system. The results for the higher-order mutual information show that there are states where the symmetric wave functions are more correlated than the antisymmetric ones with same quantum numbers. This holds in position as well as in momentum space. This behavior is opposite to that observed for the correlation between pairs of variables in this model, and the two-particle system, where the antisymmetric wave functions are in general more correlated. These results are also consistent with those observed in a system of three uncoupled oscillators. The use of higher-order mutual information as a correlation measure, is monitored and examined by considering a superposition of states or systems with two Slater determinants.

Higher-Order Statistical Correlations and Mutual Information Among Particles in a Quantum Well

International Nuclear Information System (INIS)

Yépez, V. S.; Sagar, R. P.; Laguna, H. G.

2017-01-01

The influence of wave function symmetry on statistical correlation is studied for the case of three non-interacting spin-free quantum particles in a unidimensional box, in position and in momentum space. Higher-order statistical correlations occurring among the three particles in this quantum system is quantified via higher-order mutual information and compared to the correlation between pairs of variables in this model, and to the correlation in the two-particle system. The results for the higher-order mutual information show that there are states where the symmetric wave functions are more correlated than the antisymmetric ones with same quantum numbers. This holds in position as well as in momentum space. This behavior is opposite to that observed for the correlation between pairs of variables in this model, and the two-particle system, where the antisymmetric wave functions are in general more correlated. These results are also consistent with those observed in a system of three uncoupled oscillators. The use of higher-order mutual information as a correlation measure, is monitored and examined by considering a superposition of states or systems with two Slater determinants. (author)

Higher-order statistical moments and a procedure that detects potentially anomalous years as two alternative methods describing alterations in continuous environmental data

Science.gov (United States)

Arismendi, Ivan; Johnson, Sherri L.; Dunham, Jason B.

2015-01-01

Statistics of central tendency and dispersion may not capture relevant or desired characteristics of the distribution of continuous phenomena and, thus, they may not adequately describe temporal patterns of change. Here, we present two methodological approaches that can help to identify temporal changes in environmental regimes. First, we use higher-order statistical moments (skewness and kurtosis) to examine potential changes of empirical distributions at decadal extents. Second, we adapt a statistical procedure combining a non-metric multidimensional scaling technique and higher density region plots to detect potentially anomalous years. We illustrate the use of these approaches by examining long-term stream temperature data from minimally and highly human-influenced streams. In particular, we contrast predictions about thermal regime responses to changing climates and human-related water uses. Using these methods, we effectively diagnose years with unusual thermal variability and patterns in variability through time, as well as spatial variability linked to regional and local factors that influence stream temperature. Our findings highlight the complexity of responses of thermal regimes of streams and reveal their differential vulnerability to climate warming and human-related water uses. The two approaches presented here can be applied with a variety of other continuous phenomena to address historical changes, extreme events, and their associated ecological responses.

Active control on high-order coherence and statistic characterization on random phase fluctuation of two classical point sources.

Science.gov (United States)

Hong, Peilong; Li, Liming; Liu, Jianji; Zhang, Guoquan

2016-03-29

Young's double-slit or two-beam interference is of fundamental importance to understand various interference effects, in which the stationary phase difference between two beams plays the key role in the first-order coherence. Different from the case of first-order coherence, in the high-order optical coherence the statistic behavior of the optical phase will play the key role. In this article, by employing a fundamental interfering configuration with two classical point sources, we showed that the high- order optical coherence between two classical point sources can be actively designed by controlling the statistic behavior of the relative phase difference between two point sources. Synchronous position Nth-order subwavelength interference with an effective wavelength of λ/M was demonstrated, in which λ is the wavelength of point sources and M is an integer not larger than N. Interestingly, we found that the synchronous position Nth-order interference fringe fingerprints the statistic trace of random phase fluctuation of two classical point sources, therefore, it provides an effective way to characterize the statistic properties of phase fluctuation for incoherent light sources.

Second-Order Statistics for Wave Propagation through Complex Optical Systems

DEFF Research Database (Denmark)

Yura, H.T.; Hanson, Steen Grüner

1989-01-01

Closed-form expressions are derived for various statistical functions that arise in optical propagation through arbitrary optical systems that can be characterized by a complex ABCD matrix in the presence of distributed random inhomogeneities along the optical path. Specifically, within the second......-order Rytov approximation, explicit general expressions are presented for the mutual coherence function, the log-amplitude and phase correlation functions, and the mean-square irradiance that are obtained in propagation through an arbitrary paraxial ABCD optical system containing Gaussian-shaped limiting...

Higher order capacity statistics of multi-hop transmission systems over Rayleigh fading channels

KAUST Repository

Yilmaz, Ferkan; Tabassum, Hina; Alouini, Mohamed-Slim

2012-01-01

In this paper, we present an exact analytical expression to evaluate the higher order statistics of the channel capacity for amplify and forward (AF) multihop transmission systems operating over Rayleigh fading channels. Furthermore, we present

Freezing and extreme-value statistics in a random energy model with logarithmically correlated potential

International Nuclear Information System (INIS)

Fyodorov, Yan V; Bouchaud, Jean-Philippe

2008-01-01

We investigate some implications of the freezing scenario proposed by Carpentier and Le Doussal (CLD) for a random energy model (REM) with logarithmically correlated random potential. We introduce a particular (circular) variant of the model, and show that the integer moments of the partition function in the high-temperature phase are given by the well-known Dyson Coulomb gas integrals. The CLD freezing scenario allows one to use those moments for extracting the distribution of the free energy in both high- and low-temperature phases. In particular, it yields the full distribution of the minimal value in the potential sequence. This provides an explicit new class of extreme-value statistics for strongly correlated variables, manifestly different from the standard Gumbel class. (fast track communication)

Freezing and extreme-value statistics in a random energy model with logarithmically correlated potential

Energy Technology Data Exchange (ETDEWEB)

Fyodorov, Yan V [School of Mathematical Sciences, University of Nottingham, Nottingham NG72RD (United Kingdom); Bouchaud, Jean-Philippe [Science and Finance, Capital Fund Management 6-8 Bd Haussmann, 75009 Paris (France)

2008-09-19

We investigate some implications of the freezing scenario proposed by Carpentier and Le Doussal (CLD) for a random energy model (REM) with logarithmically correlated random potential. We introduce a particular (circular) variant of the model, and show that the integer moments of the partition function in the high-temperature phase are given by the well-known Dyson Coulomb gas integrals. The CLD freezing scenario allows one to use those moments for extracting the distribution of the free energy in both high- and low-temperature phases. In particular, it yields the full distribution of the minimal value in the potential sequence. This provides an explicit new class of extreme-value statistics for strongly correlated variables, manifestly different from the standard Gumbel class. (fast track communication)

Extremely Stable Polypyrrole Achieved via Molecular Ordering for Highly Flexible Supercapacitors.

Science.gov (United States)

Huang, Yan; Zhu, Minshen; Pei, Zengxia; Huang, Yang; Geng, Huiyuan; Zhi, Chunyi

2016-01-27

The cycling stability of flexible supercapacitors with conducting polymers as electrodes is limited by the structural breakdown arising from repetitive counterion flow during charging/discharging. Supercapacitors made of facilely electropolymerized polypyrrole (e-PPy) have ultrahigh capacitance retentions of more than 97, 91, and 86% after 15000, 50000, and 100000 charging/discharging cycles, respectively, and can sustain more than 230000 charging/discharging cycles with still approximately half of the initial capacitance retained. To the best of our knowledge, such excellent long-term cycling stability was never reported. The fully controllable electropolymerization shows superiority in molecular ordering, favoring uniform stress distribution and charge transfer. Being left at ambient conditions for even 8 months, e-PPy supercapacitors completely retain the good electrochemical performance. The extremely stable supercapacitors with excellent flexibility and scalability hold considerable promise for the commerical application of flexible and wearable electronics.

f ( λ , μ $f_{(\\lambda,\\mu}$ -statistical convergence of order α̃ for double sequences

Directory of Open Access Journals (Sweden)

Mahmut Işik

2017-10-01

Full Text Available Abstract New concepts of f λ , μ $f_{\\lambda,\\mu }$ -statistical convergence for double sequences of order α̃ and strong f λ , μ $f_{\\lambda,\\mu }$ -Cesàro summability for double sequences of order α̃ are introduced for sequences of (complex or real numbers. Furthermore, we give the relationship between the spaces w α ˜ , 0 2 ( f , λ , μ $w_{\\tilde{\\alpha },0}^{2} ( f,\\lambda,\\mu $ , w α ˜ 2 ( f , λ , μ $w_{\\tilde{\\alpha }}^{2} ( f,\\lambda,\\mu $ and w α ˜ , ∞ 2 ( f , λ , μ $w_{\\tilde{\\alpha},\\infty }^{2} ( f,\\lambda,\\mu $ . Then we express the properties of strong f λ , μ $f_{\\lambda,\\mu }$ -Cesàro summability of order β̃ which is related to strong f λ , μ $f_{\\lambda,\\mu }$ -Cesàro summability of order α̃. Also, some relations between f λ , μ $f_{\\lambda,\\mu }$ -statistical convergence of order α̃ and strong f λ , μ $f_{\\lambda,\\mu }$ -Cesàro summability of order α̃ are given.

Comparison of the Effects of Walking with and without Nordic Pole on Upper Extremity and Lower Extremity Muscle Activation.

Science.gov (United States)

Shim, Je-Myung; Kwon, Hae-Yeon; Kim, Ha-Roo; Kim, Bo-In; Jung, Ju-Hyeon

2013-12-01

[Purpose] The aim of this study was to assess the effect of Nordic pole walking on the electromyographic activities of upper extremity and lower extremity muscles. [Subjects and Methods] The subjects were randomly divided into two groups as follows: without Nordic pole walking group (n=13) and with Nordic pole walking group (n=13). The EMG data were collected by measurement while the subjects walking on a treadmill for 30 minutes by measuring from one heel strike to the next. [Results] Both the average values and maximum values of the muscle activity of the upper extremity increased in both the group that used Nordic poles and the group that did not use Nordic poles, and the values showed statistically significant differences. There was an increase in the average value for muscle activity of the latissimus dorsi, but the difference was not statistically significant, although there was a statistically significant increase in its maximum value. The average and maximum values for muscle activity of the lower extremity did not show large differences in either group, and the values did not show any statistically significant differences. [Conclusion] The use of Nordic poles by increased muscle activity of the upper extremity compared with regular walking but did not affect the lower extremity.

Statistical analysis on extreme wave height

Digital Repository Service at National Institute of Oceanography (India)

Teena, N.V.; SanilKumar, V.; Sudheesh, K.; Sajeev, R.

-294. • WAFO (2000) – A MATLAB toolbox for analysis of random waves and loads, Lund University, Sweden, homepage http://www.maths.lth.se/matstat/wafo/,2000. 15    Table 1: Statistical results of data and fitted distribution for cumulative distribution...

Computing the Moments of Order Statistics from Truncated Pareto Distributions Based on the Conditional Expectation

Directory of Open Access Journals (Sweden)

Gökhan Gökdere

2014-05-01

Full Text Available In this paper, closed form expressions for the moments of the truncated Pareto order statistics are obtained by using conditional distribution. We also derive some results for the moments which will be useful for moment computations based on ordered data.

An evaluation of the uncertainty of extreme events statistics at the WMO/CIMO Lead Centre on precipitation intensity

Science.gov (United States)

Colli, M.; Lanza, L. G.; La Barbera, P.

2012-12-01

Improving the quality of point-scale rainfall measurements is a crucial issue fostered in recent years by the WMO Commission for Instruments and Methods of Observation (CIMO) by providing recommendations on the standardization of equipment and exposure, instrument calibration and data correction as a consequence of various comparative campaigns involving manufacturers and national meteorological services from the participating countries. The WMO/CIMO Lead Centre on Precipitation Intensity (LC) was recently constituted, in a joint effort between the Dep. of Civil, Chemical and Environmental Engineering of the University of Genova and the Italian Air Force Met Service, gathering the considerable asset of data and information achieved by the past infield and laboratory campaigns with the aim of researching novel methodologies for improving the accuracy of rainfall intensity (RI) measurement techniques. Among the ongoing experimental activities carried out by the LC laboratory particular attention is paid to the reliability evaluation of extreme rainfall events statistics , a common tool in the engineering practice for urban and non urban drainage system design, based on real world observations obtained from weighing gauges. Extreme events statistics were proven already to be highly affected by the traditional tipping-bucket rain gauge RI measurement inaccuracy (La Barbera et al., 2002) and the time resolution of the available RI series certainly constitutes another key-factor in the reliability of the derived hyetographs. The present work reports the LC laboratory efforts in assembling a rainfall simulation system to reproduce the inner temporal structure of the rainfall process by means of dedicated calibration and validation tests. This allowed testing of catching type rain gauges under non-steady flow conditions and quantifying, in a first instance, the dynamic behaviour of the investigated instruments. Considerations about the influence of the dynamic response on

Extreme value statistics and thermodynamics of earthquakes: aftershock sequences

Directory of Open Access Journals (Sweden)

B. H. Lavenda

2000-06-01

Full Text Available The Gutenberg-Richter magnitude-frequency law takes into account the minimum detectable magnitude, and treats aftershocks as if they were independent and identically distributed random events. A new magnitude-frequency relation is proposed which takes into account the magnitude of the main shock, and the degree to which aftershocks depend on the main shock makes them appear clustered. In certain cases, there can be two branches in the order-statistics of aftershock sequences: for energies below threshold, the Pareto law applies and the asymptotic distribution of magnitude is the double-exponential distribution, while energies above threshold follow a one-parameter beta distribution, whose exponent is the cluster dimension, and the asymptotic Gompertz distribution predicts a maximum magnitude. The 1957 Aleutian Islands aftershock sequence exemplifies such dual behavior. A thermodynamics of aftershocks is constructed on the analogy between the non-conservation of the number of aftershocks and that of the particle number in degenerate gases.

Novel asymptotic results on the high-order statistics of the channel capacity over generalized fading channels

KAUST Repository

Yilmaz, Ferkan; Alouini, Mohamed-Slim

2012-01-01

The exact analysis of the higher-order statistics of the channel capacity (i.e., higher-order ergodic capacity) often leads to complicated expressions involving advanced special functions. In this paper, we provide a generic framework

Higher order magnetic modulation structures in rare earth metal, alloys and compounds under extreme conditions

International Nuclear Information System (INIS)

Kawano, S.

2003-01-01

Magnetic materials consisting of rare earth ions form modulation structures such as a helical or sinusoidal structure caused by the oscillating magnetic interaction between rare earth ions due to RKKY magnetic interaction. These modulation structures, in some cases, develop further to higher order modulation structures by additional modulations caused by higher order crystalline electric field, magnetic interactions such as spin-lattice interaction, external magnetic field and pressure. The higher order modulation structures are observed in a spin-slip structure or a helifan structure in Ho, and a tilt helix structure in a TbEr alloy. Paramagnetic ions originated from frustration generate many magnetic phases under applied external magnetic field. KUR neutron diffraction groups have performed the development and adjustment of high-pressure instruments and external magnetic fields for neutron diffraction spectrometers. The studies of 'neutron diffraction under extreme conditions' by the seven groups are described in this report. (Y. Kazumata)

Joint statistics of partial sums of ordered exponential variates and performance of GSC RAKE receivers over rayleigh fading channel

KAUST Repository

Nam, Sungsik; Hasna, Mazen Omar; Alouini, Mohamed-Slim

2011-01-01

-interference on GSC RAKE receivers. The major difficulty in these problems is to derive some joint statistics of ordered exponential variates. With this motivation in mind, we capitalize in this paper on some new order statistics results to derive exact closed

Statistical Analysis of Wave Climate Data Using Mixed Distributions and Extreme Wave Prediction

Directory of Open Access Journals (Sweden)

Wei Li

2016-05-01

Full Text Available The investigation of various aspects of the wave climate at a wave energy test site is essential for the development of reliable and efficient wave energy conversion technology. This paper presents studies of the wave climate based on nine years of wave observations from the 2005–2013 period measured with a wave measurement buoy at the Lysekil wave energy test site located off the west coast of Sweden. A detailed analysis of the wave statistics is investigated to reveal the characteristics of the wave climate at this specific test site. The long-term extreme waves are estimated from applying the Peak over Threshold (POT method on the measured wave data. The significant wave height and the maximum wave height at the test site for different return periods are also compared. In this study, a new approach using a mixed-distribution model is proposed to describe the long-term behavior of the significant wave height and it shows an impressive goodness of fit to wave data from the test site. The mixed-distribution model is also applied to measured wave data from four other sites and it provides an illustration of the general applicability of the proposed model. The methodologies used in this paper can be applied to general wave climate analysis of wave energy test sites to estimate extreme waves for the survivability assessment of wave energy converters and characterize the long wave climate to forecast the wave energy resource of the test sites and the energy production of the wave energy converters.

How Much Math Do Students Need to Succeed in Business and Economics Statistics? An Ordered Probit Analysis

Science.gov (United States)

Green, Jeffrey J.; Stone, Courtenay C.; Zegeye, Abera; Charles, Thomas A.

2009-01-01

Because statistical analysis requires the ability to use mathematics, students typically are required to take one or more prerequisite math courses prior to enrolling in the business statistics course. Despite these math prerequisites, however, many students find it difficult to learn business statistics. In this study, we use an ordered probit…

Detection of Doppler Microembolic Signals Using High Order Statistics

Directory of Open Access Journals (Sweden)

Maroun Geryes

2016-01-01

Full Text Available Robust detection of the smallest circulating cerebral microemboli is an efficient way of preventing strokes, which is second cause of mortality worldwide. Transcranial Doppler ultrasound is widely considered the most convenient system for the detection of microemboli. The most common standard detection is achieved through the Doppler energy signal and depends on an empirically set constant threshold. On the other hand, in the past few years, higher order statistics have been an extensive field of research as they represent descriptive statistics that can be used to detect signal outliers. In this study, we propose new types of microembolic detectors based on the windowed calculation of the third moment skewness and fourth moment kurtosis of the energy signal. During energy embolus-free periods the distribution of the energy is not altered and the skewness and kurtosis signals do not exhibit any peak values. In the presence of emboli, the energy distribution is distorted and the skewness and kurtosis signals exhibit peaks, corresponding to the latter emboli. Applied on real signals, the detection of microemboli through the skewness and kurtosis signals outperformed the detection through standard methods. The sensitivities and specificities reached 78% and 91% and 80% and 90% for the skewness and kurtosis detectors, respectively.

Long-term statistics of extreme tsunami height at Crescent City

Science.gov (United States)

Dong, Sheng; Zhai, Jinjin; Tao, Shanshan

2017-06-01

Historically, Crescent City is one of the most vulnerable communities impacted by tsunamis along the west coast of the United States, largely attributed to its offshore geography. Trans-ocean tsunamis usually produce large wave runup at Crescent Harbor resulting in catastrophic damages, property loss and human death. How to determine the return values of tsunami height using relatively short-term observation data is of great significance to assess the tsunami hazards and improve engineering design along the coast of Crescent City. In the present study, the extreme tsunami heights observed along the coast of Crescent City from 1938 to 2015 are fitted using six different probabilistic distributions, namely, the Gumbel distribution, the Weibull distribution, the maximum entropy distribution, the lognormal distribution, the generalized extreme value distribution and the generalized Pareto distribution. The maximum likelihood method is applied to estimate the parameters of all above distributions. Both Kolmogorov-Smirnov test and root mean square error method are utilized for goodness-of-fit test and the better fitting distribution is selected. Assuming that the occurrence frequency of tsunami in each year follows the Poisson distribution, the Poisson compound extreme value distribution can be used to fit the annual maximum tsunami amplitude, and then the point and interval estimations of return tsunami heights are calculated for structural design. The results show that the Poisson compound extreme value distribution fits tsunami heights very well and is suitable to determine the return tsunami heights for coastal disaster prevention.

Statistics of fermions in the Randall-Wilkins model for kinetics of general order

International Nuclear Information System (INIS)

Nieto H, B.; Azorin N, J.; Vazquez C, G.A.

2004-01-01

As a theoretical planning of the thermoluminescence phenomena (Tl), we study the behavior of the systems formed by fermions, which are related with this phenomenon establishing a generalization of the Randall-Wilkins model, as for first order kinetics as for general order (equation of May and Partridge) in which we consider a of Fermi-Dirac statistics. As consequence of this study a new variable is manifested: the chemical potential, also we establish its relationship with some of the other magnitudes already known in Tl. (Author)

Spin-resolved photoelectron spectroscopy using femtosecond extreme ultraviolet light pulses from high-order harmonic generation

Energy Technology Data Exchange (ETDEWEB)

Plötzing, M.; Adam, R., E-mail: r.adam@fz-juelich.de; Weier, C.; Plucinski, L.; Schneider, C. M. [Forschungszentrum Jülich GmbH, Peter Grünberg Institut (PGI-6), 52425 Jülich (Germany); Eich, S.; Emmerich, S.; Rollinger, M.; Aeschlimann, M. [University of Kaiserslautern and Research Center OPTIMAS, 67663 Kaiserslautern (Germany); Mathias, S. [Georg-August-Universität Göttingen, I. Physikalisches Institut, 37077 Göttingen (Germany)

2016-04-15

The fundamental mechanism responsible for optically induced magnetization dynamics in ferromagnetic thin films has been under intense debate since almost two decades. Currently, numerous competing theoretical models are in strong need for a decisive experimental confirmation such as monitoring the triggered changes in the spin-dependent band structure on ultrashort time scales. Our approach explores the possibility of observing femtosecond band structure dynamics by giving access to extended parts of the Brillouin zone in a simultaneously time-, energy- and spin-resolved photoemission experiment. For this purpose, our setup uses a state-of-the-art, highly efficient spin detector and ultrashort, extreme ultraviolet light pulses created by laser-based high-order harmonic generation. In this paper, we present the setup and first spin-resolved spectra obtained with our experiment within an acquisition time short enough to allow pump-probe studies. Further, we characterize the influence of the excitation with femtosecond extreme ultraviolet pulses by comparing the results with data acquired using a continuous wave light source with similar photon energy. In addition, changes in the spectra induced by vacuum space-charge effects due to both the extreme ultraviolet probe- and near-infrared pump-pulses are studied by analyzing the resulting spectral distortions. The combination of energy resolution and electron count rate achieved in our setup confirms its suitability for spin-resolved studies of the band structure on ultrashort time scales.

Modeling the Pineapple Express phenomenon via Multivariate Extreme Value Theory

Science.gov (United States)

Weller, G.; Cooley, D. S.

2011-12-01

The pineapple express (PE) phenomenon is responsible for producing extreme winter precipitation events in the coastal and mountainous regions of the western United States. Because the PE phenomenon is also associated with warm temperatures, the heavy precipitation and associated snowmelt can cause destructive flooding. In order to study impacts, it is important that regional climate models from NARCCAP are able to reproduce extreme precipitation events produced by PE. We define a daily precipitation quantity which captures the spatial extent and intensity of precipitation events produced by the PE phenomenon. We then use statistical extreme value theory to model the tail dependence of this quantity as seen in an observational data set and each of the six NARCCAP regional models driven by NCEP reanalysis. We find that most NCEP-driven NARCCAP models do exhibit tail dependence between daily model output and observations. Furthermore, we find that not all extreme precipitation events are pineapple express events, as identified by Dettinger et al. (2011). The synoptic-scale atmospheric processes that drive extreme precipitation events produced by PE have only recently begun to be examined. Much of the current work has focused on pattern recognition, rather than quantitative analysis. We use daily mean sea-level pressure (MSLP) fields from NCEP to develop a "pineapple express index" for extreme precipitation, which exhibits tail dependence with our observed precipitation quantity for pineapple express events. We build a statistical model that connects daily precipitation output from the WRFG model, daily MSLP fields from NCEP, and daily observed precipitation in the western US. Finally, we use this model to simulate future observed precipitation based on WRFG output driven by the CCSM model, and our pineapple express index derived from future CCSM output. Our aim is to use this model to develop a better understanding of the frequency and intensity of extreme

Book review: Extreme ocean waves

Science.gov (United States)

Geist, Eric L.

2011-01-01

‘‘Extreme Ocean Waves’’ is a collection of ten papers edited by Efim Pelinovsky and Christian Kharif that followed the April 2007 meeting of the General Assembly of the European Geosciences Union. A note on terminology: extreme waves in this volume broadly encompass different types of waves, includ- ing deep-water and shallow-water rogue waves (alternatively termed freak waves), storm surges from cyclones, and internal waves. Other types of waves such as tsunamis or rissaga (meteotsunamis) are not discussed in this volume. It is generally implied that ‘‘extreme’’ has a statistical connotation relative to the average or significant wave height specific to each type of wave. Throughout the book, in fact, the reader will find a combination of theoretical and statistical/ empirical treatment necessary for the complete examination of this subject. In the introduction, the editors underscore the importance of studying extreme waves, documenting several dramatic instances of damaging extreme waves that occurred in 2007. 

Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

Science.gov (United States)

Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

2012-04-01

During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and

Quantile selection procedure and assoiated distribution of ratios of order statistics from a restricted family of probability distributions

International Nuclear Information System (INIS)

Gupta, S.S.; Panchapakesan, S.

1975-01-01

A quantile selection procedure in reliability problems pertaining to a restricted family of probability distributions is discussed. This family is assumed to be star-ordered with respect to the standard normal distribution folded at the origin. Motivation for this formulation of the problem is described. Both exact and asymptotic results dealing with the distribution of the maximum of ratios of order statistics from such a family are obtained and tables of the appropriate constants, percentiles of this statistic, are given in order to facilitate the use of the selection procedure

Using Extreme Tropical Precipitation Statistics to Constrain Future Climate States

Science.gov (United States)

Igel, M.; Biello, J. A.

2017-12-01

Tropical precipitation is characterized by a rapid growth in mean intensity as the column humidity increases. This behavior is examined in both a cloud resolving model and with high-resolution observations of precipitation and column humidity from CloudSat and AIRS, respectively. The model and the observations exhibit remarkable consistency and suggest a new paradigm for extreme precipitation. We show that the total precipitation can be decomposed into a product of contributions from a mean intensity, a probability of precipitation, and a global PDF of column humidity values. We use the modeling and observational results to suggest simple, analytic forms for each of these functions. The analytic representations are then used to construct a simple expression for the global accumulated precipitation as a function of the parameters of each of the component functions. As the climate warms, extreme precipitation intensity and global precipitation are expected to increase, though at different rates. When these predictions are incorporated into the new analytic expression for total precipitation, predictions for changes due to global warming to the probability of precipitation and the PDF of column humidity can be made. We show that strong constraints can be imposed on the future shape of the PDF of column humidity but that only weak constraints can be set on the probability of precipitation. These are largely imposed by the intensification of extreme precipitation. This result suggests that understanding precisely how extreme precipitation responds to climate warming is critical to predicting other impactful properties of global hydrology. The new framework can also be used to confirm and discount existing theories for shifting precipitation.

Large-eddy simulation in a mixing tee junction: High-order turbulent statistics analysis

International Nuclear Information System (INIS)

Howard, Richard J.A.; Serre, Eric

2015-01-01

Highlights: • Mixing and thermal fluctuations in a junction are studied using large eddy simulation. • Adiabatic and conducting steel wall boundaries are tested. • Wall thermal fluctuations are not the same between the flow and the solid. • Solid thermal fluctuations cannot be predicted from the fluid thermal fluctuations. • High-order turbulent statistics show that the turbulent transport term is important. - Abstract: This study analyses the mixing and thermal fluctuations induced in a mixing tee junction with circular cross-sections when cold water flowing in a pipe is joined by hot water from a branch pipe. This configuration is representative of industrial piping systems in which temperature fluctuations in the fluid may cause thermal fatigue damage on the walls. Implicit large-eddy simulations (LES) are performed for equal inflow rates corresponding to a bulk Reynolds number Re = 39,080. Two different thermal boundary conditions are studied for the pipe walls; an insulating adiabatic boundary and a conducting steel wall boundary. The predicted flow structures show a satisfactory agreement with the literature. The velocity and thermal fields (including high-order statistics) are not affected by the heat transfer with the steel walls. However, predicted thermal fluctuations at the boundary are not the same between the flow and the solid, showing that solid thermal fluctuations cannot be predicted by the knowledge of the fluid thermal fluctuations alone. The analysis of high-order turbulent statistics provides a better understanding of the turbulence features. In particular, the budgets of the turbulent kinetic energy and temperature variance allows a comparative analysis of dissipation, production and transport terms. It is found that the turbulent transport term is an important term that acts to balance the production. We therefore use a priori tests to evaluate three different models for the triple correlation

The effect of extremity strength training on fibromyalgia symptoms and disease impact in an existing multidisciplinary treatment program.

Science.gov (United States)

Kas, Tamara; Colby, Megan; Case, Maureen; Vaughn, Dan

2016-10-01

The purpose of this study was to examine the effect of upper and lower body extremity strengthening exercise in patients with Fibromyalgia (FM) within an existing multidisciplinary treatment program. Patients between the ages of 18-65 with the medical diagnosis of FM. Comparative study design. The control and experimental group received the same multidisciplinary treatment except that the experimental group performed upper and lower extremity strengthening exercises. The Fibromyalgia Impact Questionnaire (FIQ) was administered at evaluation and discharge from the program in order to measure change in quality of life (QOL). Statistically significant changes in FIQ scores were found for both groups. The addition of extremity strengthening in the experimental group produced an average 4 points greater reduction in FIQ score, however, these results are not considered statistically significant. This study appears to validate the success of a multidisciplinary approach in treating patients with FM, with the possibility for further benefit with the addition of extremity strengthening. Copyright © 2016 Elsevier Ltd. All rights reserved.

Wind simulation for extreme and fatigue loads

Energy Technology Data Exchange (ETDEWEB)

Nielsen, M.; Larsen, G.C.; Mann, J.; Ott, S.; Hansen, K.S.; Pedersen, B.J.

2004-01-01

Measurements of atmospheric turbulence have been studied and found to deviate from a Gaussian process, in particular regarding the velocity increments over small time steps, where the tails of the pdf are exponential rather than Gaussian. Principles for extreme event counting and the occurrence of cascading events are presented. Empirical extreme statistics agree with Rices exceedence theory, when it is assumed that the velocity and its time derivative are independent. Prediction based on the assumption that the velocity is a Gaussian process underpredicts the rate of occurrence of extreme events by many orders of magnitude, mainly because the measured pdf is non-Gaussian. Methods for simulation of turbulent signals have been developed and their computational efficiency are considered. The methods are applicable for multiple processes with individual spectra and probability distributions. Non-Gaussian processes are simulated by the correlation-distortion method. Non-stationary processes are obtained by Bezier interpolation between a set of stationary simulations with identical random seeds. Simulation of systems with some signals available is enabled by conditional statistics. A versatile method for simulation of extreme events has been developed. This will generate gusts, velocity jumps, extreme velocity shears, and sudden changes of wind direction. Gusts may be prescribed with a specified ensemble average shape, and it is possible to detect the critical gust shape for a given construction. The problem is formulated as the variational problem of finding the most probable adjustment of a standard simulation of a stationary Gaussian process subject to relevant event conditions, which are formulated as linear combination of points in the realization. The method is generalized for multiple correlated series, multiple simultaneous conditions, and 3D fields of all velocity components. Generalization are presented for a single non-Gaussian process subject to relatively

Tsunami vs Infragravity Surge: Statistics and Physical Character of Extreme Runup

Science.gov (United States)

Lynett, P. J.; Montoya, L. H.

2017-12-01

Motivated by recent observations of energetic and impulsive infragravity (IG) flooding events - also known as sneaker waves - we will present recent work on the relative probabilities and dynamics of extreme flooding events from tsunamis and long period wind wave events. The discussion will be founded on videos and records of coastal flooding by both recent tsunamis and IG, such as those in the Philippines during Typhoon Haiyan. From these observations, it is evident that IG surges may approach the coast as breaking bores with periods of minutes; a very tsunami-like character. Numerical simulations will be used to estimate flow elevations and speeds from potential IG surges, and these will be compared with similar values from tsunamis, over a range of different beach profiles. We will examine the relative rareness of each type of flooding event, which for large values of IG runup is a particularly challenging topic. For example, for a given runup elevation or flooding speed, the related tsunami return period may be longer than that associated with IG, implying that deposit information associated with such elevations or speeds are more likely to be caused by IG. Our purpose is to provide a statistical and physical discriminant between tsunami and IG, such that in areas exposed to both, a proper interpretation of overland transport, deposition, and damage is possible.

On the computation of the higher-order statistics of the channel capacity over generalized fading channels

KAUST Repository

Yilmaz, Ferkan

2012-12-01

The higher-order statistics (HOS) of the channel capacity μn=E[logn (1+γ end)], where n ∈ N denotes the order of the statistics, has received relatively little attention in the literature, due in part to the intractability of its analysis. In this letter, we propose a novel and unified analysis, which is based on the moment generating function (MGF) technique, to exactly compute the HOS of the channel capacity. More precisely, our mathematical formalism can be readily applied to maximal-ratio-combining (MRC) receivers operating in generalized fading environments. The mathematical formalism is illustrated by some numerical examples focusing on the correlated generalized fading environments. © 2012 IEEE.

On the computation of the higher-order statistics of the channel capacity over generalized fading channels

KAUST Repository

Yilmaz, Ferkan; Alouini, Mohamed-Slim

2012-01-01

The higher-order statistics (HOS) of the channel capacity μn=E[logn (1+γ end)], where n ∈ N denotes the order of the statistics, has received relatively little attention in the literature, due in part to the intractability of its analysis. In this letter, we propose a novel and unified analysis, which is based on the moment generating function (MGF) technique, to exactly compute the HOS of the channel capacity. More precisely, our mathematical formalism can be readily applied to maximal-ratio-combining (MRC) receivers operating in generalized fading environments. The mathematical formalism is illustrated by some numerical examples focusing on the correlated generalized fading environments. © 2012 IEEE.

Statistical image reconstruction for transmission tomography using relaxed ordered subset algorithms

International Nuclear Information System (INIS)

Kole, J S

2005-01-01

Statistical reconstruction methods offer possibilities for improving image quality as compared to analytical methods, but current reconstruction times prohibit routine clinical applications in x-ray computed tomography (CT). To reduce reconstruction times, we have applied (under) relaxation to ordered subset algorithms. This enables us to use subsets consisting of only single projection angle, effectively increasing the number of image updates within an entire iteration. A second advantage of applying relaxation is that it can help improve convergence by removing the limit cycle behaviour of ordered subset algorithms, which normally do not converge to an optimal solution but rather a suboptimal limit cycle consisting of as many points as there are subsets. Relaxation suppresses the limit cycle behaviour by decreasing the stepsize for approaching the solution. A simulation study for a 2D mathematical phantom and three different ordered subset algorithms shows that all three algorithms benefit from relaxation: equal noise-to-resolution trade-off can be achieved using fewer iterations than the conventional algorithms, while a lower minimal normalized mean square error (NMSE) clearly indicates a better convergence. Two different schemes for setting the relaxation parameter are studied, and both schemes yield approximately the same minimal NMSE

Statistics of Smoothed Cosmic Fields in Perturbation Theory. I. Formulation and Useful Formulae in Second-Order Perturbation Theory

Science.gov (United States)

Matsubara, Takahiko

2003-02-01

We formulate a general method for perturbative evaluations of statistics of smoothed cosmic fields and provide useful formulae for application of the perturbation theory to various statistics. This formalism is an extensive generalization of the method used by Matsubara, who derived a weakly nonlinear formula of the genus statistic in a three-dimensional density field. After describing the general method, we apply the formalism to a series of statistics, including genus statistics, level-crossing statistics, Minkowski functionals, and a density extrema statistic, regardless of the dimensions in which each statistic is defined. The relation between the Minkowski functionals and other geometrical statistics is clarified. These statistics can be applied to several cosmic fields, including three-dimensional density field, three-dimensional velocity field, two-dimensional projected density field, and so forth. The results are detailed for second-order theory of the formalism. The effect of the bias is discussed. The statistics of smoothed cosmic fields as functions of rescaled threshold by volume fraction are discussed in the framework of second-order perturbation theory. In CDM-like models, their functional deviations from linear predictions plotted against the rescaled threshold are generally much smaller than that plotted against the direct threshold. There is still a slight meatball shift against rescaled threshold, which is characterized by asymmetry in depths of troughs in the genus curve. A theory-motivated asymmetry factor in the genus curve is proposed.

Rational Calibration of Four IEC 61400-1 Extreme External Conditions

DEFF Research Database (Denmark)

Larsen, Gunner Chr.; Hansen, Kurt Schaldemose

2008-01-01

Based on a set of asymptotic statistical models on closed form this paper presents a rational and consistent calibration of four extreme external conditions defined in the International Electrotechnical Commission (IEC) 61400-1 standard: extreme operating gust, extreme wind shear, extreme coheren...... and proposed specifications of the magnitudes of the extreme external wind conditions are highlighted and discussed using an illustrative example based on two selected terrain types. Copyright © 2008 John Wiley & Sons, Ltd....... gust with direction change and extreme wind direction change. These four extreme external conditions are used in the definition of six of the IEC 61400-1 ultimate load cases. The statistical models are based on simple and easily accessible mean wind speed and turbulence characteristics...

Analytical model of SiPM time resolution and order statistics with crosstalk

International Nuclear Information System (INIS)

Vinogradov, S.

2015-01-01

Time resolution is the most important parameter of photon detectors in a wide range of time-of-flight and time correlation applications within the areas of high energy physics, medical imaging, and others. Silicon photomultipliers (SiPM) have been initially recognized as perfect photon-number-resolving detectors; now they also provide outstanding results in the scintillator timing resolution. However, crosstalk and afterpulsing introduce false secondary non-Poissonian events, and SiPM time resolution models are experiencing significant difficulties with that. This study presents an attempt to develop an analytical model of the timing resolution of an SiPM taking into account statistics of secondary events resulting from a crosstalk. Two approaches have been utilized to derive an analytical expression for time resolution: the first one based on statistics of independent identically distributed detection event times and the second one based on order statistics of these times. The first approach is found to be more straightforward and “analytical-friendly” to model analog SiPMs. Comparisons of coincidence resolving times predicted by the model with the known experimental results from a LYSO:Ce scintillator and a Hamamatsu MPPC are presented

Analytical model of SiPM time resolution and order statistics with crosstalk

Energy Technology Data Exchange (ETDEWEB)

Vinogradov, S., E-mail: Sergey.Vinogradov@liverpool.ac.uk [University of Liverpool and Cockcroft Institute, Sci-Tech Daresbury, Keckwick Lane, Warrington WA4 4AD (United Kingdom); P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 119991 Leninskiy Prospekt 53, Moscow (Russian Federation)

2015-07-01

Time resolution is the most important parameter of photon detectors in a wide range of time-of-flight and time correlation applications within the areas of high energy physics, medical imaging, and others. Silicon photomultipliers (SiPM) have been initially recognized as perfect photon-number-resolving detectors; now they also provide outstanding results in the scintillator timing resolution. However, crosstalk and afterpulsing introduce false secondary non-Poissonian events, and SiPM time resolution models are experiencing significant difficulties with that. This study presents an attempt to develop an analytical model of the timing resolution of an SiPM taking into account statistics of secondary events resulting from a crosstalk. Two approaches have been utilized to derive an analytical expression for time resolution: the first one based on statistics of independent identically distributed detection event times and the second one based on order statistics of these times. The first approach is found to be more straightforward and “analytical-friendly” to model analog SiPMs. Comparisons of coincidence resolving times predicted by the model with the known experimental results from a LYSO:Ce scintillator and a Hamamatsu MPPC are presented.

Seasonal Cycle in German Daily Precipitation Extremes

Directory of Open Access Journals (Sweden)

Madlen Fischer

2018-01-01

Full Text Available The seasonal cycle of extreme precipitation in Germany is investigated by fitting statistical models to monthly maxima of daily precipitation sums for 2,865 rain gauges. The basis is a non-stationary generalized extreme value (GEV distribution variation of location and scale parameters. The negative log-likelihood serves as the forecast error for a cross validation to select adequate orders of the harmonic functions for each station. For nearly all gauges considered, the seasonal model is more appropriate to estimate return levels on a monthly scale than a stationary GEV used for individual months. The 100-year return-levels show the influence of cyclones in the western, and convective events in the eastern part of Germany. In addition to resolving the seasonality, we use a simulation study to show that annual return levels can be estimated more precisely from a monthly-resolved seasonal model than from a stationary model based on annual maxima.

Statistics for Research

CERN Document Server

Dowdy, Shirley; Chilko, Daniel

2011-01-01

Praise for the Second Edition "Statistics for Research has other fine qualities besides superior organization. The examples and the statistical methods are laid out with unusual clarity by the simple device of using special formats for each. The book was written with great care and is extremely user-friendly."-The UMAP Journal Although the goals and procedures of statistical research have changed little since the Second Edition of Statistics for Research was published, the almost universal availability of personal computers and statistical computing application packages have made it possible f

Seasonal Climate Extremes : Mechanism, Predictability and Responses to Global Warming

NARCIS (Netherlands)

Shongwe, M.E.

2010-01-01

Climate extremes are rarely occurring natural phenomena in the climate system. They often pose one of the greatest environmental threats to human and natural systems. Statistical methods are commonly used to investigate characteristics of climate extremes. The fitted statistical properties are often

Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain

Science.gov (United States)

Zhou, Anran; Xie, Weixin; Pei, Jihong

2018-06-01

Accurate detection of maritime targets in infrared imagery under various sea clutter conditions is always a challenging task. The fractional Fourier transform (FRFT) is the extension of the Fourier transform in the fractional order, and has richer spatial-frequency information. By combining it with the high order statistic filtering, a new ship detection method is proposed. First, the proper range of angle parameter is determined to make it easier for the ship components and background to be separated. Second, a new high order statistic curve (HOSC) at each fractional frequency point is designed. It is proved that maximal peak interval in HOSC reflects the target information, while the points outside the interval reflect the background. And the value of HOSC relative to the ship is much bigger than that to the sea clutter. Then, search the curve's maximal target peak interval and extract the interval by bandpass filtering in fractional Fourier domain. The value outside the peak interval of HOSC decreases rapidly to 0, so the background is effectively suppressed. Finally, the detection result is obtained by the double threshold segmenting and the target region selection method. The results show the proposed method is excellent for maritime targets detection with high clutters.

First-Order SPICE Modeling of Extreme-Temperature 4H-SiC JFET Integrated Circuits

Science.gov (United States)

Neudeck, Philip G.; Spry, David J.; Chen, Liang-Yu

2016-01-01

A separate submission to this conference reports that 4H-SiC Junction Field Effect Transistor (JFET) digital and analog Integrated Circuits (ICs) with two levels of metal interconnect have reproducibly demonstrated electrical operation at 500 C in excess of 1000 hours. While this progress expands the complexity and durability envelope of high temperature ICs, one important area for further technology maturation is the development of reasonably accurate and accessible computer-aided modeling and simulation tools for circuit design of these ICs. Towards this end, we report on development and verification of 25 C to 500 C SPICE simulation models of first order accuracy for this extreme-temperature durable 4H-SiC JFET IC technology. For maximum availability, the JFET IC modeling is implemented using the baseline-version SPICE NMOS LEVEL 1 model that is common to other variations of SPICE software and importantly includes the body-bias effect. The first-order accuracy of these device models is verified by direct comparison with measured experimental device characteristics.

Tukey max-stable processes for spatial extremes

KAUST Repository

Xu, Ganggang; Genton, Marc G.

2016-01-01

We propose a new type of max-stable process that we call the Tukey max-stable process for spatial extremes. It brings additional flexibility to modeling dependence structures among spatial extremes. The statistical properties of the Tukey max

Stochastic generation of multi-site daily precipitation focusing on extreme events

Directory of Open Access Journals (Sweden)

G. Evin

2018-01-01

Full Text Available Many multi-site stochastic models have been proposed for the generation of daily precipitation, but they generally focus on the reproduction of low to high precipitation amounts at the stations concerned. This paper proposes significant extensions to the multi-site daily precipitation model introduced by Wilks, with the aim of reproducing the statistical features of extremely rare events (in terms of frequency and magnitude at different temporal and spatial scales. In particular, the first extended version integrates heavy-tailed distributions, spatial tail dependence, and temporal dependence in order to obtain a robust and appropriate representation of the most extreme precipitation fields. A second version enhances the first version using a disaggregation method. The performance of these models is compared at different temporal and spatial scales on a large region covering approximately half of Switzerland. While daily extremes are adequately reproduced at the stations by all models, including the benchmark Wilks version, extreme precipitation amounts at larger temporal scales (e.g., 3-day amounts are clearly underestimated when temporal dependence is ignored.

On the Extreme Wave Height Analysis

DEFF Research Database (Denmark)

Burcharth, H. F.; Liu, Zhou

1994-01-01

The determination of the design wave height is usually based on the statistical analysis of long-term extreme wave height measurements. After an introduction to the procedure of the extreme wave height analysis, the paper presents new development concerning various aspects of the extreme wave...... height analysis. Finally, the paper gives a practical example based on a data set of the hindcasted wave heights for a deep water location in the Mediterranean Sea....

Assessment of extreme value distributions for maximum temperature in the Mediterranean area

Science.gov (United States)

Beck, Alexander; Hertig, Elke; Jacobeit, Jucundus

2015-04-01

Extreme maximum temperatures highly affect the natural as well as the societal environment Heat stress has great effects on flora, fauna and humans and culminates in heat related morbidity and mortality. Agriculture and different industries are severely affected by extreme air temperatures. Even more under climate change conditions, it is necessary to detect potential hazards which arise from changes in the distributional parameters of extreme values, and this is especially relevant for the Mediterranean region which is characterized as a climate change hot spot. Therefore statistical approaches are developed to estimate these parameters with a focus on non-stationarities emerging in the relationship between regional climate variables and their large-scale predictors like sea level pressure, geopotential heights, atmospheric temperatures and relative humidity. Gridded maximum temperature data from the daily E-OBS dataset (Haylock et al., 2008) with a spatial resolution of 0.25° x 0.25° from January 1950 until December 2012 are the predictands for the present analyses. A s-mode principal component analysis (PCA) has been performed in order to reduce data dimension and to retain different regions of similar maximum temperature variability. The grid box with the highest PC-loading represents the corresponding principal component. A central part of the analyses is the model development for temperature extremes under the use of extreme value statistics. A combined model is derived consisting of a Generalized Pareto Distribution (GPD) model and a quantile regression (QR) model which determines the GPD location parameters. The QR model as well as the scale parameters of the GPD model are conditioned by various large-scale predictor variables. In order to account for potential non-stationarities in the predictors-temperature relationships, a special calibration and validation scheme is applied, respectively. Haylock, M. R., N. Hofstra, A. M. G. Klein Tank, E. J. Klok, P

Symmetries, invariants and generating functions: higher-order statistics of biased tracers

Science.gov (United States)

Munshi, Dipak

2018-01-01

Gravitationally collapsed objects are known to be biased tracers of an underlying density contrast. Using symmetry arguments, generalised biasing schemes have recently been developed to relate the halo density contrast δh with the underlying density contrast δ, divergence of velocity θ and their higher-order derivatives. This is done by constructing invariants such as s, t, ψ,η. We show how the generating function formalism in Eulerian standard perturbation theory (SPT) can be used to show that many of the additional terms based on extended Galilean and Lifshitz symmetry actually do not make any contribution to the higher-order statistics of biased tracers. Other terms can also be drastically simplified allowing us to write the vertices associated with δh in terms of the vertices of δ and θ, the higher-order derivatives and the bias coefficients. We also compute the cumulant correlators (CCs) for two different tracer populations. These perturbative results are valid for tree-level contributions but at an arbitrary order. We also take into account the stochastic nature bias in our analysis. Extending previous results of a local polynomial model of bias, we express the one-point cumulants Script SN and their two-point counterparts, the CCs i.e. Script Cpq, of biased tracers in terms of that of their underlying density contrast counterparts. As a by-product of our calculation we also discuss the results using approximations based on Lagrangian perturbation theory (LPT).

Order statistics and energy-ordered histograms: an analytical approach to continuum gamma-ray spectra

International Nuclear Information System (INIS)

Urrego, J.P.; Cristancho, F.

2001-01-01

Full text: Fusion-evaporation heavy ion collisions have enable us to explore new regions of phase space E - I, particularly high spin and excitation energy regions, where level densities are so high that modern detectors are unable to resolve individual gamma-ray transitions and consequently the resulting spectrum is continuous and undoubtedly contains a lot of new physics. In spite of that, very few experiments have been designed to extract conclusions about behavior of nuclei in continuum, thus in order to obtain a continuum spectroscopy it is necessary to apply to numerical simulations. In this sense GAMBLE a Monte Carlo based code- is a powerful tool that with some modifications allows us to test a new method to analyze the outcome of experiments focused on the properties of phase space regions in nuclear continuum: The use of Energy-Ordered Spectra (EOS) . Let's suppose that in a experiment is collected all gamma radiation emitted by a specific nucleus in a fixed intrinsic excitation energy range and that the different EOS are constructed. Although it has been shown that comparisons between such EOS and Monte Carlo simulations give information about the level density and the strength function their interpretation is not too clear because the large number of input values needed in a code like GAMBLE. On the other hand, if we could have an analytical description of EOS, the understanding of the underlying physics would be more simple because one could control exactly the involved variables and eventually simulation would be unnecessary. Promissory advances in that direction come from mathematical theory of Order Statistics (OS) In this work it is described the modified code GAMBLE and some simulated EOS for 170 Hf are shown. The simulations are made with different formulations for both level density (Fermi Gas at constant and variable temperature) and gamma strength function (GDR, single particle). Further it is described in detail how OS are employed in the

Extremes in random fields a theory and its applications

CERN Document Server

Yakir, Benjamin

2013-01-01

Presents a useful new technique for analyzing the extreme-value behaviour of random fields Modern science typically involves the analysis of increasingly complex data. The extreme values that emerge in the statistical analysis of complex data are often of particular interest. This book focuses on the analytical approximations of the statistical significance of extreme values. Several relatively complex applications of the technique to problems that emerge in practical situations are presented.  All the examples are difficult to analyze using classical methods, and as a result, the author pr

SOERP, Statistics and 2. Order Error Propagation for Function of Random Variables

International Nuclear Information System (INIS)

Cox, N. D.; Miller, C. F.

1985-01-01

1 - Description of problem or function: SOERP computes second-order error propagation equations for the first four moments of a function of independently distributed random variables. SOERP was written for a rigorous second-order error propagation of any function which may be expanded in a multivariable Taylor series, the input variables being independently distributed. The required input consists of numbers directly related to the partial derivatives of the function, evaluated at the nominal values of the input variables and the central moments of the input variables from the second through the eighth. 2 - Method of solution: The development of equations for computing the propagation of errors begins by expressing the function of random variables in a multivariable Taylor series expansion. The Taylor series expansion is then truncated, and statistical operations are applied to the series in order to obtain equations for the moments (about the origin) of the distribution of the computed value. If the Taylor series is truncated after powers of two, the procedure produces second-order error propagation equations. 3 - Restrictions on the complexity of the problem: The maximum number of component variables allowed is 30. The IBM version will only process one set of input data per run

Statistical nature of non-Gaussianity from cubic order primordial perturbations: CMB map simulations and genus statistic

International Nuclear Information System (INIS)

Chingangbam, Pravabati; Park, Changbom

2009-01-01

We simulate CMB maps including non-Gaussianity arising from cubic order perturbations of the primordial gravitational potential, characterized by the non-linearity parameter g NL . The maps are used to study the characteristic nature of the resulting non-Gaussian temperature fluctuations. We measure the genus and investigate how it deviates from Gaussian shape as a function of g NL and smoothing scale. We find that the deviation of the non-Gaussian genus curve from the Gaussian one has an antisymmetric, sine function like shape, implying more hot and more cold spots for g NL > 0 and less of both for g NL NL and also exhibits mild increase as the smoothing scale increases. We further study other statistics derived from the genus, namely, the number of hot spots, the number of cold spots, combined number of hot and cold spots and the slope of the genus curve at mean temperature fluctuation. We find that these observables carry signatures of g NL that are clearly distinct from the quadratic order perturbations, encoded in the parameter f NL . Hence they can be very useful tools for distinguishing not only between non-Gaussian temperature fluctuations and Gaussian ones but also between g NL and f NL type non-Gaussianities

A Statistically-Hiding Integer Commitment Scheme Based on Groups with Hidden Order

DEFF Research Database (Denmark)

Damgård, Ivan Bjerre; Fujisaki, Eiichiro

2002-01-01

We present a statistically-hiding commitment scheme allowing commitment to arbitrary size integers, based on any (Abelian) group with certain properties, most importantly, that it is hard for the committer to compute its order. We also give efficient zero-knowledge protocols for proving knowledge...... input is chosen by the (possibly cheating) prover. -  - Our results apply to any group with suitable properties. In particular, they apply to a much larger class of RSA moduli than the safe prime products proposed in [14] - Potential examples include RSA moduli, class groups and, with a slight...

Extreme value statistics for two-dimensional convective penetration in a pre-main sequence star

Science.gov (United States)

Pratt, J.; Baraffe, I.; Goffrey, T.; Constantino, T.; Viallet, M.; Popov, M. V.; Walder, R.; Folini, D.

2017-08-01

Context. In the interior of stars, a convectively unstable zone typically borders a zone that is stable to convection. Convective motions can penetrate the boundary between these zones, creating a layer characterized by intermittent convective mixing, and gradual erosion of the density and temperature stratification. Aims: We examine a penetration layer formed between a central radiative zone and a large convection zone in the deep interior of a young low-mass star. Using the Multidimensional Stellar Implicit Code (MUSIC) to simulate two-dimensional compressible stellar convection in a spherical geometry over long times, we produce statistics that characterize the extent and impact of convective penetration in this layer. Methods: We apply extreme value theory to the maximal extent of convective penetration at any time. We compare statistical results from simulations which treat non-local convection, throughout a large portion of the stellar radius, with simulations designed to treat local convection in a small region surrounding the penetration layer. For each of these situations, we compare simulations of different resolution, which have different velocity magnitudes. We also compare statistical results between simulations that radiate energy at a constant rate to those that allow energy to radiate from the stellar surface according to the local surface temperature. Results: Based on the frequency and depth of penetrating convective structures, we observe two distinct layers that form between the convection zone and the stable radiative zone. We show that the probability density function of the maximal depth of convective penetration at any time corresponds closely in space with the radial position where internal waves are excited. We find that the maximal penetration depth can be modeled by a Weibull distribution with a small shape parameter. Using these results, and building on established scalings for diffusion enhanced by large-scale convective motions, we

Evaluation of extreme temperature events in northern Spain based on process control charts

Science.gov (United States)

Villeta, M.; Valencia, J. L.; Saá, A.; Tarquis, A. M.

2018-02-01

Extreme climate events have recently attracted the attention of a growing number of researchers because these events impose a large cost on agriculture and associated insurance planning. This study focuses on extreme temperature events and proposes a new method for their evaluation based on statistical process control tools, which are unusual in climate studies. A series of minimum and maximum daily temperatures for 12 geographical areas of a Spanish region between 1931 and 2009 were evaluated by applying statistical process control charts to statistically test whether evidence existed for an increase or a decrease of extreme temperature events. Specification limits were determined for each geographical area and used to define four types of extreme anomalies: lower and upper extremes for the minimum and maximum anomalies. A new binomial Markov extended process that considers the autocorrelation between extreme temperature events was generated for each geographical area and extreme anomaly type to establish the attribute control charts for the annual fraction of extreme days and to monitor the occurrence of annual extreme days. This method was used to assess the significance of changes and trends of extreme temperature events in the analysed region. The results demonstrate the effectiveness of an attribute control chart for evaluating extreme temperature events. For example, the evaluation of extreme maximum temperature events using the proposed statistical process control charts was consistent with the evidence of an increase in maximum temperatures during the last decades of the last century.

Order-specific fertility rates for Germany: Estimates from perinatal statistics for the period 2001-2008

NARCIS (Netherlands)

M. Kreyenfeld (Michaela); Scholz, R. (Rembrandt); F. Peters (Frederick); Wlosnewski, I. (Ines)

2010-01-01

textabstractUntil 2008, Germany's vital statistics did not include information on the biological order of each birth. This resulted in a dearth of important demographic indicators, such as the mean age at first birth and the level of childlessness. Researchers have tried to fill this gap by

Consistency of extreme flood estimation approaches

Science.gov (United States)

Felder, Guido; Paquet, Emmanuel; Penot, David; Zischg, Andreas; Weingartner, Rolf

2017-04-01

Estimations of low-probability flood events are frequently used for the planning of infrastructure as well as for determining the dimensions of flood protection measures. There are several well-established methodical procedures to estimate low-probability floods. However, a global assessment of the consistency of these methods is difficult to achieve, the "true value" of an extreme flood being not observable. Anyway, a detailed comparison performed on a given case study brings useful information about the statistical and hydrological processes involved in different methods. In this study, the following three different approaches for estimating low-probability floods are compared: a purely statistical approach (ordinary extreme value statistics), a statistical approach based on stochastic rainfall-runoff simulation (SCHADEX method), and a deterministic approach (physically based PMF estimation). These methods are tested for two different Swiss catchments. The results and some intermediate variables are used for assessing potential strengths and weaknesses of each method, as well as for evaluating the consistency of these methods.

Extreme meteorological conditions

International Nuclear Information System (INIS)

Altinger de Schwarzkopf, M.L.

1983-01-01

Different meteorological variables which may reach significant extreme values, such as the windspeed and, in particular, its occurrence through tornadoes and hurricanes that necesarily incide and wich must be taken into account at the time of nuclear power plants' installation, are analyzed. For this kind of study, it is necessary to determine the basic phenomenum of design. Two criteria are applied to define the basic values of design for extreme meteorological variables. The first one determines the expected extreme value: it is obtained from analyzing the recurence of the phenomenum in a convened period of time, wich may be generally of 50 years. The second one determines the extreme value of low probability, taking into account the nuclear power plant's operating life -f.ex. 25 years- and considering, during said lapse, the occurrence probabilities of extreme meteorological phenomena. The values may be determined either by the deterministic method, which is based on the acknowledgement of the fundamental physical characteristics of the phenomena or by the probabilistic method, that aims to the analysis of historical statistical data. Brief comments are made on the subject in relation to the Argentine Republic area. (R.J.S.) [es

Second-order advantage from kinetic-spectroscopic data matrices in the presence of extreme spectral overlapping

International Nuclear Information System (INIS)

Culzoni, Maria J.; Goicoechea, Hector C.; Ibanez, Gabriela A.; Lozano, Valeria A.; Marsili, Nilda R.; Olivieri, Alejandro C.; Pagani, Ariana P.

2008-01-01

Multivariate curve resolution coupled to alternating least-squares (MCR-ALS) has been employed to model kinetic-spectroscopic second-order data, with focus on the achievement of the important second-order advantage, under conditions of extreme spectral overlapping among sample components. A series of simulated examples shows that MCR-ALS can conveniently handle the studied analytical problem unlike other second-order multivariate calibration algorithms, provided matrix augmentation is implemented in the spectral mode instead of in the usual kinetic mode. The approach has also been applied to three experimental examples, which involve the determination of: (1) the antiparkinsonian carbidopa (analyte) in the presence of levodopa as a potential interferent, both reacting with cerium (IV) to produce the fluorescent species cerium (III) with different kinetics; (2) Fe(II) (analyte) in the presence of the interferent Zn(II), both catalyzing the oxidation of methyl orange with potassium bromate; and (3) tartrazine (analyte) in the presence of the interferent brilliant blue, both oxidized with potassium bromate, with the interferent leading to a product with an absorption spectrum very similar to tartrazine. The results indicate good analytical performance towards the analytes, despite the intense spectral overlapping and the presence of unexpected constituents in the test samples

Second-order advantage from kinetic-spectroscopic data matrices in the presence of extreme spectral overlapping

Energy Technology Data Exchange (ETDEWEB)

Culzoni, Maria J. [Laboratorio de Desarrollo Analitico y Quimiometria (LADAQ), Catedra de Quimica Analitica I, Facultad de Bioquimica y Ciencias Biologicas, Universidad Nacional del Litoral, Ciudad Universitaria, Santa Fe S3000ZAA (Argentina); Goicoechea, Hector C. [Laboratorio de Desarrollo Analitico y Quimiometria (LADAQ), Catedra de Quimica Analitica I, Facultad de Bioquimica y Ciencias Biologicas, Universidad Nacional del Litoral, Ciudad Universitaria, Santa Fe S3000ZAA (Argentina)], E-mail: hgoico@fbcb.unl.edu.ar; Ibanez, Gabriela A.; Lozano, Valeria A. [Departamento de Quimica Analitica, Facultad de Ciencias Bioquimicas y Farmaceuticas, Universidad Nacional de Rosario and Instituto de Quimica Rosario (IQUIR-CONICET), Suipacha 531, Rosario S2002LRK (Argentina); Marsili, Nilda R. [Laboratorio de Desarrollo Analitico y Quimiometria (LADAQ), Catedra de Quimica Analitica I, Facultad de Bioquimica y Ciencias Biologicas, Universidad Nacional del Litoral, Ciudad Universitaria, Santa Fe S3000ZAA (Argentina); Olivieri, Alejandro C. [Departamento de Quimica Analitica, Facultad de Ciencias Bioquimicas y Farmaceuticas, Universidad Nacional de Rosario and Instituto de Quimica Rosario (IQUIR-CONICET), Suipacha 531, Rosario S2002LRK (Argentina)], E-mail: aolivier@fbioyf.unr.edu.ar; Pagani, Ariana P. [Departamento de Quimica Analitica, Facultad de Ciencias Bioquimicas y Farmaceuticas, Universidad Nacional de Rosario and Instituto de Quimica Rosario (IQUIR-CONICET), Suipacha 531, Rosario S2002LRK (Argentina)

2008-04-28

Multivariate curve resolution coupled to alternating least-squares (MCR-ALS) has been employed to model kinetic-spectroscopic second-order data, with focus on the achievement of the important second-order advantage, under conditions of extreme spectral overlapping among sample components. A series of simulated examples shows that MCR-ALS can conveniently handle the studied analytical problem unlike other second-order multivariate calibration algorithms, provided matrix augmentation is implemented in the spectral mode instead of in the usual kinetic mode. The approach has also been applied to three experimental examples, which involve the determination of: (1) the antiparkinsonian carbidopa (analyte) in the presence of levodopa as a potential interferent, both reacting with cerium (IV) to produce the fluorescent species cerium (III) with different kinetics; (2) Fe(II) (analyte) in the presence of the interferent Zn(II), both catalyzing the oxidation of methyl orange with potassium bromate; and (3) tartrazine (analyte) in the presence of the interferent brilliant blue, both oxidized with potassium bromate, with the interferent leading to a product with an absorption spectrum very similar to tartrazine. The results indicate good analytical performance towards the analytes, despite the intense spectral overlapping and the presence of unexpected constituents in the test samples.

Classification of lung sounds using higher-order statistics: A divide-and-conquer approach.

Science.gov (United States)

Naves, Raphael; Barbosa, Bruno H G; Ferreira, Danton D

2016-06-01

Lung sound auscultation is one of the most commonly used methods to evaluate respiratory diseases. However, the effectiveness of this method depends on the physician's training. If the physician does not have the proper training, he/she will be unable to distinguish between normal and abnormal sounds generated by the human body. Thus, the aim of this study was to implement a pattern recognition system to classify lung sounds. We used a dataset composed of five types of lung sounds: normal, coarse crackle, fine crackle, monophonic and polyphonic wheezes. We used higher-order statistics (HOS) to extract features (second-, third- and fourth-order cumulants), Genetic Algorithms (GA) and Fisher's Discriminant Ratio (FDR) to reduce dimensionality, and k-Nearest Neighbors and Naive Bayes classifiers to recognize the lung sound events in a tree-based system. We used the cross-validation procedure to analyze the classifiers performance and the Tukey's Honestly Significant Difference criterion to compare the results. Our results showed that the Genetic Algorithms outperformed the Fisher's Discriminant Ratio for feature selection. Moreover, each lung class had a different signature pattern according to their cumulants showing that HOS is a promising feature extraction tool for lung sounds. Besides, the proposed divide-and-conquer approach can accurately classify different types of lung sounds. The classification accuracy obtained by the best tree-based classifier was 98.1% for classification accuracy on training, and 94.6% for validation data. The proposed approach achieved good results even using only one feature extraction tool (higher-order statistics). Additionally, the implementation of the proposed classifier in an embedded system is feasible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Removal of impulse noise clusters from color images with local order statistics

Science.gov (United States)

Ruchay, Alexey; Kober, Vitaly

2017-09-01

This paper proposes a novel algorithm for restoring images corrupted with clusters of impulse noise. The noise clusters often occur when the probability of impulse noise is very high. The proposed noise removal algorithm consists of detection of bulky impulse noise in three color channels with local order statistics followed by removal of the detected clusters by means of vector median filtering. With the help of computer simulation we show that the proposed algorithm is able to effectively remove clustered impulse noise. The performance of the proposed algorithm is compared in terms of image restoration metrics with that of common successful algorithms.

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

Advances in modeling fuel rod behavior and accumulations of adequate experimental data have made possible the introduction of quantitative methods to estimate the uncertainty of predictions made with best-estimate fuel rod codes. The uncertainty range of the input variables is characterized by a truncated distribution which is typically a normal, lognormal, or uniform distribution. While the distribution for fabrication parameters is defined to cover the design or fabrication tolerances, the distribution of modeling parameters is inferred from the experimental database consisting of separate effects tests and global tests. The final step of the methodology uses a Monte Carlo type of random sampling of all relevant input variables and performs best-estimate code calculations to propagate these uncertainties in order to evaluate the uncertainty range of outputs of interest for design analysis, such as internal rod pressure and fuel centerline temperature. The statistical method underlying this Monte Carlo sampling is non-parametric order statistics, which is perfectly suited to evaluate quantiles of populations with unknown distribution. The application of this method is straightforward in the case of one single fuel rod, when a 95/95 statement is applicable: 'with a probability of 95% and confidence level of 95% the values of output of interest are below a certain value'. Therefore, the 0.95-quantile is estimated for the distribution of all possible values of one fuel rod with a statistical confidence of 95%. On the other hand, a more elaborate procedure is required if all the fuel rods in the core are being analyzed. In this case, the aim is to evaluate the following global statement: with 95% confidence level, the expected number of fuel rods which are not exceeding a certain value is all the fuel rods in the core except only a few fuel rods. In both cases, the thresholds determined by the analysis should be below the safety acceptable design limit. An indirect

A study of outliers in statistical distributions of mechanical properties of structural steels

International Nuclear Information System (INIS)

Oefverbeck, P.; Oestberg, G.

1977-01-01

The safety against failure of pressure vessels can be assessed by statistical methods, so-called probabilistic fracture mechanics. The data base for such estimations is admittedly rather meagre, making it necessary to assume certain conventional statistical distributions. Since the failure rates arrived at are low, for nuclear vessels of the order of 10 - to 10 - per year, the extremes of the variables involved, among other things the mechanical properties of the steel used, are of particular interest. A question sometimes raised is whether outliers, or values exceeding the extremes in the assumed distributions, might occur. In order to explore this possibility a study has been made of strength values of three qualities of structural steels, available in samples of up to about 12,000. Statistical evaluation of these samples with respect to outliers, using standard methods for this purpose, revealed the presence of such outliers in most cases, with a frequency of occurrence of, typically, a few values per thousand, estimated by the methods described. Obviously, statistical analysis alone cannot be expected to shed any light on the causes of outliers. Thus, the interpretation of these results with respect to their implication for the probabilistic estimation of the integrety of pressure vessels must await further studies of a similar nature in which the test specimens corresponding to outliers can be recovered and examined metallographically. For the moment the results should be regarded only as a factor to be considered in discussions of the safety of pressure vessels. (author)

On the extreme value statistics of normal random matrices and 2D Coulomb gases: Universality and finite N corrections

Science.gov (United States)

Ebrahimi, R.; Zohren, S.

2018-03-01

In this paper we extend the orthogonal polynomials approach for extreme value calculations of Hermitian random matrices, developed by Nadal and Majumdar (J. Stat. Mech. P04001 arXiv:1102.0738), to normal random matrices and 2D Coulomb gases in general. Firstly, we show that this approach provides an alternative derivation of results in the literature. More precisely, we show convergence of the rescaled eigenvalue with largest modulus of a normal Gaussian ensemble to a Gumbel distribution, as well as universality for an arbitrary radially symmetric potential. Secondly, it is shown that this approach can be generalised to obtain convergence of the eigenvalue with smallest modulus and its universality for ring distributions. Most interestingly, the here presented techniques are used to compute all slowly varying finite N correction of the above distributions, which is important for practical applications, given the slow convergence. Another interesting aspect of this work is the fact that we can use standard techniques from Hermitian random matrices to obtain the extreme value statistics of non-Hermitian random matrices resembling the large N expansion used in context of the double scaling limit of Hermitian matrix models in string theory.

Fraternal Birth Order and Extreme Right-Handedness as Predictors of Sexual Orientation and Gender Nonconformity in Men.

Science.gov (United States)

Kishida, Mariana; Rahman, Qazi

2015-07-01

The present study explored whether there were relationships between number of older brothers, handedness, recalled childhood gender nonconformity (CGN), and sexual orientation in men. We used data from previous British studies conducted in our laboratory (N = 1,011 heterosexual men and 921 gay men). These men had completed measures of demographic variables, number and sex of siblings, CGN, and the Edinburgh Handedness Inventory. The results did not replicate the fraternal birth order effect. However, gay men had fewer "other siblings" than heterosexual men (even after controlling for the stopping-rule and family size). In a sub-sample (425 gay men and 478 heterosexual men) with data available on both sibling sex composition and handedness scores, gay men were found to show a significantly greater likelihood of extreme right-handedness and non-right-handedness compared to heterosexual men. There were no significant effects of sibling sex composition in this sub-sample. In a further sub-sample (N = 487) with data available on sibling sex composition, handedness, and CGN, we found that men with feminine scores on CGN were more extremely right-handed and had fewer other-siblings compared to masculine scoring men. Mediation analysis revealed that handedness was associated with sexual orientation directly and also indirectly through the mediating factor of CGN. We were unable to replicate the fraternal birth order effect in our archived dataset but there was evidence for a relationship among handedness, sexual orientation, and CGN. These data help narrow down the number of possible neurodevelopmental pathways leading to variations in male sexual orientation.

Higher order statistical moment application for solar PV potential analysis

Science.gov (United States)

Basri, Mohd Juhari Mat; Abdullah, Samizee; Azrulhisham, Engku Ahmad; Harun, Khairulezuan

2016-10-01

Solar photovoltaic energy could be as alternative energy to fossil fuel, which is depleting and posing a global warming problem. However, this renewable energy is so variable and intermittent to be relied on. Therefore the knowledge of energy potential is very important for any site to build this solar photovoltaic power generation system. Here, the application of higher order statistical moment model is being analyzed using data collected from 5MW grid-connected photovoltaic system. Due to the dynamic changes of skewness and kurtosis of AC power and solar irradiance distributions of the solar farm, Pearson system where the probability distribution is calculated by matching their theoretical moments with that of the empirical moments of a distribution could be suitable for this purpose. On the advantage of the Pearson system in MATLAB, a software programming has been developed to help in data processing for distribution fitting and potential analysis for future projection of amount of AC power and solar irradiance availability.

Temporal and spatial scaling impacts on extreme precipitation

Science.gov (United States)

Eggert, B.; Berg, P.; Haerter, J. O.; Jacob, D.; Moseley, C.

2015-01-01

Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space-time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.

Evaluation and projection of daily temperature percentiles from statistical and dynamical downscaling methods

Directory of Open Access Journals (Sweden)

A. Casanueva

2013-08-01

Full Text Available The study of extreme events has become of great interest in recent years due to their direct impact on society. Extremes are usually evaluated by using extreme indicators, based on order statistics on the tail of the probability distribution function (typically percentiles. In this study, we focus on the tail of the distribution of daily maximum and minimum temperatures. For this purpose, we analyse high (95th and low (5th percentiles in daily maximum and minimum temperatures on the Iberian Peninsula, respectively, derived from different downscaling methods (statistical and dynamical. First, we analyse the performance of reanalysis-driven downscaling methods in present climate conditions. The comparison among the different methods is performed in terms of the bias of seasonal percentiles, considering as observations the public gridded data sets E-OBS and Spain02, and obtaining an estimation of both the mean and spatial percentile errors. Secondly, we analyse the increments of future percentile projections under the SRES A1B scenario and compare them with those corresponding to the mean temperature, showing that their relative importance depends on the method, and stressing the need to consider an ensemble of methodologies.

Expected impacts of climate change on extreme climate events

International Nuclear Information System (INIS)

Planton, S.; Deque, M.; Chauvin, F.; Terray, L.

2008-01-01

An overview of the expected change of climate extremes during this century due to greenhouse gases and aerosol anthropogenic emissions is presented. The most commonly used methodologies rely on the dynamical or statistical down-scaling of climate projections, performed with coupled atmosphere-ocean general circulation models. Either of dynamical or of statistical type, down-scaling methods present strengths and weaknesses, but neither their validation on present climate conditions, nor their potential ability to project the impact of climate change on extreme event statistics allows one to give a specific advantage to one of the two types. The results synthesized in the last IPCC report and more recent studies underline a convergence for a very likely increase in heat wave episodes over land surfaces, linked to the mean warming and the increase in temperature variability. In addition, the number of days of frost should decrease and the growing season length should increase. The projected increase in heavy precipitation events appears also as very likely over most areas and also seems linked to a change in the shape of the precipitation intensity distribution. The global trends for drought duration are less consistent between models and down-scaling methodologies, due to their regional variability. The change of wind-related extremes is also regionally dependent, and associated to a poleward displacement of the mid-latitude storm tracks. The specific study of extreme events over France reveals the high sensitivity of some statistics of climate extremes at the decadal time scale as a consequence of regional climate internal variability. (authors)

Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

DEFF Research Database (Denmark)

Sunyer Pinya, Maria Antonia; Hundecha, Y.; Lawrence, D.

2015-01-01

Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models......), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation...... that at least 30% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided...

Risk assessment of precipitation extremes in northern Xinjiang, China

Science.gov (United States)

Yang, Jun; Pei, Ying; Zhang, Yanwei; Ge, Quansheng

2018-05-01

This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity-humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity-humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites' 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required.

Temperature extremes in Europe: mechanisms and responses to climatic change

International Nuclear Information System (INIS)

Cattiaux, Julien

2010-01-01

Europe witnessed a spate of record-breaking warm seasons during the 2000's. As illustrated by the devastating heat-wave of the summer 2003, these episodes induced strong societal and environmental impacts. Such occurrence of exceptional events over a relatively short time period raised up many questionings in the present context of climate change. In particular, can recent temperature extremes be considered as 'previews' of future climate conditions? Do they result from an increasing temperature variability? These questions constitute the main motivations of this thesis. Thus, our work aims to contribute to the understanding of physical mechanisms responsible for seasonal temperature extremes in Europe, in order to anticipate their future statistical characteristics. Involved processes are assessed by both statistical data-analysis of observations and climate projections and regional modeling experiments. First we show that while the inter-annual European temperature variability appears driven by disturbances in the North-Atlantic dynamics, the recent warming is likely to be dissociated with potential circulation changes. This inconsistency climaxes during the exceptionally mild autumn of 2006, whose temperature anomaly is only half explained by the atmospheric flow. Recent warm surface conditions in the North-Atlantic ocean seem to substantially contribute to the European warming in autumn-winter, through the establishment of advective and radiative processes. In spring-summer, since both advection by the westerlies and Atlantic warming are reduced, more local processes appear predominant (e.g. soil moisture, clouds, aerosols). Then the issue of future evolution of the relationship between North-Atlantic dynamics and European temperatures is addressed, based on climate projections of the International Panel on Climate Change. Multi-model analysis, using both flow-analogues and weather regimes methods, show that the inconsistency noticed over recent decades is

Changes in observed climate extremes in global urban areas

International Nuclear Information System (INIS)

Mishra, Vimal; Ganguly, Auroop R; Nijssen, Bart; Lettenmaier, Dennis P

2015-01-01

Climate extremes have profound implications for urban infrastructure and human society, but studies of observed changes in climate extremes over the global urban areas are few, even though more than half of the global population now resides in urban areas. Here, using observed station data for 217 urban areas across the globe, we show that these urban areas have experienced significant increases (p-value <0.05) in the number of heat waves during the period 1973–2012, while the frequency of cold waves has declined. Almost half of the urban areas experienced significant increases in the number of extreme hot days, while almost 2/3 showed significant increases in the frequency of extreme hot nights. Extreme windy days declined substantially during the last four decades with statistically significant declines in about 60% in the urban areas. Significant increases (p-value <0.05) in the frequency of daily precipitation extremes and in annual maximum precipitation occurred at smaller fractions (17 and 10% respectively) of the total urban areas, with about half as many urban areas showing statistically significant downtrends as uptrends. Changes in temperature and wind extremes, estimated as the result of a 40 year linear trend, differed for urban and non-urban pairs, while changes in indices of extreme precipitation showed no clear differentiation for urban and selected non-urban stations. (letter)

High-order Composite Likelihood Inference for Max-Stable Distributions and Processes

KAUST Repository

Castruccio, Stefano; Huser, Raphaë l; Genton, Marc G.

2015-01-01

In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of locations is a very challenging problem in computational statistics, and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely-used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.

High-order Composite Likelihood Inference for Max-Stable Distributions and Processes

KAUST Repository

Castruccio, Stefano

2015-09-29

In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of locations is a very challenging problem in computational statistics, and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely-used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.

Extreme wind conditions for a Danish offshore site

DEFF Research Database (Denmark)

Hansen, Kurt S.

2000-01-01

This paper presents an analysis of extreme wind speed gust values measured at a shallow water offshore site and at a coastal onshore site in Denmark. An estimate of 50-year extreme values has been evaluated using a new statistical method. In addition a mean gust shape is determined, based on a la...

An MGF-based unified framework to determine the joint statistics of partial sums of ordered i.n.d. random variables

KAUST Repository

Nam, Sungsik

2014-08-01

The joint statistics of partial sums of ordered random variables (RVs) are often needed for the accurate performance characterization of a wide variety of wireless communication systems. A unified analytical framework to determine the joint statistics of partial sums of ordered independent and identically distributed (i.i.d.) random variables was recently presented. However, the identical distribution assumption may not be valid in several real-world applications. With this motivation in mind, we consider in this paper the more general case in which the random variables are independent but not necessarily identically distributed (i.n.d.). More specifically, we extend the previous analysis and introduce a new more general unified analytical framework to determine the joint statistics of partial sums of ordered i.n.d. RVs. Our mathematical formalism is illustrated with an application on the exact performance analysis of the capture probability of generalized selection combining (GSC)-based RAKE receivers operating over frequency-selective fading channels with a non-uniform power delay profile. © 1991-2012 IEEE.

Extremes in nature

CERN Document Server

Salvadori, Gianfausto; Kottegoda, Nathabandu T

2007-01-01

This book is about the theoretical and practical aspects of the statistics of Extreme Events in Nature. Most importantly, this is the first text in which Copulas are introduced and used in Geophysics. Several topics are fully original, and show how standard models and calculations can be improved by exploiting the opportunities offered by Copulas. In addition, new quantities useful for design and risk assessment are introduced.

Measures of serial extremal dependence and their estimation

DEFF Research Database (Denmark)

Davis, Richard A.; Mikosch, Thomas Valentin; Zhao, Yuwei

2013-01-01

extremal dependence is typically characterized by clusters of exceedances of high thresholds in the series. We start by discussing the notion of extremal index of a univariate sequence, i.e. the reciprocal of the expected cluster size, which has attracted major attention in the extremal value literature...... has attracted attention for modeling and statistical purposes. We apply the extremogram to max-stable processes. Finally, we discuss estimation of the extremogram both in the time and frequency domains....

Official Statistics and Statistics Education: Bridging the Gap

Directory of Open Access Journals (Sweden)

Gal Iddo

2017-03-01

Full Text Available This article aims to challenge official statistics providers and statistics educators to ponder on how to help non-specialist adult users of statistics develop those aspects of statistical literacy that pertain to official statistics. We first document the gap in the literature in terms of the conceptual basis and educational materials needed for such an undertaking. We then review skills and competencies that may help adults to make sense of statistical information in areas of importance to society. Based on this review, we identify six elements related to official statistics about which non-specialist adult users should possess knowledge in order to be considered literate in official statistics: (1 the system of official statistics and its work principles; (2 the nature of statistics about society; (3 indicators; (4 statistical techniques and big ideas; (5 research methods and data sources; and (6 awareness and skills for citizens’ access to statistical reports. Based on this ad hoc typology, we discuss directions that official statistics providers, in cooperation with statistics educators, could take in order to (1 advance the conceptualization of skills needed to understand official statistics, and (2 expand educational activities and services, specifically by developing a collaborative digital textbook and a modular online course, to improve public capacity for understanding of official statistics.

Tukey max-stable processes for spatial extremes

KAUST Repository

Xu, Ganggang

2016-09-21

We propose a new type of max-stable process that we call the Tukey max-stable process for spatial extremes. It brings additional flexibility to modeling dependence structures among spatial extremes. The statistical properties of the Tukey max-stable process are demonstrated theoretically and numerically. Simulation studies and an application to Swiss rainfall data indicate the effectiveness of the proposed process. © 2016 Elsevier B.V.

Danish extreme wind atlas: Background and methods for a WAsP engineering option

Energy Technology Data Exchange (ETDEWEB)

Rathmann, O; Kristensen, L; Mann, J [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark); Hansen, S O [Svend Ole Hansen ApS, Copenhagen (Denmark)

1999-03-01

Extreme wind statistics is necessary design information when establishing wind farms and erecting bridges, buildings and other structures in the open air. Normal mean wind statistics in terms of directional and speed distribution may be estimated by wind atlas methods and are used to estimate e.g. annual energy output for wind turbines. It is the purpose of the present work to extend the wind atlas method to also include the local extreme wind statistics so that an extreme value as e.g. the 50-year wind can be estimated at locations of interest. Together with turbulence estimates such information is important regarding the necessary strength of wind turbines or structures to withstand high wind loads. In the `WAsP Engineering` computer program a flow model, which includes a model for the dynamic roughness of water surfaces, is used to realise such an extended wind atlas method. With basis in an extended wind atlas, also containing extreme wind statistics, this allows the program to estimate extreme winds in addition to mean winds and turbulence intensities at specified positions and heights. (au) EFP-97. 15 refs.

Patterns and singular features of extreme fluctuational paths of a periodically driven system

International Nuclear Information System (INIS)

Chen, Zhen; Liu, Xianbin

2016-01-01

Large fluctuations of an overdamped periodically driven oscillating system are investigated theoretically and numerically in the limit of weak noise. Optimal paths fluctuating to certain point are given by statistical analysis using the concept of prehistory probability distribution. The validity of statistical results is verified by solutions of boundary value problem. Optimal paths are found to change topologically when terminating points lie at opposite side of a switching line. Patterns of extreme paths are plotted through a proper parameterization of Lagrangian manifold having complicated structures. Several extreme paths to the same point are obtained by multiple solutions of boundary value solutions. Actions along various extreme paths are calculated and associated analysis is performed in relation to the singular features of the patterns. - Highlights: • Both extreme and optimal paths are obtained by various methods. • Boundary value problems are solved to ensure the validity of statistical results. • Topological structure of Lagrangian manifold is considered. • Singularities of the pattern of extreme paths are studied.

Adaptation to climate extremes: Experiences in the agricultural sector

International Nuclear Information System (INIS)

Ball, M.; Dowlatabadi, H.

1994-01-01

Various social and economic systems are at risk from variability in weather conditions. A realization of this fact has prompted endogenous adaptations to cope with weather variability. Climate change may overwhelm existing adaptive strategies. These systems would experience this change from the secular trends in first-order and higher order statistics of climate parameters (e.g., mean biotemperature, intensity, and inter-arrival times of extreme events). Historically, different human activities have formally or informally incorporated adaptation to climate conditions. Activities such as agriculture are influenced strongly by weather, yet through a variety of mechanisms, impacts are ameliorated. Taking agriculture as an example of a central and substantive system, the authors' study presents response strategies of oranges production -- a crop currently affected greatly by weather conditions. Understanding the adaptation mechanisms used today can be used to examine the cost and effectiveness of adaptive actions to future climate change

Directional analysis of extreme winds under mixed climate conditions

CSIR Research Space (South Africa)

Kruger, A

2013-07-01

Full Text Available Directional statistics provide design engineers with the opportunity to realise considerable cost savings, but these are not yet provided for in the South African standard for wind loading. The development of the directional statistics of extreme...

Statistics of the largest sunspot and facular areas per solar cycle

International Nuclear Information System (INIS)

Willis, D.M.; Kabasakal Tulunay, Y.

1979-01-01

The statistics of extreme values is used to investigate the statistical properties of the largest areas sunspots and photospheric faculae per solar cycle. The largest values of the synodic-solar-rotation mean areas of umbrae, whole spots and faculae, which have been recorded for nine solar cycles, are each shown to comply with the general form of the extreme value probability function. Empirical expressions are derived for the three extreme value populations from which the characteristic statistical parameters, namely the mode, median, mean and standard deviation, can be calculated for each population. These three extreme value populations are also used to find the expected ranges of the extreme areas in a group of solar cycles as a function of the number of cycles in the group. The extreme areas of umbrae and whole spots have a dispersion comparable to that found by Siscoe for the extreme values of sunspot number, whereas the extreme areas of faculae have a smaller dispersion which is comparable to that found by Siscoe for the largest geomagnetic storm per solar cycle. The expected range of the largest sunspot area per solar cycle for a group of one hundred cycles appears to be inconsistent with the existence of the prolonged periods of sunspot minima that have been inferred from the historical information on solar variability. This inconsistency supports the contention that there are temporal changes of solar-cycle statistics during protracted periods of sunspot minima (or maxima). Indeed, without such temporal changes, photospheric faculae should have been continually observable throughout the lifetime of the Sun. (orig.)

A comparison of observed extreme water levels at the German Bight elaborated through an extreme value analysis (EVA) with extremes derived from a regionally coupled ocean-atmospheric climate model (MPI-OM)

Science.gov (United States)

Möller, Jens; Heinrich, Hartmut

2017-04-01

As a consequence of climate change atmospheric and oceanographic extremes and their potential impacts on coastal regions are of growing concern for governmental authorities responsible for the transportation infrastructure. Highest risks for shipping as well as for rail and road traffic originate from combined effects of extremes of storm surges and heavy rainfall which sometimes lead to insufficient dewatering of inland waterways. The German Ministry of Transport and digital Infrastructure therefore has tasked its Network of Experts to investigate the possible evolutions of extreme threats for low lands and especially for Kiel Canal, which is an important shortcut for shipping between the North and Baltic Seas. In this study we present results of a comparison of an Extreme Value Analysis (EVA) carried out on gauge observations and values derived from a coupled Regional Ocean-Atmosphere Climate Model (MPI-OM). High water levels at the coasts of the North and Baltic Seas are one of the most important hazards which increase the risk of flooding of the low-lying land and prevents such areas from an adequate dewatering. In this study changes in the intensity (magnitude of the extremes) and duration of extreme water levels (above a selected threshold) are investigated for several gauge stations with data partly reaching back to 1843. Different methods are used for the extreme value statistics, (1) a stationary general Pareto distribution (GPD) model as well as (2) an instationary statistical model for better reproduction of the impact of climate change. Most gauge stations show an increase of the mean water level of about 1-2 mm/year, with a stronger increase of the highest water levels and a decrease (or lower increase) of the lowest water levels. Also, the duration of possible dewatering time intervals for the Kiel-Canal was analysed. The results for the historical gauge station observations are compared to the statistics of modelled water levels from the coupled

Bridging Centrality and Extremity : Refining Empirical Data Depth using Extreme Value Statistics

NARCIS (Netherlands)

Einmahl, J.H.J.; Li, Jun; Liu, Regina

2015-01-01

Abstract: Data depth measures the centrality of a point with respect to a given distribution or data cloud. It provides a natural center-outward ordering of multivariate data points and yields a systematic nonparametric multivariate analysis scheme. In particular, the halfspace depth is shown to

Modulation of extreme temperatures in Europe under extreme values of the North Atlantic Oscillation Index.

Science.gov (United States)

Beniston, Martin

2018-03-10

This paper reports on the influence that extreme values in the tails of the North Atlantic Oscillation (NAO) Index probability density function (PDF) can exert on temperatures in Europe. When the NAO Index enters into its lowest (10% quantile or less) and highest (90% quantile or higher) modes, European temperatures often exhibit large negative or positive departures from their mean values, respectively. Analyses of the joint quantiles of the Index and temperatures (i.e., the simultaneous exceedance of particular quantile thresholds by the two variables) show that temperatures enter into the upper or lower tails of their PDF when the NAO Index also enters into its extreme tails, more often that could be expected from random statistics. Studies of this nature help further our understanding of the manner by which mechanisms of decadal-scale climate variability can influence extremes of temperature-and thus perhaps improve the forecasting of extreme temperatures in weather and climate models. © 2018 New York Academy of Sciences.

On Extreme Value Statistics: maximum likelihood; portfolio optimization; extremal rainfall; internet auctions

NARCIS (Netherlands)

C. Zhou (Chen)

2008-01-01

textabstractIn the 18th century, statisticians sometimes worked as consultants to gamblers. In order to answer questions like "If a fair coin is flipped 100 times, what is the probability of getting 60 or more heads?", Abraham de Moivre discovered the so-called "normal curve". Independently,

Bridging centrality and extremity : Refining empirical data depth using extreme value statistics

NARCIS (Netherlands)

Einmahl, John; Li, Jun; R.Y., Liu

2015-01-01

Data depth measures the centrality of a point with respect to a given distribution or data cloud. It provides a natural center-outward ordering of multivariate data points and yields a systematic nonparametric multivariate analysis scheme. In particular, the halfspace depth is shown to have many

Variability of extreme wet events over Malawi

Directory of Open Access Journals (Sweden)

Libanda Brigadier

2017-01-01

Full Text Available Adverse effects of extreme wet events are well documented by several studies around the world. These effects are exacerbated in developing countries like Malawi that have insufficient risk reduction strategies and capacity to cope with extreme wet weather. Ardent monitoring of the variability of extreme wet events over Malawi is therefore imperative. The use of the Expert Team on Climate Change Detection and Indices (ETCCDI has been recommended by many studies as an effective way of quantifying extreme wet events. In this study, ETCCDI indices were used to examine the number of heavy, very heavy, and extremely heavy rainfall days; daily and five-day maximum rainfall; very wet and extremely wet days; annual wet days and simple daily intensity. The Standard Normal Homogeneity Test (SNHT was employed at 5% significance level before any statistical test was done. Trend analysis was done using the nonparametric Mann-Kendall statistical test. All stations were found to be homogeneous apart from Mimosa. Trend results show high temporal and spatial variability with the only significant results being: increase in daily maximum rainfall (Rx1day over Karonga and Bvumbwe, increase in five-day maximum rainfall (Rx5day over Bvumbwe. Mzimba and Chileka recorded a significant decrease in very wet days (R95p while a significant increase was observed over Thyolo. Chileka was the only station which observed a significant trend (decrease in extremely wet rainfall (R99p. Mzimba was the only station that reported a significant trend (decrease in annual wet-day rainfall total (PRCPTOT and Thyolo was the only station that reported a significant trend (increase in simple daily intensity (SDII. Furthermore, the findings of this study revealed that, during wet years, Malawi is characterised by an anomalous convergence of strong south-easterly and north-easterly winds. This convergence is the main rain bringing mechanism to Malawi.

Statistical thermodynamics of long straight rigid rods on triangular lattices: nematic order and adsorption thermodynamic functions.

Science.gov (United States)

Matoz-Fernandez, D A; Linares, D H; Ramirez-Pastor, A J

2012-09-04

The statistical thermodynamics of straight rigid rods of length k on triangular lattices was developed on a generalization in the spirit of the lattice-gas model and the classical Guggenheim-DiMarzio approximation. In this scheme, the Helmholtz free energy and its derivatives were written in terms of the order parameter, δ, which characterizes the nematic phase occurring in the system at intermediate densities. Then, using the principle of minimum free energy with δ as a parameter, the main adsorption properties were calculated. Comparisons with Monte Carlo simulations and experimental data were performed in order to evaluate the outcome and limitations of the theoretical model.

New advances in statistical modeling and applications

CERN Document Server

Santos, Rui; Oliveira, Maria; Paulino, Carlos

2014-01-01

This volume presents selected papers from the XIXth Congress of the Portuguese Statistical Society, held in the town of Nazaré, Portugal, from September 28 to October 1, 2011. All contributions were selected after a thorough peer-review process. It covers a broad range of papers in the areas of statistical science, probability and stochastic processes, extremes and statistical applications.

Seasonal temperature extremes in Potsdam

Science.gov (United States)

Kundzewicz, Zbigniew; Huang, Shaochun

2010-12-01

The awareness of global warming is well established and results from the observations made on thousands of stations. This paper complements the large-scale results by examining a long time-series of high-quality temperature data from the Secular Meteorological Station in Potsdam, where observation records over the last 117 years, i.e., from January 1893 are available. Tendencies of change in seasonal temperature-related climate extremes are demonstrated. "Cold" extremes have become less frequent and less severe than in the past, while "warm" extremes have become more frequent and more severe. Moreover, the interval of the occurrence of frost has been decreasing, while the interval of the occurrence of hot days has been increasing. However, many changes are not statistically significant, since the variability of temperature indices at the Potsdam station has been very strong.

Magnetic-Field-Assisted Assembly of Ordered Multifunctional Ceramic Nanocomposites for Extreme Environments

Science.gov (United States)

2016-04-01

SUBJECT TERMS carbon nanotubes, composite, electromagnetic shielding , extreme environments, magnetism, fibers, woven composite, boron nitride...The samples were sealed in glass vial and exposed to the magnetic field immediately after deposition prior to crystallization of PEG that allowed

Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

Science.gov (United States)

Qi, Di

Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are

Contribution to the study of the dependence in the limit between various statistics of a sample; Contribution a l'etude des liaisons limites entre differentes statistiques d'un echantillon

Energy Technology Data Exchange (ETDEWEB)

Rosengard, A [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1966-02-01

With a view to the investigation of the dependence in the limit between some statistics, we give general definitions of the independence in the limit and some of their properties are investigated. We then give some necessary and sufficient conditions for the independence in the limit between sample mean and orders statistics, in particular quantities and extreme values. For example, we show that, for bounded variance laws, the sample mean and orders statistics, in particular quantities and extreme values. For example, we show that, for bounded variance laws, the sample mean tends to become independent of the extreme values, whereas it is asymptotically dependent on the quantities, with a positive correlation coefficient for which an expression is given. We investigate also the case in which variance is unbounded. (author) [French] Afin d'etudier la liaison limite entre certaines statistiques d'un echantillon, on est amene a donner des definitions generales de l'independance limite, et a en etudier quelques proprietes. On donne ensuite les conditions necessaires et suffisantes pour l'independance limite des statistiques d'ordre, et on etudie la liaison limite entre la moyenne et les statistiques d'ordre, en particulier quantites et valeurs extremes. On montre par exemple, que pour des lois dont la variance est finie, la moyenne tend a devenir independante des valeurs extremes, alors qu'elle est asymptotiquement liee aux quantites, avec un coefficient de correlation positif, dont on donne l'expression. On etudie egalement le cas ou la variance est infinie. (auteur)

Bootstrap and Order Statistics for Quantifying Thermal-Hydraulic Code Uncertainties in the Estimation of Safety Margins

Directory of Open Access Journals (Sweden)

Enrico Zio

2008-01-01

Full Text Available In the present work, the uncertainties affecting the safety margins estimated from thermal-hydraulic code calculations are captured quantitatively by resorting to the order statistics and the bootstrap technique. The proposed framework of analysis is applied to the estimation of the safety margin, with its confidence interval, of the maximum fuel cladding temperature reached during a complete group distribution blockage scenario in a RBMK-1500 nuclear reactor.

Statistics in the medical sciences - the long Germany road to there

Directory of Open Access Journals (Sweden)

Weiß, Christel

2005-06-01

Full Text Available This contribution aims at tracing the development of statistical methods in medical science. Statistical methodology in medical research was first implemented in England in the age of the Enlightenment during the 18th century. As this approach stood in a clear opposition to the conventional medical practice directed in a rather authoritarian manner, this research field had to overcome a lot of difficulties. Nowadays, there is a widespread consensus that medical research is hardly possible without profound knowledge and application of statistical methods. Nevertheless, it took an extremely long time until the end of the 20th century, before this methodology was taken notice of and became appreciated. In order to better understand this long process, a brief summary of the development of statistics beginning from the Ancient Times is presented. It is shown how medical progress evolved parallel to the advancing mathematical understanding. A focus is put on the influence of the latter on medical sciences. Moreover, the special case of Germany in this aspect is analysed.

Statistical evaluation and measuring strategy for extremely small line shifts

International Nuclear Information System (INIS)

Hansen, P.G.

1978-01-01

For a measuring situation limited by counting statistics, but where the level of precision is such that possible systematic errors are a major concern, it is proposed to determine the position of a spectral line from a measured line segment by applying a bias correction to the centre of gravity of the segment. This procedure is statistically highly efficient and not sensitive to small errors in assumptions about the line shape. The counting strategy for an instrument that takes data point by point is also considered. It is shown that an optimum (''two-point'') strategy exists; a scan of the central part of the line is 68% efficient by this standard. (Auth.)

On the statistics of the largest geomagnetic storms per solar cycle

International Nuclear Information System (INIS)

Siscoe, G.L.

1976-01-01

The theory of extreme value statistics is applied to the first, second, and third largest geomagnetic storms in nine solar cycles measured by the average half-daily aa indices compiled by Mayaud. Analytic expressions giving the probability of the extremes per solar cycle as a contour function of storm magnitude are obtained by least squares fitting of the observations to the appropriate theoretical extreme value probability functions. The results are used to obtain the statistical characteristics (mode, median, mean, and standard deviation) for the extreme values. The results are applied to find the expected range of extreme values in a set as a function of the number of solar cycles in the set. We find that the expected range of the largest storm is quite narrow and is larger for the second and third largest storms. The observed range of the extreme half-daily aa index for the nine solar cycles is 354--546 γ. In a set of 100 cycles the range is expanded esentially to 311--680γ, an increase of only 39% in the range. The result supports the argument for a change in solar cycle statistics in the latter part of the Seventeenth Century (the Maunder minimum)

Comparison of past and future Mediterranean high and low extremes of precipitation and river flow projected using different statistical downscaling methods

Directory of Open Access Journals (Sweden)

P. Quintana-Seguí

2011-05-01

Full Text Available The extremes of precipitation and river flow obtained using three different statistical downscaling methods applied to the same regional climate simulation have been compared. The methods compared are the anomaly method, quantile mapping and a weather typing. The hydrological model used in the study is distributed and it is applied to the Mediterranean basins of France. The study shows that both quantile mapping and weather typing methods are able to reproduce the high and low precipitation extremes in the region of interest. The study also shows that when the hydrological model is forced with these downscaled data, there are important differences in the outputs. This shows that the model amplifies the differences and that the downscaling of other atmospheric variables might be very relevant when simulating river discharges. In terms of river flow, the method of the anomalies, which is very simple, performs better than expected. The methods produce qualitatively similar future scenarios of the extremes of river flow. However, quantitatively, there are still significant differences between them for each individual gauging station. According to these scenarios, it is expected that in the middle of the 21st century (2035–2064, the monthly low flows will have diminished almost everywhere in the region of our study by as much as 20 %. Regarding high flows, there will be important increases in the area of the Cévennes, which is already seriously affected by flash-floods. For some gauging stations in this area, the frequency of what was a 10-yr return flood at the end of the 20th century is expected to increase, with such return floods then occurring every two years in the middle of the 21st century. Similarly, the 10-yr return floods at that time are expected to carry 100 % more water than the 10-yr return floods experienced at the end of the 20th century. In the northern part of the Rhône basin, these extremes will be reduced.

GPR Raw-Data Order Statistic Filtering and Split-Spectrum Processing to Detect Moisture

Directory of Open Access Journals (Sweden)

Gokhan Kilic

2014-05-01

Full Text Available Considerable research into the area of bridge health monitoring has been undertaken; however, information is still lacking on the effects of certain defects, such as moisture ingress, on the results of ground penetrating radar (GPR surveying. In this paper, this issue will be addressed by examining the results of a GPR bridge survey, specifically the effect of moisture in the predicted position of the rebars. It was found that moisture ingress alters the radargram to indicate distortion or skewing of the steel reinforcements, when in fact destructive testing was able to confirm that no such distortion or skewing had occurred. Additionally, split-spectrum processing with order statistic filters was utilized to detect moisture ingress from the GPR raw data.

Automatic Assessment of Pathological Voice Quality Using Higher-Order Statistics in the LPC Residual Domain

Directory of Open Access Journals (Sweden)

JiYeoun Lee

2009-01-01

Full Text Available A preprocessing scheme based on linear prediction coefficient (LPC residual is applied to higher-order statistics (HOSs for automatic assessment of an overall pathological voice quality. The normalized skewness and kurtosis are estimated from the LPC residual and show statistically meaningful distributions to characterize the pathological voice quality. 83 voice samples of the sustained vowel /a/ phonation are used in this study and are independently assessed by a speech and language therapist (SALT according to the grade of the severity of dysphonia of GRBAS scale. These are used to train and test classification and regression tree (CART. The best result is obtained using an optima l decision tree implemented by a combination of the normalized skewness and kurtosis, with an accuracy of 92.9%. It is concluded that the method can be used as an assessment tool, providing a valuable aid to the SALT during clinical evaluation of an overall pathological voice quality.

Do climate extreme events foster violent civil conflicts? A coincidence analysis

Science.gov (United States)

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Donner, Reik V.

2014-05-01

Civil conflicts promoted by adverse environmental conditions represent one of the most important potential feedbacks in the global socio-environmental nexus. While the role of climate extremes as a triggering factor is often discussed, no consensus is yet reached about the cause-and-effect relation in the observed data record. Here we present results of a rigorous statistical coincidence analysis based on the Munich Re Inc. extreme events database and the Uppsala conflict data program. We report evidence for statistically significant synchronicity between climate extremes with high economic impact and violent conflicts for various regions, although no coherent global signal emerges from our analysis. Our results indicate the importance of regional vulnerability and might aid to identify hot-spot regions for potential climate-triggered violent social conflicts.

Supernova signatures of neutrino mass ordering

Science.gov (United States)

Scholberg, Kate

2018-01-01

A suite of detectors around the world is poised to measure the flavor-energy-time evolution of the ten-second burst of neutrinos from a core-collapse supernova occurring in the Milky Way or nearby. Next-generation detectors to be built in the next decade will have enhanced flavor sensitivity and statistics. Not only will the observation of this burst allow us to peer inside the dense matter of the extreme event and learn about the collapse processes and the birth of the remnant, but the neutrinos will bring information about neutrino properties themselves. This review surveys some of the physical signatures that the currently-unknown neutrino mass pattern will imprint on the observed neutrino events at Earth, emphasizing the most robust and least model-dependent signatures of mass ordering.

Approximate Forward Difference Equations for the Lower Order Non-Stationary Statistics of Geometrically Non-Linear Systems subject to Random Excitation

DEFF Research Database (Denmark)

Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.

Geometrically non-linear multi-degree-of-freedom (MDOF) systems subject to random excitation are considered. New semi-analytical approximate forward difference equations for the lower order non-stationary statistical moments of the response are derived from the stochastic differential equations...... of motion, and, the accuracy of these equations is numerically investigated. For stationary excitations, the proposed method computes the stationary statistical moments of the response from the solution of non-linear algebraic equations....

Analysis of Low Appropriateness Score Exam Trends in Decision Support-based Radiology Order Entry System.

Science.gov (United States)

Gupta, Supriya; Klein, Kandace; Singh, Anand H; Thrall, James H

2017-05-01

Awareness of imaging utilization increased after implementation of Radiology Order Entry with decision support systems (ROE-DS). Our hypothesis is few exams with low Clinical Appropriateness Score (CAS) on ROE-DS are performed. Clinical indications of exams with CAS less than 3 (9-point scale) were re-reviewed and reports analyzed. Structured Query Language-based query retrieved exams with CAS less than 3 in ROE-DS from January 2007 to December 2011. Reasons provided by physicians for ordering these exams and reports of exams performed were analyzed. For each indication, number of exams ordered and performed was calculated. Statistical significance was assessed using Student's t test and χ 2 analysis (P < .05). From 445,984 exams, 12,615 exams (2.8%) had CAS less than 3, and 7,956 exams (63%) were performed. Reasons for ordering of 12,615 low CAS exams were as follows: Requests by physician specialists without further explanation (4,516 = 35.8%), notation of special clinical circumstances (2,877 = 22.8%), requests by nonphysician staff without further explanation (1,383 = 10.9%), absence of suspected finding on previous modality (1,099 = 8.7%), patient preference (737 = 5.8%), and requests based on radiologists' recommendations (706 = 5.6%). Difference between male and female (male < female) preferences for low CAS exams was statistically significant (P < .01). Imaging outcome was highest for extremity MRI cases (66.7%; P < .01). Less than 3% of exams ordered had low CAS and about two-thirds of these were performed. Most common indication for ordering these exams was physician specialist request based on opinion of medical necessity without specification. Extremity MRI constituted the highest positive findings for low CAS exams performed. Published by Elsevier Inc.

Sea Extremes: Integrated impact assessment in coastal climate adaptation

Science.gov (United States)

Sorensen, Carlo; Knudsen, Per; Broge, Niels; Molgaard, Mads; Andersen, Ole

2016-04-01

We investigate effects of sea level rise and a change in precipitation pattern on coastal flooding hazards. Historic and present in situ and satellite data of water and groundwater levels, precipitation, vertical ground motion, geology, and geotechnical soil properties are combined with flood protection measures, topography, and infrastructure to provide a more complete picture of the water-related impact from climate change at an exposed coastal location. Results show that future sea extremes evaluated from extreme value statistics may, indeed, have a large impact. The integrated effects from future storm surges and other geo- and hydro-parameters need to be considered in order to provide for the best protection and mitigation efforts, however. Based on the results we present and discuss a simple conceptual model setup that can e.g. be used for 'translation' of regional sea level rise evidence and projections to concrete impact measures. This may be used by potentially affected stakeholders -often working in different sectors and across levels of governance, in a common appraisal of the challenges faced ahead. The model may also enter dynamic tools to evaluate local impact as sea level research advances and projections for the future are updated.

A new simple model for composite fading channels: Second order statistics and channel capacity

KAUST Repository

Yilmaz, Ferkan

2010-09-01

In this paper, we introduce the most general composite fading distribution to model the envelope and the power of the received signal in such fading channels as millimeter wave (60 GHz or above) fading channels and free-space optical channels, which we term extended generalized-K (EGK) composite fading distribution. We obtain the second-order statistics of the received signal envelope characterized by the EGK composite fading distribution. Expressions for probability density function, cumulative distribution function, level crossing rate and average fade duration, moments, amount of fading and average capacity are derived. Numerical and computer simulation examples validate the accuracy of the presented mathematical analysis. © 2010 IEEE.

Statistics of extreme events in Chinese stock markets

International Nuclear Information System (INIS)

Wu Gan-Hua; Qiu Lu; Li Xin-Li; Yang Yue; Yang Hui-Jie; Jiang Yan; Stephen Mutua

2014-01-01

We investigate the impact of financial factors on daily volume recurrent time intervals in the developing Chinese stock markets. The tails of probability distribution functions (PDFs) of volume recurrent intervals behave as a power-law, and the scaling exponent decreases with the increase of stock lifetime, which are similar to those in the US stock markets, and they are typical representatives of developed markets. The difference is that the power-law exponent values remain almost the same with the changes of market capitalization, mean volume, and mean trading value, respectively. These findings enrich the results for event statistics for financial markets. (interdisciplinary physics and related areas of science and technology)

Application of extreme value distribution function in the determination of standard meteorological parameters for nuclear power plants

International Nuclear Information System (INIS)

Jiang Haimei; Liu Xinjian; Qiu Lin; Li Fengju

2014-01-01

Based on the meteorological data from weather stations around several domestic nuclear power plants, the statistical results of extreme minimum temperatures, minimum. central pressures of tropical cyclones and some other parameters are calculated using extreme value I distribution function (EV- I), generalized extreme value distribution function (GEV) and generalized Pareto distribution function (GP), respectively. The influence of different distribution functions and parameter solution methods on the statistical results of extreme values is investigated. Results indicate that generalized extreme value function has better applicability than the other two distribution functions in the determination of standard meteorological parameters for nuclear power plants. (authors)

How does public opinion become extreme?

Science.gov (United States)

Ramos, Marlon; Shao, Jia; Reis, Saulo D S; Anteneodo, Celia; Andrade, José S; Havlin, Shlomo; Makse, Hernán A

2015-05-19

We investigate the emergence of extreme opinion trends in society by employing statistical physics modeling and analysis on polls that inquire about a wide range of issues such as religion, economics, politics, abortion, extramarital sex, books, movies, and electoral vote. The surveys lay out a clear indicator of the rise of extreme views. The precursor is a nonlinear relation between the fraction of individuals holding a certain extreme view and the fraction of individuals that includes also moderates, e.g., in politics, those who are "very conservative" versus "moderate to very conservative" ones. We propose an activation model of opinion dynamics with interaction rules based on the existence of individual "stubbornness" that mimics empirical observations. According to our modeling, the onset of nonlinearity can be associated to an abrupt bootstrap-percolation transition with cascades of extreme views through society. Therefore, it represents an early-warning signal to forecast the transition from moderate to extreme views. Moreover, by means of a phase diagram we can classify societies according to the percolative regime they belong to, in terms of critical fractions of extremists and people's ties.

How does public opinion become extreme?

Science.gov (United States)

Ramos, Marlon; Shao, Jia; Reis, Saulo D. S.; Anteneodo, Celia; Andrade, José S.; Havlin, Shlomo; Makse, Hernán A.

2015-05-01

We investigate the emergence of extreme opinion trends in society by employing statistical physics modeling and analysis on polls that inquire about a wide range of issues such as religion, economics, politics, abortion, extramarital sex, books, movies, and electoral vote. The surveys lay out a clear indicator of the rise of extreme views. The precursor is a nonlinear relation between the fraction of individuals holding a certain extreme view and the fraction of individuals that includes also moderates, e.g., in politics, those who are “very conservative” versus “moderate to very conservative” ones. We propose an activation model of opinion dynamics with interaction rules based on the existence of individual “stubbornness” that mimics empirical observations. According to our modeling, the onset of nonlinearity can be associated to an abrupt bootstrap-percolation transition with cascades of extreme views through society. Therefore, it represents an early-warning signal to forecast the transition from moderate to extreme views. Moreover, by means of a phase diagram we can classify societies according to the percolative regime they belong to, in terms of critical fractions of extremists and people’s ties.

Frequency Analysis of High Flow Extremes in the Yingluoxia Watershed in Northwest China

Directory of Open Access Journals (Sweden)

Zhanling Li

2016-05-01

Full Text Available Statistical modeling of hydrological extremes is significant to the construction of hydraulic engineering. This paper, taking the Yingluoxia watershed as the study area, compares the annual maximum (AM series and the peaks over a threshold (POT series in order to study the hydrological extremes, examines the stationarity and independence assumptions for the two series, and discusses the estimations and uncertainties of return levels from the two series using the Generalized Extreme Value (GEV and Generalized Pareto distribution (GPD models. For comparison, the return levels from all threshold excesses with considering the extremal index are also estimated. For the POT series, the threshold is selected by examining the mean excess plot and the stability of the parameter estimates and by using common-sense. The serial correlation is reduced by filtering out a set of dependent threshold excesses. Results show that both series are approximately stationary and independent. The GEV model fits the AM series well and the GPD model fits the POT series well. The estimated return levels are fairly comparable for the AM series, the POT series, and all threshold excesses with considering the extremal index, with the difference being less than 10% for return periods longer than 10 years. The uncertainties of the estimated return levels are the highest for the AM series, and next for the POT series and then for all threshold excesses series in turn.

Incidences des extremes pluviometriques au Benin Impact of ...

African Journals Online (AJOL)

. These data were extracted from the file of ASECNA-Cotonou. In addition, surveys have been conducted to understand the impacts of these extreme rainfalls. The data and information collected was processed using descriptive statistics.

Regional frequency analysis of extreme rainfalls using partial L moments method

Science.gov (United States)

Zakaria, Zahrahtul Amani; Shabri, Ani

2013-07-01

An approach based on regional frequency analysis using L moments and LH moments are revisited in this study. Subsequently, an alternative regional frequency analysis using the partial L moments (PL moments) method is employed, and a new relationship for homogeneity analysis is developed. The results were then compared with those obtained using the method of L moments and LH moments of order two. The Selangor catchment, consisting of 37 sites and located on the west coast of Peninsular Malaysia, is chosen as a case study. PL moments for the generalized extreme value (GEV), generalized logistic (GLO), and generalized Pareto distributions were derived and used to develop the regional frequency analysis procedure. PL moment ratio diagram and Z test were employed in determining the best-fit distribution. Comparison between the three approaches showed that GLO and GEV distributions were identified as the suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation used for performance evaluation shows that the method of PL moments would outperform L and LH moments methods for estimation of large return period events.

Extreme Weather Events and Climate Change Attribution

Energy Technology Data Exchange (ETDEWEB)

Thomas, Katherine [National Academy of Sciences, Washington, DC (United States)

2016-03-31

A report from the National Academies of Sciences, Engineering, and Medicine concludes it is now possible to estimate the influence of climate change on some types of extreme events. The science of extreme event attribution has advanced rapidly in recent years, giving new insight to the ways that human-caused climate change can influence the magnitude or frequency of some extreme weather events. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities. Confidence is strongest in attributing types of extreme events that are influenced by climate change through a well-understood physical mechanism, such as, the more frequent heat waves that are closely connected to human-caused global temperature increases, the report finds. Confidence is lower for other types of events, such as hurricanes, whose relationship to climate change is more complex and less understood at present. For any extreme event, the results of attribution studies hinge on how questions about the event's causes are posed, and on the data, modeling approaches, and statistical tools chosen for the analysis.

Experimental statistics

CERN Document Server

Natrella, Mary Gibbons

1963-01-01

Formulated to assist scientists and engineers engaged in army ordnance research and development programs, this well-known and highly regarded handbook is a ready reference for advanced undergraduate and graduate students as well as for professionals seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Topics include characterizing and comparing the measured performance of a material, product, or process; general considerations in planning experiments; statistical techniques for analyzing extreme-value data; use of transformations

Statistical optics

Science.gov (United States)

Goodman, J. W.

This book is based on the thesis that some training in the area of statistical optics should be included as a standard part of any advanced optics curriculum. Random variables are discussed, taking into account definitions of probability and random variables, distribution functions and density functions, an extension to two or more random variables, statistical averages, transformations of random variables, sums of real random variables, Gaussian random variables, complex-valued random variables, and random phasor sums. Other subjects examined are related to random processes, some first-order properties of light waves, the coherence of optical waves, some problems involving high-order coherence, effects of partial coherence on imaging systems, imaging in the presence of randomly inhomogeneous media, and fundamental limits in photoelectric detection of light. Attention is given to deterministic versus statistical phenomena and models, the Fourier transform, and the fourth-order moment of the spectrum of a detected speckle image.

Early prediction of lung cancer recurrence after stereotactic radiotherapy using second order texture statistics

Science.gov (United States)

Mattonen, Sarah A.; Palma, David A.; Haasbeek, Cornelis J. A.; Senan, Suresh; Ward, Aaron D.

2014-03-01

Benign radiation-induced lung injury is a common finding following stereotactic ablative radiotherapy (SABR) for lung cancer, and is often difficult to differentiate from a recurring tumour due to the ablative doses and highly conformal treatment with SABR. Current approaches to treatment response assessment have shown limited ability to predict recurrence within 6 months of treatment. The purpose of our study was to evaluate the accuracy of second order texture statistics for prediction of eventual recurrence based on computed tomography (CT) images acquired within 6 months of treatment, and compare with the performance of first order appearance and lesion size measures. Consolidative and ground-glass opacity (GGO) regions were manually delineated on post-SABR CT images. Automatic consolidation expansion was also investigated to act as a surrogate for GGO position. The top features for prediction of recurrence were all texture features within the GGO and included energy, entropy, correlation, inertia, and first order texture (standard deviation of density). These predicted recurrence with 2-fold cross validation (CV) accuracies of 70-77% at 2- 5 months post-SABR, with energy, entropy, and first order texture having leave-one-out CV accuracies greater than 80%. Our results also suggest that automatic expansion of the consolidation region could eliminate the need for manual delineation, and produced reproducible results when compared to manually delineated GGO. If validated on a larger data set, this could lead to a clinically useful computer-aided diagnosis system for prediction of recurrence within 6 months of SABR and allow for early salvage therapy for patients with recurrence.

De-trending of wind speed variance based on first-order and second-order statistical moments only

DEFF Research Database (Denmark)

Larsen, Gunner Chr.; Hansen, Kurt Schaldemose

2014-01-01

The lack of efficient methods for de-trending of wind speed resource data may lead to erroneous wind turbine fatigue and ultimate load predictions. The present paper presents two models, which quantify the effect of an assumed linear trend on wind speed standard deviations as based on available...... statistical data only. The first model is a pure time series analysis approach, which quantifies the effect of non-stationary characteristics of ensemble mean wind speeds on the estimated wind speed standard deviations as based on mean wind speed statistics only. This model is applicable to statistics...... of arbitrary types of time series. The second model uses the full set of information and includes thus additionally observed wind speed standard deviations to estimate the effect of ensemble mean non-stationarities on wind speed standard deviations. This model takes advantage of a simple physical relationship...

An MGF-based unified framework to determine the joint statistics of partial sums of ordered i.n.d. random variables

KAUST Repository

Nam, Sungsik; Yang, Hongchuan; Alouini, Mohamed-Slim; Kim, Dongin

2014-01-01

framework to determine the joint statistics of partial sums of ordered i.n.d. RVs. Our mathematical formalism is illustrated with an application on the exact performance analysis of the capture probability of generalized selection combining (GSC)-based RAKE

A Statistical Primer: Understanding Descriptive and Inferential Statistics

OpenAIRE

Gillian Byrne

2007-01-01

As libraries and librarians move more towards evidence‐based decision making, the data being generated in libraries is growing. Understanding the basics of statistical analysis is crucial for evidence‐based practice (EBP), in order to correctly design and analyze researchas well as to evaluate the research of others. This article covers the fundamentals of descriptive and inferential statistics, from hypothesis construction to sampling to common statistical techniques including chi‐square, co...

Using PROGUMBEL to predict extreme external hazards during nuclear power plant construction

International Nuclear Information System (INIS)

Diburg, S.; Hoelscher, N.; Niemann, H.J.; Meiswinkel, R.

2010-01-01

Safety considerations concerning the construction of power plants, supporting structure planning, safety concept and structural design require reliable data on external events, their incidence probability and characteristic parameters. The basis for supporting structure calculations based on probabilistic reliability considerations is the knowledge on the statistical distribution or the incidence frequency of specific phenomena and their characteristic basic variables. The extreme value statistics software PRO GUMBEL is the extended version of the original GUMBEL software used for seismic assessments. The authors describe the features of the software, that covers seismic events, flooding and extreme storms.

On alternative q-Weibull and q-extreme value distributions: Properties and applications

Science.gov (United States)

Zhang, Fode; Ng, Hon Keung Tony; Shi, Yimin

2018-01-01

Tsallis statistics and Tsallis distributions have been attracting a significant amount of research work in recent years. Importantly, the Tsallis statistics, q-distributions have been applied in different disciplines. Yet, a relationship between some existing q-Weibull distributions and q-extreme value distributions that is parallel to the well-established relationship between the conventional Weibull and extreme value distributions through a logarithmic transformation has not be established. In this paper, we proposed an alternative q-Weibull distribution that leads to a q-extreme value distribution via the q-logarithm transformation. Some important properties of the proposed q-Weibull and q-extreme value distributions are studied. Maximum likelihood and least squares estimation methods are used to estimate the parameters of q-Weibull distribution and their performances are investigated through a Monte Carlo simulation study. The methodologies and the usefulness of the proposed distributions are illustrated by fitting the 2014 traffic fatalities data from The National Highway Traffic Safety Administration.

Projecting changes in regional temperature and precipitation extremes in the United States

OpenAIRE

Justin T. Schoof; Scott M. Robeson

2016-01-01

Regional and local climate extremes, and their impacts, result from the multifaceted interplay between large-scale climate forcing, local environmental factors (physiography), and societal vulnerability. In this paper, we review historical and projected changes in temperature and precipitation extremes in the United States, with a focus on strengths and weaknesses of (1) commonly used definitions for extremes such as thresholds and percentiles, (2) statistical approaches to quantifying change...

Capturing spatial and temporal patterns of widespread, extreme flooding across Europe

Science.gov (United States)

Busby, Kathryn; Raven, Emma; Liu, Ye

2013-04-01

Statistical characterisation of physical hazards is an integral part of probabilistic catastrophe models used by the reinsurance industry to estimate losses from large scale events. Extreme flood events are not restricted by country boundaries which poses an issue for reinsurance companies as their exposures often extend beyond them. We discuss challenges and solutions that allow us to appropriately capture the spatial and temporal dependence of extreme hydrological events on a continental-scale, which in turn enables us to generate an industry-standard stochastic event set for estimating financial losses for widespread flooding. By presenting our event set methodology, we focus on explaining how extreme value theory (EVT) and dependence modelling are used to account for short, inconsistent hydrological data from different countries, and how to make appropriate statistical decisions that best characterise the nature of flooding across Europe. The consistency of input data is of vital importance when identifying historical flood patterns. Collating data from numerous sources inherently causes inconsistencies and we demonstrate our robust approach to assessing the data and refining it to compile a single consistent dataset. This dataset is then extrapolated using a parameterised EVT distribution to estimate extremes. Our method then captures the dependence of flood events across countries using an advanced multivariate extreme value model. Throughout, important statistical decisions are explored including: (1) distribution choice; (2) the threshold to apply for extracting extreme data points; (3) a regional analysis; (4) the definition of a flood event, which is often linked with reinsurance industry's hour's clause; and (5) handling of missing values. Finally, having modelled the historical patterns of flooding across Europe, we sample from this model to generate our stochastic event set comprising of thousands of events over thousands of years. We then briefly

State-Space Geometry, Statistical Fluctuations, and Black Holes in String Theory

Directory of Open Access Journals (Sweden)

Stefano Bellucci

2014-01-01

Full Text Available We study the state-space geometry of various extremal and nonextremal black holes in string theory. From the notion of the intrinsic geometry, we offer a state-space perspective to the black hole vacuum fluctuations. For a given black hole entropy, we explicate the intrinsic geometric meaning of the statistical fluctuations, local and global stability conditions, and long range statistical correlations. We provide a set of physical motivations pertaining to the extremal and nonextremal black holes, namely, the meaning of the chemical geometry and physics of correlation. We illustrate the state-space configurations for general charge extremal black holes. In sequel, we extend our analysis for various possible charge and anticharge nonextremal black holes. From the perspective of statistical fluctuation theory, we offer general remarks, future directions, and open issues towards the intrinsic geometric understanding of the vacuum fluctuations and black holes in string theory.

Statistical model with two order parameters for ductile and soft fiber bundles in nanoscience and biomaterials.

Science.gov (United States)

Rinaldi, Antonio

2011-04-01

Traditional fiber bundles models (FBMs) have been an effective tool to understand brittle heterogeneous systems. However, fiber bundles in modern nano- and bioapplications demand a new generation of FBM capturing more complex deformation processes in addition to damage. In the context of loose bundle systems and with reference to time-independent plasticity and soft biomaterials, we formulate a generalized statistical model for ductile fracture and nonlinear elastic problems capable of handling more simultaneous deformation mechanisms by means of two order parameters (as opposed to one). As the first rational FBM for coupled damage problems, it may be the cornerstone for advanced statistical models of heterogeneous systems in nanoscience and materials design, especially to explore hierarchical and bio-inspired concepts in the arena of nanobiotechnology. Applicative examples are provided for illustrative purposes at last, discussing issues in inverse analysis (i.e., nonlinear elastic polymer fiber and ductile Cu submicron bars arrays) and direct design (i.e., strength prediction).

Drought assessment in the Duero basin (Central Spain) by means of multivariate extreme value statistics

Science.gov (United States)

Kallache, M.

2012-04-01

Droughts cause important losses. On the Iberian Peninsula, for example, non-irrigated agriculture and the tourism sector are affected in regular intervals. The goal of this study is the description of droughts and their dependence in the Duero basin in Central Spain. To do so, daily or monthly precipitation data is used. Here cumulative precipitation deficits below a threshold define meteorological droughts. This drought indicator is similar to the commonly used standard precipitation index. However, here the focus lies on the modeling of severe droughts, which is done by applying multivariate extreme value theory (MEVT) to model extreme drought events. Data from several stations are assessed jointly, thus the uncertainty of the results is reduced. Droughts are a complex phenomenon, their severity, spatial extension and duration has to be taken into account. Our approach captures severity and spatial extension. In general we find a high correlation between deficit volumes and drought duration, thus the duration is not explicitely modeled. We apply a MEVT model with asymmetric logistic dependence function, which is capable to model asymptotic dependence and independence (cf. Ramos and Ledford, 2009). To summarize the information on the dependence in the joint tail of the extreme drought events, we utilise the fragility index (Geluk et al., 2007). Results show that droughts also occur frequently in winter. Moreover, it is very common for one site to suffer dry conditions, whilst neighboring areas experience normal or even humid conditions. Interpolation is thus difficult. Bivariate extremal dependence is present in the data. However, most stations are at least asymptotically independent. The according fragility indices are important information for risk calculations. The emerging spatial patterns for bivariate dependence are mostly influenced by topography. When looking at the dependence between more than two stations, it shows that joint extremes can occur more

Visuanimation in statistics

KAUST Repository

Genton, Marc G.

2015-04-14

This paper explores the use of visualization through animations, coined visuanimation, in the field of statistics. In particular, it illustrates the embedding of animations in the paper itself and the storage of larger movies in the online supplemental material. We present results from statistics research projects using a variety of visuanimations, ranging from exploratory data analysis of image data sets to spatio-temporal extreme event modelling; these include a multiscale analysis of classification methods, the study of the effects of a simulated explosive volcanic eruption and an emulation of climate model output. This paper serves as an illustration of visuanimation for future publications in Stat. Copyright © 2015 John Wiley & Sons, Ltd.

Quantifying the consequences of changing hydroclimatic extremes on protection levels for the Rhine

Science.gov (United States)

Sperna Weiland, Frederiek; Hegnauer, Mark; Buiteveld, Hendrik; Lammersen, Rita; van den Boogaard, Henk; Beersma, Jules

2017-04-01

The Dutch method for quantifying the magnitude and frequency of occurrence of discharge extremes in the Rhine basin and the potential influence of climate change hereon are presented. In the Netherlands flood protection design requires estimates of discharge extremes for return periods of 1000 up to 100,000 years. Observed discharge records are too short to derive such extreme return discharges, therefore extreme value assessment is based on very long synthetic discharge time-series generated with the Generator of Rainfall And Discharge Extremes (GRADE). The GRADE instrument consists of (1) a stochastic weather generator based on time series resampling of historical f rainfall and temperature and (2) a hydrological model optimized following the GLUE methodology and (3) a hydrodynamic model to simulate the propagation of flood waves based on the generated hydrological time-series. To assess the potential influence of climate change, the four KNMI'14 climate scenarios are applied. These four scenarios represent a large part of the uncertainty provided by the GCMs used for the IPCC 5th assessment report (the CMIP5 GCM simulations under different climate forcings) and are for this purpose tailored to the Rhine and Meuse river basins. To derive the probability distributions of extreme discharges under climate change the historical synthetic rainfall and temperature series simulated with the weather generator are transformed to the future following the KNMI'14 scenarios. For this transformation the Advanced Delta Change method, which allows that the changes in the extremes differ from those in the means, is used. Subsequently the hydrological model is forced with the historical and future (i.e. transformed) synthetic time-series after which the propagation of the flood waves is simulated with the hydrodynamic model to obtain the extreme discharge statistics both for current and future climate conditions. The study shows that both for 2050 and 2085 increases in discharge

Combining Radar and Daily Precipitation Data to Estimate Meaningful Sub-daily Precipitation Extremes

Science.gov (United States)

Pegram, G. G. S.; Bardossy, A.

2016-12-01

Short duration extreme rainfalls are important for design. The purpose of this presentation is not to improve the day by day estimation of precipitation, but to obtain reasonable statistics for the subdaily extremes at gauge locations. We are interested specifically in daily and sub-daily extreme values of precipitation at gauge locations. We do not employ the common procedure of using time series of control station to determine the missing data values in a target. We are interested in individual rare events, not sequences. The idea is to use radar to disaggregate daily totals to sub-daily amounts. In South Arica, an S-band radar operated relatively continuously at Bethlehem from 1998 to 2003, whose scan at 1.5 km above ground [CAPPI] overlapped a dense (10 km spacing) set of 45 pluviometers recording in the same 6-year period. Using this valuable set of data, we are only interested in rare extremes, therefore small to medium values of rainfall depth were neglected, leaving 12 days of ranked daily maxima in each set per year, whose sum typically comprised about 50% of each annual rainfall total. The method presented here uses radar for disaggregating daily gauge totals in subdaily intervals down to 15 minutes in order to extract the maxima of sub-hourly through to daily rainfall at each of 37 selected radar pixels [1 km square in plan] which contained one of the 45 pluviometers not masked out by the radar foot-print. The pluviometer data were aggregated to daily totals, to act as if they were daily read gauges; their only other task was to help in the cross-validation exercise. The extrema were obtained as quantiles by ordering the 12 daily maxima of each interval per year. The unusual and novel goal was not to obtain the reproduction of the precipitation matching in space and time, but to obtain frequency distributions of the gauge and radar extremes, by matching their ranks, which we found to be stable and meaningful in cross-validation tests. We provide and

Mathematical aspects of assessing extreme events for the safety of nuclear plants

Science.gov (United States)

Potempski, Slawomir; Borysiewicz, Mieczyslaw

2015-04-01

In the paper the review of mathematical methodologies applied for assessing low frequencies of rare natural events like earthquakes, tsunamis, hurricanes or tornadoes, floods (in particular flash floods and surge storms), lightning, solar flares, etc., will be given in the perspective of the safety assessment of nuclear plants. The statistical methods are usually based on the extreme value theory, which deals with the analysis of extreme deviation from the median (or the mean). In this respect application of various mathematical tools can be useful, like: the extreme value theorem of Fisher-Tippett-Gnedenko leading to possible choices of general extreme value distributions, or the Pickands-Balkema-de Haan theorem for tail fitting, or the methods related to large deviation theory. In the paper the most important stochastic distributions relevant for performing rare events statistical analysis will be presented. This concerns, for example, the analysis of the data with the annual extreme values (maxima - "Annual Maxima Series" or minima), or the peak values, exceeding given thresholds at some periods of interest ("Peak Over Threshold"), or the estimation of the size of exceedance. Despite of the fact that there is a lack of sufficient statistical data directly containing rare events, in some cases it is still possible to extract useful information from existing larger data sets. As an example one can consider some data sets available from the web sites for floods, earthquakes or generally natural hazards. Some aspects of such data sets will be also presented taking into account their usefulness for the practical assessment of risk for nuclear power plants coming from extreme weather conditions.

Overview of the biology of extreme events

Science.gov (United States)

Gutschick, V. P.; Bassirirad, H.

2008-12-01

Extreme events have, variously, meteorological origins as in heat waves or precipitation extremes, or biological origins as in pest and disease eruptions (or tectonic, earth-orbital, or impact-body origins). Despite growing recognition that these events are changing in frequency and intensity, a universal model of ecological responses to these events is slow to emerge. Extreme events, negative and positive, contrast with normal events in terms of their effects on the physiology, ecology, and evolution of organisms, hence also on water, carbon, and nutrient cycles. They structure biogeographic ranges and biomes, almost surely more than mean values often used to define biogeography. They are challenging to study for obvious reasons of field-readiness but also because they are defined by sequences of driving variables such as temperature, not point events. As sequences, their statistics (return times, for example) are challenging to develop, as also from the involvement of multiple environmental variables. These statistics are not captured well by climate models. They are expected to change with climate and land-use change but our predictive capacity is currently limited. A number of tools for description and analysis of extreme events are available, if not widely applied to date. Extremes for organisms are defined by their fitness effects on those organisms, and are specific to genotypes, making them major agents of natural selection. There is evidence that effects of extreme events may be concentrated in an extended recovery phase. We review selected events covering ranges of time and magnitude, from Snowball Earth to leaf functional loss in weather events. A number of events, such as the 2003 European heat wave, evidence effects on water and carbon cycles over large regions. Rising CO2 is the recent extreme of note, for its climatic effects and consequences for growing seasons, transpiration, etc., but also directly in its action as a substrate of photosynthesis

Nonlinear wave-mixing processes in the extreme ultraviolet

International Nuclear Information System (INIS)

Misoguti, L.; Christov, I. P.; Backus, S.; Murnane, M. M.; Kapteyn, H. C.

2005-01-01

We present data from two-color high-order harmonic generation in a hollow waveguide, that suggest the presence of a nonlinear-optical frequency conversion process driven by extreme ultraviolet light. By combining the fundamental and second harmonic of an 800 nm laser in a hollow-core fiber, with varying relative polarizations, and by observing the pressure and power scaling of the various harmonic orders, we show that the data are consistent with a picture where we drive the process of high-harmonic generation, which in turn drives four-wave frequency mixing processes in the extreme EUV. This work promises a method for extending nonlinear optics into the extreme ultraviolet region of the spectrum using an approach that has not previously been considered, and has compelling implications for generating tunable light at short wavelengths

Efficient Estimation of Extreme Non-linear Roll Motions using the First-order Reliability Method (FORM)

DEFF Research Database (Denmark)

Jensen, Jørgen Juncher

2007-01-01

In on-board decision support systems efficient procedures are needed for real-time estimation of the maximum ship responses to be expected within the next few hours, given on-line information on the sea state and user defined ranges of possible headings and speeds. For linear responses standard...... frequency domain methods can be applied. To non-linear responses like the roll motion, standard methods like direct time domain simulations are not feasible due to the required computational time. However, the statistical distribution of non-linear ship responses can be estimated very accurately using...... the first-order reliability method (FORM), well-known from structural reliability problems. To illustrate the proposed procedure, the roll motion is modelled by a simplified non-linear procedure taking into account non-linear hydrodynamic damping, time-varying restoring and wave excitation moments...

Direction-of-Arrival Estimation Based on Sparse Recovery with Second-Order Statistics

Directory of Open Access Journals (Sweden)

H. Chen

2015-04-01

Full Text Available Traditional direction-of-arrival (DOA estimation techniques perform Nyquist-rate sampling of the received signals and as a result they require high storage. To reduce sampling ratio, we introduce level-crossing (LC sampling which captures samples whenever the signal crosses predetermined reference levels, and the LC-based analog-to-digital converter (LC ADC has been shown to efficiently sample certain classes of signals. In this paper, we focus on the DOA estimation problem by using second-order statistics based on the LC samplings recording on one sensor, along with the synchronous samplings of the another sensors, a sparse angle space scenario can be found by solving an $ell_1$ minimization problem, giving the number of sources and their DOA's. The experimental results show that our proposed method, when compared with some existing norm-based constrained optimization compressive sensing (CS algorithms, as well as subspace method, improves the DOA estimation performance, while using less samples when compared with Nyquist-rate sampling and reducing sensor activity especially for long time silence signal.

Is prescribed lower extremity weight-bearing status after geriatric lower extremity trauma associated with increased mortality?

Science.gov (United States)

Gitajn, Ida Leah; Connelly, Daniel; Mascarenhas, Daniel; Breazeale, Stephen; Berger, Peter; Schoonover, Carrie; Martin, Brook; O'Toole, Robert V; Pensy, Raymond; Sciadini, Marcus

2018-02-01

Evaluate whether mortality after discharge is elevated in geriatric fracture patients whose lower extremity weight-bearing is restricted. Retrospective cohort study SETTING: Urban Level 1 trauma center PATIENTS/PARTICIPANTS: 1746 patients >65 years of age INTERVENTION: Post-operative lower extremity weight-bearing status MAIN OUTCOME MEASURE: Mortality, as determined by the Social Security Death Index RESULTS: Univariate analysis demonstrated that patients who were weight-bearing as tolerated on bilateral lower extremities (BLE) had significantly higher 5-year mortality compared to patients with restricted weight-bearing on one lower extremity and restricted weight-bearing on BLE (30%, 21% and 22% respectively, p bearing as tolerated on BLE, restricted weight-bearing on one lower extremity had a hazard ratio (HR) of 0.97 (95% confidence interval 0.78 to 1.20, p = 0.76) and restricted weight-bearing in BLE had a HR of 0.91 (95% confidence interval 0.60 to 1.36, p = 0.73). In geriatric patients, prescribed weight-bearing status did not have a statistically significant association with mortality after discharge, when controlling for age, sex, body mass index, medical comorbidities, Injury Severity Scale (ISS), mechanism of injury, nonoperative treatment and admission GCS. This remained true in when the analysis was restricted to operative injuries only. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Separation Algorithm for Sources with Temporal Structure Only Using Second-order Statistics

Directory of Open Access Journals (Sweden)

J.G. Wang

2013-09-01

Full Text Available Unlike conventional blind source separation (BSS deals with independent identically distributed (i.i.d. sources, this paper addresses the separation from mixtures of sources with temporal structure, such as linear autocorrelations. Many sequential extraction algorithms have been reported, resulting in inevitable cumulated errors introduced by the deflation scheme. We propose a robust separation algorithm to recover original sources simultaneously, through a joint diagonalizer of several average delayed covariance matrices at positions of the optimal time delay and its integers. The proposed algorithm is computationally simple and efficient, since it is based on the second-order statistics only. Extensive simulation results confirm the validity and high performance of the algorithm. Compared with related extraction algorithms, its separation signal-to-noise rate for a desired source can reach 20dB higher, and it seems rather insensitive to the estimation error of the time delay.

Spatial extreme learning machines: An application on prediction of disease counts.

Science.gov (United States)

Prates, Marcos O

2018-01-01

Extreme learning machines have gained a lot of attention by the machine learning community because of its interesting properties and computational advantages. With the increase in collection of information nowadays, many sources of data have missing information making statistical analysis harder or unfeasible. In this paper, we present a new model, coined spatial extreme learning machine, that combine spatial modeling with extreme learning machines keeping the nice properties of both methodologies and making it very flexible and robust. As explained throughout the text, the spatial extreme learning machines have many advantages in comparison with the traditional extreme learning machines. By a simulation study and a real data analysis we present how the spatial extreme learning machine can be used to improve imputation of missing data and uncertainty prediction estimation.

Feasibility of estimating generalized extreme-value distribution of floods

International Nuclear Information System (INIS)

Ferreira de Queiroz, Manoel Moises

2004-01-01

Flood frequency analysis by generalized extreme-value probability distribution (GEV) has found increased application in recent years, given its flexibility in dealing with the three asymptotic forms of extreme distribution derived from different initial probability distributions. Estimation of higher quantiles of floods is usually accomplished by extrapolating one of the three inverse forms of GEV distribution fitted to the experimental data for return periods much higher than those actually observed. This paper studies the feasibility of fitting GEV distribution by moments of linear combinations of higher order statistics (LH moments) using synthetic annual flood series with varying characteristics and lengths. As the hydrologic events in nature such as daily discharge occur with finite values, their annual maximums are expected to follow the asymptotic form of the limited GEV distribution. Synthetic annual flood series were thus obtained from the stochastic sequences of 365 daily discharges generated by Monte Carlo simulation on the basis of limited probability distribution underlying the limited GEV distribution. The results show that parameter estimation by LH moments of this distribution, fitted to annual flood samples of less than 100-year length derived from initial limited distribution, may indicate any form of extreme-value distribution, not just the limited form as expected, and with large uncertainty in fitted parameters. A frequency analysis, on the basis of GEV distribution and LH moments, of annual flood series of lengths varying between 13 and 73 years observed at 88 gauge stations on Parana River in Brazil, indicated all the three forms of GEV distribution.(Author)

Entropy, extremality, euclidean variations, and the equations of motion

Science.gov (United States)

Dong, Xi; Lewkowycz, Aitor

2018-01-01

We study the Euclidean gravitational path integral computing the Rényi entropy and analyze its behavior under small variations. We argue that, in Einstein gravity, the extremality condition can be understood from the variational principle at the level of the action, without having to solve explicitly the equations of motion. This set-up is then generalized to arbitrary theories of gravity, where we show that the respective entanglement entropy functional needs to be extremized. We also extend this result to all orders in Newton's constant G N , providing a derivation of quantum extremality. Understanding quantum extremality for mixtures of states provides a generalization of the dual of the boundary modular Hamiltonian which is given by the bulk modular Hamiltonian plus the area operator, evaluated on the so-called modular extremal surface. This gives a bulk prescription for computing the relative entropies to all orders in G N . We also comment on how these ideas can be used to derive an integrated version of the equations of motion, linearized around arbitrary states.

Statistics for Physical Sciences An Introduction

CERN Document Server

Martin, Brian

2012-01-01

Statistical Methods for the Physical Sciences is an informal, relatively short, but systematic, guide to the more commonly used ideas and techniques in statistical analysis, as used in physical sciences, together with explanations of their origins. It steers a path between the extremes of a recipe of methods with a collection of useful formulas, and a full mathematical account of statistics, while at the same time developing the subject in a logical way. The book can be read in its entirety by anyone with a basic exposure to mathematics at the level of a first-year undergraduate student

A NEW TEST OF THE STATISTICAL NATURE OF THE BRIGHTEST CLUSTER GALAXIES

International Nuclear Information System (INIS)

Lin, Yen-Ting; Ostriker, Jeremiah P.; Miller, Christopher J.

2010-01-01

A novel statistic is proposed to examine the hypothesis that all cluster galaxies are drawn from the same luminosity distribution (LD). In such a 'statistical model' of galaxy LD, the brightest cluster galaxies (BCGs) are simply the statistical extreme of the galaxy population. Using a large sample of nearby clusters, we show that BCGs in high luminosity clusters (e.g., L tot ∼> 4 x 10 11 h -2 70 L sun ) are unlikely (probability ≤3 x 10 -4 ) to be drawn from the LD defined by all red cluster galaxies more luminous than M r = -20. On the other hand, BCGs in less luminous clusters are consistent with being the statistical extreme. Applying our method to the second brightest galaxies, we show that they are consistent with being the statistical extreme, which implies that the BCGs are also distinct from non-BCG luminous, red, cluster galaxies. We point out some issues with the interpretation of the classical tests proposed by Tremaine and Richstone (TR) that are designed to examine the statistical nature of BCGs, investigate the robustness of both our statistical test and those of TR against difficulties in photometry of galaxies of large angular size, and discuss the implication of our findings on surveys that use the luminous red galaxies to measure the baryon acoustic oscillation features in the galaxy power spectrum.

Counting States of Near-Extremal Black Holes

International Nuclear Information System (INIS)

Horowitz, G.T.; Strominger, A.

1996-01-01

A six-dimensional black string is considered and its Bekenstein-Hawking entropy computed. It is shown that to leading order above extremality this entropy precisely counts the number of string states with the given energy and charges. This identification implies that Hawking decay of the near-extremal black string can be analyzed in string perturbation theory and is perturbatively unitary. copyright 1996 The American Physical Society

Dynamic process analysis by moments of extreme orders

Czech Academy of Sciences Publication Activity Database

Šimberová, Stanislava; Suk, Tomáš

2016-01-01

Roč. 14, January (2016), s. 43-51 ISSN 2213-1337 R&D Projects: GA ČR GA15-16928S Institutional support: RVO:67985815 ; RVO:67985556 Keywords : high-order moments * principal component analysis * frequency analysis Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics; BD - Theory of Information (UTIA-B) Impact factor: 2.010, year: 2016

Acclimatization to extreme heat

Science.gov (United States)

Warner, M. E.; Ganguly, A. R.; Bhatia, U.

2017-12-01

Heat extremes throughout the globe, as well as in the United States, are expected to increase. These heat extremes have been shown to impact human health, resulting in some of the highest levels of lives lost as compared with similar natural disasters. But in order to inform decision makers and best understand future mortality and morbidity, adaptation and mitigation must be considered. Defined as the ability for individuals or society to change behavior and/or adapt physiologically, acclimatization encompasses the gradual adaptation that occurs over time. Therefore, this research aims to account for acclimatization to extreme heat by using a hybrid methodology that incorporates future air conditioning use and installation patterns with future temperature-related time series data. While previous studies have not accounted for energy usage patterns and market saturation scenarios, we integrate such factors to compare the impact of air conditioning as a tool for acclimatization, with a particular emphasis on mortality within vulnerable communities.

Probability, statistics, and queueing theory

CERN Document Server

Allen, Arnold O

1990-01-01

This is a textbook on applied probability and statistics with computer science applications for students at the upper undergraduate level. It may also be used as a self study book for the practicing computer science professional. The successful first edition of this book proved extremely useful to students who need to use probability, statistics and queueing theory to solve problems in other fields, such as engineering, physics, operations research, and management science. The book has also been successfully used for courses in queueing theory for operations research students. This second edit

Investigation of hand function among children diagnosed with autism spectrum disorder with upper extremity trauma history.

Science.gov (United States)

Huri, Meral; Şahin, Sedef; Kayıhan, Hülya

2016-11-01

The present study was designed to compare hand function in autistic children with history of upper extremity trauma with that of autistic children those who do not have history of trauma. The study group included total of 65 children diagnosed with autism spectrum disorder (ASD) and was divided into 2 groups: children with trauma history (Group I) and control group (Group II) (Group I: n=28; Group II: n=37). Hand function was evaluated with 9-Hole Peg Test and Jebsen Hand Function Test. Somatosensory function was evaluated using somatosensory subtests of Sensory Integration and Praxis Test. Results were analyzed with Student's t-test and Mann-Whitney U test using SPSS version 20 software. Hand function and somatosensory perception test scores were statistically significantly better in children without upper extremity trauma history (pManual Form Perception and Localization of Tactile Stimuli Test results (p<0.05). Autistic children with upper extremity trauma history had poor somatosensory perception and hand function. It is important to raise awareness among emergency service staff and inform them about strong relationship between somatosensory perception, hand function, and upper extremity trauma in children with ASD in order to develop appropriate rehabilitation process and prevent further trauma.

Extreme prices in electricity balancing markets from an approach of statistical physics

Science.gov (United States)

Mureddu, Mario; Meyer-Ortmanns, Hildegard

2018-01-01

An increase in energy production from renewable energy sources is viewed as a crucial achievement in most industrialized countries. The higher variability of power production via renewables leads to a rise in ancillary service costs over the power system, in particular costs within the electricity balancing markets, mainly due to an increased number of extreme price spikes. This study analyzes the impact of an increased share of renewable energy sources on the behavior of price and volumes of the Italian balancing market. Starting from configurations of load and power production, which guarantee a stable performance, we implement fluctuations in the load and in renewables; in particular we artificially increase the contribution of renewables as compared to conventional power sources to cover the total load. We then determine the amount of requested energy in the balancing market and its fluctuations, which are induced by production and consumption. Within an approach of agent-based modeling we estimate the resulting energy prices and costs. While their average values turn out to be only slightly affected by an increased contribution from renewables, the probability for extreme price events is shown to increase along with undesired peaks in the costs. Our methodology provides a tool for estimating outliers in prices obtained in the energy balancing market, once data of consumption, production and their typical fluctuations are provided.

Caregiver Statistics: Demographics

Science.gov (United States)

... You are here Home Selected Long-Term Care Statistics Order this publication Printer-friendly version What is ... needs and services are wide-ranging and complex, statistics may vary from study to study. Sources for ...

Influence of climate variability versus change at multi-decadal time scales on hydrological extremes

Science.gov (United States)

Willems, Patrick

2014-05-01

Recent studies have shown that rainfall and hydrological extremes do not randomly occur in time, but are subject to multidecadal oscillations. In addition to these oscillations, there are temporal trends due to climate change. Design statistics, such as intensity-duration-frequency (IDF) for extreme rainfall or flow-duration-frequency (QDF) relationships, are affected by both types of temporal changes (short term and long term). This presentation discusses these changes, how they influence water engineering design and decision making, and how this influence can be assessed and taken into account in practice. The multidecadal oscillations in rainfall and hydrological extremes were studied based on a technique for the identification and analysis of changes in extreme quantiles. The statistical significance of the oscillations was evaluated by means of a non-parametric bootstrapping method. Oscillations in large scale atmospheric circulation were identified as the main drivers for the temporal oscillations in rainfall and hydrological extremes. They also explain why spatial phase shifts (e.g. north-south variations in Europe) exist between the oscillation highs and lows. Next to the multidecadal climate oscillations, several stations show trends during the most recent decades, which may be attributed to climate change as a result of anthropogenic global warming. Such attribution to anthropogenic global warming is, however, uncertain. It can be done based on simulation results with climate models, but it is shown that the climate model results are too uncertain to enable a clear attribution. Water engineering design statistics, such as extreme rainfall IDF or peak or low flow QDF statistics, obviously are influenced by these temporal variations (oscillations, trends). It is shown in the paper, based on the Brussels 10-minutes rainfall data, that rainfall design values may be about 20% biased or different when based on short rainfall series of 10 to 15 years length, and

Suppression of intensity transition artifacts in statistical x-ray computer tomography reconstruction through Radon inversion initialization

International Nuclear Information System (INIS)

Zbijewski, Wojciech; Beekman, Freek J.

2004-01-01

Statistical reconstruction (SR) methods provide a general and flexible framework for obtaining tomographic images from projections. For several applications SR has been shown to outperform analytical algorithms in terms of resolution-noise trade-off achieved in the reconstructions. A disadvantage of SR is the long computational time required to obtain the reconstructions, in particular when large data sets characteristic for x-ray computer tomography (CT) are involved. As was shown recently, by combining statistical methods with block iterative acceleration schemes [e.g., like in the ordered subsets convex (OSC) algorithm], the reconstruction time for x-ray CT applications can be reduced by about two orders of magnitude. There are, however, some factors lengthening the reconstruction process that hamper both accelerated and standard statistical algorithms to similar degree. In this simulation study based on monoenergetic and scatter-free projection data, we demonstrate that one of these factors is the extremely high number of iterations needed to remove artifacts that can appear around high-contrast structures. We also show (using the OSC method) that these artifacts can be adequately suppressed if statistical reconstruction is initialized with images generated by means of Radon inversion algorithms like filtered back projection (FBP). This allows the reconstruction time to be shortened by even as much as one order of magnitude. Although the initialization of the statistical algorithm with FBP image introduces some additional noise into the first iteration of OSC reconstruction, the resolution-noise trade-off and the contrast-to-noise ratio of final images are not markedly compromised

Technical Note: Higher-order statistical moments and a procedure that detects potentially anomalous years as two alternative methods describing alterations in continuous environmental data

Science.gov (United States)

I. Arismendi; S. L. Johnson; J. B. Dunham

2015-01-01

Statistics of central tendency and dispersion may not capture relevant or desired characteristics of the distribution of continuous phenomena and, thus, they may not adequately describe temporal patterns of change. Here, we present two methodological approaches that can help to identify temporal changes in environmental regimes. First, we use higher-order statistical...

Comparison of different statistical methods for estimation of extreme sea levels with wave set-up contribution

Science.gov (United States)

Kergadallan, Xavier; Bernardara, Pietro; Benoit, Michel; Andreewsky, Marc; Weiss, Jérôme

2013-04-01

Estimating the probability of occurrence of extreme sea levels is a central issue for the protection of the coast. Return periods of sea level with wave set-up contribution are estimated here in one site : Cherbourg in France in the English Channel. The methodology follows two steps : the first one is computation of joint probability of simultaneous wave height and still sea level, the second one is interpretation of that joint probabilities to assess a sea level for a given return period. Two different approaches were evaluated to compute joint probability of simultaneous wave height and still sea level : the first one is multivariate extreme values distributions of logistic type in which all components of the variables become large simultaneously, the second one is conditional approach for multivariate extreme values in which only one component of the variables have to be large. Two different methods were applied to estimate sea level with wave set-up contribution for a given return period : Monte-Carlo simulation in which estimation is more accurate but needs higher calculation time and classical ocean engineering design contours of type inverse-FORM in which the method is simpler and allows more complex estimation of wave setup part (wave propagation to the coast for example). We compare results from the two different approaches with the two different methods. To be able to use both Monte-Carlo simulation and design contours methods, wave setup is estimated with an simple empirical formula. We show advantages of the conditional approach compared to the multivariate extreme values approach when extreme sea-level occurs when either surge or wave height is large. We discuss the validity of the ocean engineering design contours method which is an alternative when computation of sea levels is too complex to use Monte-Carlo simulation method.

Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

DEFF Research Database (Denmark)

Thorndahl, Søren; Korup Andersen, Aske; Larsen, Anders Badsberg

2017-01-01

Continuous and long rainfall series are a necessity in rural and urban hydrology for analysis and design purposes. Local historical point rainfall series often cover several decades, which makes it possible to estimate rainfall means at different timescales, and to assess return periods of extreme...... includes climate changes projected to a specific future period. This paper presents a framework for resampling of historical point rainfall series in order to generate synthetic rainfall series, which has the same statistical properties as an original series. Using a number of key target predictions...... for the future climate, such as winter and summer precipitation, and representation of extreme events, the resampled historical series are projected to represent rainfall properties in a future climate. Climate-projected rainfall series are simulated by brute force randomization of model parameters, which leads...

Angiography of the upper extremity

International Nuclear Information System (INIS)

Janevski, B.K.

1982-01-01

This thesis provides a description of the technical and medical aspects of arteriography of the upper extremity and an extensive analysis of the angiographic anatomy and pathology of 750 selective studies performed in more than 500 patients. A short historical review is provided of angiography as a whole and of arteriography of the hand in particular. The method of percutaneous transfemoral catheterization of the arteries of the upper extremity and particularly the arteries of the hand is considered, discussing the problems the angiographer encounters frequently, describing the angiographic complications which may occur and emphasizing the measures to keep them to a minimum. The use of vasodilators in hand angiography is discussed. A short description of the embryological patterns persisting in the arteries of the arm is included in order to understand the congenital variations of the arteries of the upper extremity. The angiographic patterns and clinical aspects of the most common pathological processes involving the arteries of the upper extremities are presented. Special attention is paid to the correlation between angiography and pathology. (Auth.)

Laws of small numbers extremes and rare events

CERN Document Server

Falk, Michael; Hüsler, Jürg

2004-01-01

Since the publication of the first edition of this seminar book in 1994, the theory and applications of extremes and rare events have enjoyed an enormous and still increasing interest. The intention of the book is to give a mathematically oriented development of the theory of rare events underlying various applications. This characteristic of the book was strengthened in the second edition by incorporating various new results on about 130 additional pages. Part II, which has been added in the second edition, discusses recent developments in multivariate extreme value theory. Particularly notable is a new spectral decomposition of multivariate distributions in univariate ones which makes multivariate questions more accessible in theory and practice. One of the most innovative and fruitful topics during the last decades was the introduction of generalized Pareto distributions in the univariate extreme value theory. Such a statistical modelling of extremes is now systematically developed in the multivariate fram...

Volcanic hazard assessment for the Canary Islands (Spain using extreme value theory

Directory of Open Access Journals (Sweden)

R. Sobradelo

2011-10-01

Full Text Available The Canary Islands are an active volcanic region densely populated and visited by several millions of tourists every year. Nearly twenty eruptions have been reported through written chronicles in the last 600 yr, suggesting that the probability of a new eruption in the near future is far from zero. This shows the importance of assessing and monitoring the volcanic hazard of the region in order to reduce and manage its potential volcanic risk, and ultimately contribute to the design of appropriate preparedness plans. Hence, the probabilistic analysis of the volcanic eruption time series for the Canary Islands is an essential step for the assessment of volcanic hazard and risk in the area. Such a series describes complex processes involving different types of eruptions over different time scales. Here we propose a statistical method for calculating the probabilities of future eruptions which is most appropriate given the nature of the documented historical eruptive data. We first characterize the eruptions by their magnitudes, and then carry out a preliminary analysis of the data to establish the requirements for the statistical method. Past studies in eruptive time series used conventional statistics and treated the series as an homogeneous process. In this paper, we will use a method that accounts for the time-dependence of the series and includes rare or extreme events, in the form of few data of large eruptions, since these data require special methods of analysis. Hence, we will use a statistical method from extreme value theory. In particular, we will apply a non-homogeneous Poisson process to the historical eruptive data of the Canary Islands to estimate the probability of having at least one volcanic event of a magnitude greater than one in the upcoming years. This is done in three steps: First, we analyze the historical eruptive series to assess independence and homogeneity of the process. Second, we perform a Weibull analysis of the

Higher-Order Moment Characterisation of Rogue Wave Statistics in Supercontinuum Generation

DEFF Research Database (Denmark)

Sørensen, Simon Toft; Bang, Ole; Wetzel, Benjamin

2012-01-01

The noise characteristics of supercontinuum generation are characterized using higherorder statistical moments. Measures of skew and kurtosis, and the coefficient of variation allow quantitative identification of spectral regions dominated by rogue wave like behaviour.......The noise characteristics of supercontinuum generation are characterized using higherorder statistical moments. Measures of skew and kurtosis, and the coefficient of variation allow quantitative identification of spectral regions dominated by rogue wave like behaviour....

Growth Curve Analysis and Change-Points Detection in Extremes

KAUST Repository

Meng, Rui

2016-05-15

The thesis consists of two coherent projects. The first project presents the results of evaluating salinity tolerance in barley using growth curve analysis where different growth trajectories are observed within barley families. The study of salinity tolerance in plants is crucial to understanding plant growth and productivity. Because fully-automated smarthouses with conveyor systems allow non-destructive and high-throughput phenotyping of large number of plants, it is now possible to apply advanced statistical tools to analyze daily measurements and to study salinity tolerance. To compare different growth patterns of barley variates, we use functional data analysis techniques to analyze the daily projected shoot areas. In particular, we apply the curve registration method to align all the curves from the same barley family in order to summarize the family-wise features. We also illustrate how to use statistical modeling to account for spatial variation in microclimate in smarthouses and for temporal variation across runs, which is crucial for identifying traits of the barley variates. In our analysis, we show that the concentrations of sodium and potassium in leaves are negatively correlated, and their interactions are associated with the degree of salinity tolerance. The second project studies change-points detection methods in extremes when multiple time series data are available. Motived by the scientific question of whether the chances to experience extreme weather are different in different seasons of a year, we develop a change-points detection model to study changes in extremes or in the tail of a distribution. Most of existing models identify seasons from multiple yearly time series assuming a season or a change-point location remains exactly the same across years. In this work, we propose a random effect model that allows the change-point to vary from year to year, following a given distribution. Both parametric and nonparametric methods are developed

Practical Statistics

CERN Document Server

Lyons, L.

2016-01-01

Accelerators and detectors are expensive, both in terms of money and human effort. It is thus important to invest effort in performing a good statistical anal- ysis of the data, in order to extract the best information from it. This series of five lectures deals with practical aspects of statistical issues that arise in typical High Energy Physics analyses.

Joint statistics of partial sums of ordered exponential variates and performance of GSC RAKE receivers over rayleigh fading channel

KAUST Repository

Nam, Sungsik

2011-08-01

Spread spectrum receivers with generalized selection combining (GSC) RAKE reception were proposed and have been studied as alternatives to the classical two fundamental schemes: maximal ratio combining and selection combining because the number of diversity paths increases with the transmission bandwidth. Previous work on performance analyses of GSC RAKE receivers based on the signal to noise ratio focused on the development of methodologies to derive exact closed-form expressions for various performance measures. However, some open problems related to the performance evaluation of GSC RAKE receivers still remain to be solved such as the exact performance analysis of the capture probability and an exact assessment of the impact of self-interference on GSC RAKE receivers. The major difficulty in these problems is to derive some joint statistics of ordered exponential variates. With this motivation in mind, we capitalize in this paper on some new order statistics results to derive exact closed-form expressions for the capture probability and outage probability of GSC RAKE receivers subject to self-interference over independent and identically distributed Rayleigh fading channels, and compare it to that of partial RAKE receivers. © 2011 IEEE.

Circular contour retrieval in real-world conditions by higher order statistics and an alternating-least squares algorithm

Science.gov (United States)

Jiang, Haiping; Marot, Julien; Fossati, Caroline; Bourennane, Salah

2011-12-01

In real-world conditions, contours are most often blurred in digital images because of acquisition conditions such as movement, light transmission environment, and defocus. Among image segmentation methods, Hough transform requires a computational load which increases with the number of noise pixels, level set methods also require a high computational load, and some other methods assume that the contours are one-pixel wide. For the first time, we retrieve the characteristics of multiple possibly concentric blurred circles. We face correlated noise environment, to get closer to real-world conditions. For this, we model a blurred circle by a few parameters--center coordinates, radius, and spread--which characterize its mean position and gray level variations. We derive the signal model which results from signal generation on circular antenna. Linear antennas provide the center coordinates. To retrieve the circle radii, we adapt the second-order statistics TLS-ESPRIT method for non-correlated noise environment, and propose a novel version of TLS-ESPRIT based on higher-order statistics for correlated noise environment. Then, we derive a least-squares criterion and propose an alternating least-squares algorithm to retrieve simultaneously all spread values of concentric circles. Experiments performed on hand-made and real-world images show that the proposed methods outperform the Hough transform and a level set method dedicated to blurred contours in terms of computational load. Moreover, the proposed model and optimization method provide the information of the contour grey level variations.

Classifying Returns as Extreme: European Stock and Bond Markets

DEFF Research Database (Denmark)

Christiansen, Charlotte

whereby a shorter sample period is needed. For the bond markets the simultaneous extreme return variable (used for analyzing integration and contagion of financial markets) is not statistically different for the two schemes. For the stock markets there are differences, but they are disappearing......I consider the stock and bond markets of 14 EU countries. I use two classification schemes for defining extreme returns: One, the existing univariate classification scheme which considers each market separately. Two, the new multivariate classification scheme that considers all the markets jointly...

A method of validating climate models in climate research with a view to extreme events; Eine Methode zur Validierung von Klimamodellen fuer die Klimawirkungsforschung hinsichtlich der Wiedergabe extremer Ereignisse

Energy Technology Data Exchange (ETDEWEB)

Boehm, U

2000-08-01

A method is presented to validate climate models with respect to extreme events which are suitable for risk assessment in impact modeling. The algorithm is intended to complement conventional techniques. These procedures mainly compare simulation results with reference data based on single or only a few climatic variables at the same time under the aspect how well a model performs in reproducing the known physical processes of the atmosphere. Such investigations are often based on seasonal or annual mean values. For impact research, however, extreme climatic conditions with shorter typical time scales are generally more interesting. Furthermore, such extreme events are frequently characterized by combinations of individual extremes which require a multivariate approach. The validation method presented here basically consists of a combination of several well-known statistical techniques, completed by a newly developed diagnosis module to quantify model deficiencies. First of all, critical threshold values of key climatic variables for impact research have to be derived serving as criteria to define extreme conditions for a specific activity. Unlike in other techniques, the simulation results to be validated are interpolated to the reference data sampling points in the initial step of this new technique. Besides that fact that the same spatial representation is provided in this way in both data sets for the next diagnostic steps, this procedure also enables to leave the reference basis unchanged for any type of model output and to perform the validation on a real orography. To simultaneously identify the spatial characteristics of a given situation regarding all considered extreme value criteria, a multivariate cluster analysis method for pattern recognition is separately applied to both simulation results and reference data. Afterwards, various distribution-free statistical tests are applied depending on the specific situation to detect statistical significant

A method of validating climate models in climate research with a view to extreme events; Eine Methode zur Validierung von Klimamodellen fuer die Klimawirkungsforschung hinsichtlich der Wiedergabe extremer Ereignisse

Energy Technology Data Exchange (ETDEWEB)

Boehm, U.

2000-08-01

A method is presented to validate climate models with respect to extreme events which are suitable for risk assessment in impact modeling. The algorithm is intended to complement conventional techniques. These procedures mainly compare simulation results with reference data based on single or only a few climatic variables at the same time under the aspect how well a model performs in reproducing the known physical processes of the atmosphere. Such investigations are often based on seasonal or annual mean values. For impact research, however, extreme climatic conditions with shorter typical time scales are generally more interesting. Furthermore, such extreme events are frequently characterized by combinations of individual extremes which require a multivariate approach. The validation method presented here basically consists of a combination of several well-known statistical techniques, completed by a newly developed diagnosis module to quantify model deficiencies. First of all, critical threshold values of key climatic variables for impact research have to be derived serving as criteria to define extreme conditions for a specific activity. Unlike in other techniques, the simulation results to be validated are interpolated to the reference data sampling points in the initial step of this new technique. Besides that fact that the same spatial representation is provided in this way in both data sets for the next diagnostic steps, this procedure also enables to leave the reference basis unchanged for any type of model output and to perform the validation on a real orography. To simultaneously identify the spatial characteristics of a given situation regarding all considered extreme value criteria, a multivariate cluster analysis method for pattern recognition is separately applied to both simulation results and reference data. Afterwards, various distribution-free statistical tests are applied depending on the specific situation to detect statistical significant

Sound statistical model checking for MDP using partial order and confluence reduction

NARCIS (Netherlands)

Hartmanns, Arnd; Timmer, Mark

Statistical model checking (SMC) is an analysis method that circumvents the state space explosion problem in model-based verification by combining probabilistic simulation with statistical methods that provide clear error bounds. As a simulation-based technique, it can in general only provide sound

Extreme value theory in emerging markets

Directory of Open Access Journals (Sweden)

Anđelić Goran

2010-01-01

Full Text Available This paper investigates the performance of extreme value theory (EVT with the daily stock index returns of four different emerging markets. The research covers the sample representing the Serbian (BELEXline, Croatian (CROBEX, Slovenian (SBI20, and Hungarian (BUX stock indexes using the data from January 2006 - September 2009. In the paper a performance test was carried out for the success of application of the extreme value theory in estimating and forecasting of the tails of daily return distribution of the analyzed stock indexes. Therefore the main goal is to determine whether EVT adequately estimates and forecasts the tails (2.5% and 5% at the tail of daily stock index return distribution in the emerging markets of Serbia, Croatia, Slovenia, and Hungary. The applied methodology during the research includes analysis, synthesis and statistical/mathematical methods. Research results according to estimated Generalized Pareto Distribution (GPD parameters indicate the necessity of applying market risk estimation methods, i.e. extreme value theory (EVT in the framework of a broader analysis of investment processes in emerging markets.

An Update on Statistical Boosting in Biomedicine.

Science.gov (United States)

Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian; Gefeller, Olaf

2017-01-01

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

Do work-related factors affect care-seeking in general practice for back pain or upper extremity pain?

Science.gov (United States)

Jensen, Jens Christian; Haahr, Jens Peder; Frost, Poul; Andersen, Johan Hviid

2013-10-01

Musculoskeletal pain conditions remain a major cause of care-seeking in general practice. Not all patients with musculoskeletal pain (MP) seek care at their general practitioner (GP), but for those who do, the GP's knowledge of what work-related factors might have influenced the patient's decision to seek care could be important in order to give more well-founded advice to our patients. The objective of this study was to elucidate the effects of workloads on care-seeking for back pain or upper extremity pain during an eighteen-month follow-up period. This is a prospective study with a baseline questionnaire and eighteen-month follow-up. Among the registered patients of 8 GPs, we identified 8,517 persons between 17 and 65 years of age, who all received the questionnaire. A total of 5,068 (59.5 %) persons answered. During the eighteen months of follow-up, we used the International Classification for Primary Care (ICPC) to identify all care-seekers with either back pain or upper extremity pain. Of these, all currently employed persons were included in our analysis, in all 4,325 persons. For analysis, we used Cox proportional hazards regression analysis. Analyses were stratified by gender. High levels of heavy lifting, defined as the upper tertile on a categorical scale, were associated with care-seeking for back pain (HR 1.90 [95 % CI: 1.14-3.15]) and upper extremity pain (HR 2.09 [95 % CI: 1.30-3.38]) among males, but not in a statistically significant way among females. Repetitive work and psychosocial factors did not have any statistically significant impact on care-seeking for neither back pain nor upper extremity pain. Work-related factors such as heavy lifting do, to some extent, contribute to care-seeking with MP. We suggest that asking the patient about physical workloads should be routinely included in consultations dealing with MP.

Ultrasonography of the lower extremity veins: Anatomy and basic approach

Energy Technology Data Exchange (ETDEWEB)

Lee, Dong Kyu; Ahn, Kyung Sik; Kang, Chang Ho; Cho, Sung Bum [Dept. of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul (Korea, Republic of)

2017-04-15

Ultrasonography is an imaging modality widely used to evaluate venous diseases of the lower extremities. It is important to understand the normal venous anatomy of the lower extremities, which has deep, superficial, and perforating venous components, in order to determine the pathophysiology of venous disease. This review provides a basic description of the anatomy of the lower extremity veins and useful techniques for approaching each vein via ultrasonography.

Ultrasonography of the lower extremity veins: Anatomy and basic approach

International Nuclear Information System (INIS)

Lee, Dong Kyu; Ahn, Kyung Sik; Kang, Chang Ho; Cho, Sung Bum

2017-01-01

Ultrasonography is an imaging modality widely used to evaluate venous diseases of the lower extremities. It is important to understand the normal venous anatomy of the lower extremities, which has deep, superficial, and perforating venous components, in order to determine the pathophysiology of venous disease. This review provides a basic description of the anatomy of the lower extremity veins and useful techniques for approaching each vein via ultrasonography

On the use of non-Gaussian models for prediction of extreme pollution levels in environmental studies

Science.gov (United States)

Berg, D. B.; Medvedev, A. N.; Sergeev, A. P.; Taubayev, A. A.

2015-11-01

The aim of this work is to study the distribution of contamination at the territory on the data of snow samples analysis, in order to find an approach to forecasting of the extreme pollution levels. The hypothesis of normal distribution of the values of pollution index (the intensity of dust fallout on the territory, mg /m2/day) is not confirmed on the results of statistical analysis of the data for six different experimental sites (from 81 to 256 values of the index for each site). For the set of 243 values of the pollution index at the territory of a city, there is made an attempt of forecast of its possible extreme values not detected on the results of the snow sampling. For this, the linear dependence "pollution index - the number of points with the given pollution index" built in double logarithmic coordinates, is extrapolated into the area of high values of the pollution index.

Extreme-event geoelectric hazard maps: Chapter 9

Science.gov (United States)

Love, Jeffrey J.; Bedrosian, Paul A.

2018-01-01

Maps of geoelectric amplitude covering about half the continental United States are presented that will be exceeded, on average, once per century in response to an extreme-intensity geomagnetic disturbance. These maps are constructed using an empirical parameterization of induction: convolving latitude-dependent statistical maps of extreme-value geomagnetic disturbances, obtained from decades of 1-minute magnetic observatory data, with local estimates of Earth-surface impedance obtained at discrete geographic sites from magnetotelluric surveys. Geoelectric amplitudes are estimated for geomagnetic waveforms having a 240-s (and 1200-s) sinusoidal period and amplitudes over 10 min (1 h) that exceed a once-per-century threshold. As a result of the combination of geographic differences in geomagnetic variation and Earth-surface impedance, once-per-century geoelectric amplitudes span more than two orders of magnitude and are a highly granular function of location. Specifically for north-south 240-s induction, once-per-century geoelectric amplitudes across large parts of the United States have a median value of 0.34 V/km; for east-west variation, they have a median value of 0.23 V/km. In Northern Minnesota, amplitudes exceed 14.00 V/km for north-south geomagnetic variation (23.34 V/km for east-west variation), while just over 100 km away, amplitudes are only 0.08 V/km (0.02 V/km). At some sites in the northern-central United States, once-per-century geoelectric amplitudes exceed the 2 V/km realized in Québec during the March 1989 storm.

Brownian gas models for extreme-value laws

International Nuclear Information System (INIS)

Eliazar, Iddo

2013-01-01

In this paper we establish one-dimensional Brownian gas models for the extreme-value laws of Gumbel, Weibull, and Fréchet. A gas model is a countable collection of independent particles governed by common diffusion dynamics. The extreme-value laws are the universal probability distributions governing the affine scaling limits of the maxima and minima of ensembles of independent and identically distributed one-dimensional random variables. Using the recently introduced concept of stationary Poissonian intensities, we construct two gas models whose global statistical structures are stationary, and yield the extreme-value laws: a linear Brownian motion gas model for the Gumbel law, and a geometric Brownian motion gas model for the Weibull and Fréchet laws. The stochastic dynamics of these gas models are studied in detail, and closed-form analytical descriptions of their temporal correlation structures, their topological phase transitions, and their intrinsic first-passage-time fluxes are presented. (paper)

Temperature dependence of the short-range order parameter and the concentration dependence of the order disorder temperature for Ni-Pt and Ni-Fe systems in the improved statistical pseudopotential approximation

International Nuclear Information System (INIS)

Khwaja, F.A.

1980-08-01

The calculations for the temperature dependence of the first shell short-range order (SRO) parameter for Ni 3 Fe using the cubic approximation of Tahir Kheli, and the concentration dependence of order-disorder temperature Tsub(c) for Ni-Fe and Ni-Pt systems using the linear approximation, have been carried out in the framework of pseudopotential theory. It is shown that the cubic approximation yields a good agreement between the theoretical prediction of the α 1 and the experimental data. Results for the concentration dependence of the Tsub(c) show that improvements in the statistical pseudo-potential approach are essential to achieve a good agreement with experiment. (author)

Wind and Wave Setup Contributions to Extreme Sea Levels at a Tropical High Island: A Stochastic Cyclone Simulation Study for Apia, Samoa

Directory of Open Access Journals (Sweden)

Ron Karl Hoeke

2015-09-01

Full Text Available Wind-wave contributions to tropical cyclone (TC-induced extreme sea levels are known to be significant in areas with narrow littoral zones, particularly at oceanic islands. Despite this, little information exists in many of these locations to assess the likelihood of inundation, the relative contribution of wind and wave setup to this inundation, and how it may change with sea level rise (SLR, particularly at scales relevant to coastal infrastructure. In this study, we explore TC-induced extreme sea levels at spatial scales on the order of tens of meters at Apia, the capitol of Samoa, a nation in the tropical South Pacific with typical high-island fringing reef morphology. Ensembles of stochastically generated TCs (based on historical information are combined with numerical simulations of wind waves, storm-surge, and wave setup to develop high-resolution statistical information on extreme sea levels and local contributions of wind setup and wave setup. The results indicate that storm track and local morphological details lead to local differences in extreme sea levels on the order of 1 m at spatial scales of less than 1 km. Wave setup is the overall largest contributor at most locations; however, wind setup may exceed wave setup in some sheltered bays. When an arbitrary SLR scenario (+1 m is introduced, overall extreme sea levels are found to modestly decrease relative to SLR, but wave energy near the shoreline greatly increases, consistent with a number of other recent studies. These differences have implications for coastal adaptation strategies.

Extreme weather events and infectious disease outbreaks.

Science.gov (United States)

McMichael, Anthony J

2015-01-01

Human-driven climatic changes will fundamentally influence patterns of human health, including infectious disease clusters and epidemics following extreme weather events. Extreme weather events are projected to increase further with the advance of human-driven climate change. Both recent and historical experiences indicate that infectious disease outbreaks very often follow extreme weather events, as microbes, vectors and reservoir animal hosts exploit the disrupted social and environmental conditions of extreme weather events. This review article examines infectious disease risks associated with extreme weather events; it draws on recent experiences including Hurricane Katrina in 2005 and the 2010 Pakistan mega-floods, and historical examples from previous centuries of epidemics and 'pestilence' associated with extreme weather disasters and climatic changes. A fuller understanding of climatic change, the precursors and triggers of extreme weather events and health consequences is needed in order to anticipate and respond to the infectious disease risks associated with human-driven climate change. Post-event risks to human health can be constrained, nonetheless, by reducing background rates of persistent infection, preparatory action such as coordinated disease surveillance and vaccination coverage, and strengthened disaster response. In the face of changing climate and weather conditions, it is critically important to think in ecological terms about the determinants of health, disease and death in human populations.

Extremal dependencies and rank correlations in power law networks

NARCIS (Netherlands)

Volkovich, Y.; Litvak, Nelli; Zwart, B.; Jie, Z.

2009-01-01

We analyze dependencies in complex networks characterized by power laws (Web sample, Wikipedia sample and a preferential attachment graph) using statistical techniques from the extreme value theory and the theory of multivariate regular variation. To the best of our knowledge, this is the first

Distant Galaxy Clusters Hosting Extreme Central Galaxies

Science.gov (United States)

McDonald, Michael

2014-09-01

The recently-discovered Phoenix cluster harbors the most star-forming central cluster galaxy of any cluster in the known Universe, by nearly a factor of 10. This extreme system appears to be fulfilling early cooling flow predictions, although the lack of similar systems makes any interpretation difficult. In an attempt to find other "Phoenix-like" clusters, we have cross-correlated archival all-sky surveys (in which Phoenix was detected) and isolated 4 similarly-extreme systems which are also coincident in position and redshift with an overdensity of red galaxies. We propose here to obtain Chandra observations of these extreme, Phoenix-like systems, in order to confirm them as relaxed, rapidly-cooling galaxy clusters.

The problem of defining contemporary right-wing extremism in political theory

Directory of Open Access Journals (Sweden)

Đorić Marija

2016-01-01

Full Text Available The subject matter of research in this paper is theoretical controversy related to the definition of right-wing extremism. Given the fact that extremism is a variable, amorphous and insufficiently researched phenomenon, largely conditioned by time, space, political and cultural differences, there is a great confusion in the field of political science when defining right-wing extremism. The problem of researching right-wing extremism is additionally complicated by various terms that are being used in the contemporary literature as its synonyms, such as right-wing radicalism, neo-Fascism, ultra-radicalism, etc. In order to provide the most valid theoretical determination of right-wing extremism, the author provides a detailed analysis of all the components constituting this phenomenon and examines their causality. In the political praxis, the term extremism is extensively abused, which additionally complicates its determination. Videlicet, politicians often use term 'extremist' in order to discredit their political opponents. While during the French revolution aristocracy saw the bourgeoisie as extremists, the members of the working class later stated that the bourgeoisie were extremists. The problem lies in the fact that, in politics, extremists are not only the ones who use violence as modus operandi; indeed, it is also used by political opponents who do not belong to the extreme political option. Another aggravating factor in defining right-wing extremism is that many administrative and academic definitions do not make a clear distinction between extremism and related phenomena, such as terrorism, radicalism and populism. Extremism is most often equaled with terrorism, which gives rise to another problem in defining this phenomenon. The relation between extremism and terrorism is the relation of general and specific. Namely, every act of terrorism is concurrently considered to be an act of extremism, but not vice versa, given the fact that

On the applicability of extreme value statistics in the prediction of maximum pit depth in heavily corroded non-piggable buried pipelines

Energy Technology Data Exchange (ETDEWEB)

Alfonso, L. [Universidad Autonoma de la Ciudad de Mexico, Mexico D.F. 09790 (Mexico); Caleyo, F.; Hallen, J. M.; Araujo, J. [ESIQIE, Instituto Politecnico Nacional, Mexico D.F. (Mexico)

2010-07-01

Pitting corrosion entails serious risks in industrial plants, since a perforation resulting from a single pit can cause the failure of in-service components like water pipes, heat exchangers or oil tanks. A number of statistical methods have been suggested to estimate the maximum pit depth. Over the years, a successful application of extreme value analysis has been found in the application of the Gumbel distribution to predict the maximum pit depth from a smaller number of samples with small area. There is a lack of studies devoted to the applicability of the Gumbel method to the prediction of maximum pitting-corrosion depth. The aim of the work presented in this paper is to introduce a new strategy for the application of the Gumbel method in real pipelines. The methodology proposed is based on the fact that the clustered pattern of the pit depth distribution is less pronounced when the analysis is restricted to sections of the pipeline that exhibits similar characteristics.

Extremal black holes as exact string solutions

International Nuclear Information System (INIS)

Horowitz, G.T.; Tseytlin, A.A.

1994-01-01

We show that the leading order solution describing an extremal electrically charged black hole in string theory is, in fact, an exact solution to all orders in α' when interpreted in a Kaluza-Klein fashion. This follows from the observation that it can be obtained via dimensional reduction from a five-dimensional background which is proved to be an exact string solution

Evaluation of higher order statistics parameters for multi channel sEMG using different force levels.

Science.gov (United States)

Naik, Ganesh R; Kumar, Dinesh K

2011-01-01

The electromyograpy (EMG) signal provides information about the performance of muscles and nerves. The shape of the muscle signal and motor unit action potential (MUAP) varies due to the movement of the position of the electrode or due to changes in contraction level. This research deals with evaluating the non-Gaussianity in Surface Electromyogram signal (sEMG) using higher order statistics (HOS) parameters. To achieve this, experiments were conducted for four different finger and wrist actions at different levels of Maximum Voluntary Contractions (MVCs). Our experimental analysis shows that at constant force and for non-fatiguing contractions, probability density functions (PDF) of sEMG signals were non-Gaussian. For lesser MVCs (below 30% of MVC) PDF measures tends to be Gaussian process. The above measures were verified by computing the Kurtosis values for different MVCs.

Climate network analysis of regional precipitation extremes: The true story told by event synchronization

Science.gov (United States)

Odenweller, Adrian; Donner, Reik V.

2017-04-01

Over the last decade, complex network methods have been frequently used for characterizing spatio-temporal patterns of climate variability from a complex systems perspective, yielding new insights into time-dependent teleconnectivity patterns and couplings between different components of the Earth climate. Among the foremost results reported, network analyses of the synchronicity of extreme events as captured by the so-called event synchronization have been proposed to be powerful tools for disentangling the spatio-temporal organization of particularly extreme rainfall events and anticipating the timing of monsoon onsets or extreme floodings. Rooted in the analysis of spike train synchrony analysis in the neurosciences, event synchronization has the great advantage of automatically classifying pairs of events arising at two distinct spatial locations as temporally close (and, thus, possibly statistically - or even dynamically - interrelated) or not without the necessity of selecting an additional parameter in terms of a maximally tolerable delay between these events. This consideration is conceptually justified in case of the original application to spike trains in electroencephalogram (EEG) recordings, where the inter-spike intervals show relatively narrow distributions at high temporal sampling rates. However, in case of climate studies, precipitation extremes defined by daily precipitation sums exceeding a certain empirical percentile of their local distribution exhibit a distinctively different type of distribution of waiting times between subsequent events. This raises conceptual concerns if event synchronization is still appropriate for detecting interlinkages between spatially distributed precipitation extremes. In order to study this problem in more detail, we employ event synchronization together with an alternative similarity measure for event sequences, event coincidence rates, which requires a manual setting of the tolerable maximum delay between two

Extreme conditions (p, T, H)

Energy Technology Data Exchange (ETDEWEB)

Mesot, J [Lab. for Neutron Scattering ETH Zurich, Zurich (Switzerland) and Paul Scherrer Institute, Villigen (Switzerland)

1996-11-01

The aim of this paper is to summarize the sample environment which will be accessible at the SINQ. In order to illustrate the type of experiments which will be feasible under extreme conditions of temperature, magnetic field and pressure at the SINQ a few selected examples are also given. (author) 7 figs., 14 refs.

Near-extreme system condition and near-extreme remaining useful time for a group of products

International Nuclear Information System (INIS)

Wang, Hai-Kun; Li, Yan-Feng; Huang, Hong-Zhong; Jin, Tongdan

2017-01-01

When a group of identical products is operating in field, the aggregation of failures is a catastrophe to engineers and customers who strive to develop reliable and safe products. In order to avoid a swarm of failures in a short time, it is essential to measure the degree of dispersion from different failure times in a group of products to the first failure time. This phenomenon is relevant to the crowding of system conditions near the worst one among a group of products. The group size in this paper represents a finite number of products, instead of infinite number or a single product. We evaluate the reliability of the product fleet from two aspects. First, we define near-extreme system condition and near-extreme failure time for offline solutions, which means no online observations. Second, we apply them to a continuous degradation system that breaks down when it reaches a soft failure threshold. By using particle filtering in the framework of prognostics and health management for a group of products, we aim to estimate near-extreme system condition and further predict the remaining useful life (RUL) using online solutions. Numerical examples are provided to demonstrate the effectiveness of the proposed method. - Highlights: • The aggregation of failures is measured for a group of identical products. • The crowding of failures is quantitated by the near-extreme evaluations. • Near-extreme system condition are given for offline solutions. • Near-extreme remaining useful time are provided for online solutions.

An Update on Statistical Boosting in Biomedicine

Directory of Open Access Journals (Sweden)

Andreas Mayr

2017-01-01

Full Text Available Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting. In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

On the Fluctuations that Order and Frustrate Liquid Water

Science.gov (United States)

Limmer, David Tyler

At ambient conditions, water sits close to phase coexistence with its crystal. More so than in many other materials, this fact is manifested in the fluctuations that maintain a large degree of local order in the liquid. These fluctuations and how they result in long-ranged order, or its absence, are emergent features of many interacting molecules. Their study therefore requires using the tools of statistical mechanics for their their systematic understanding. In this dissertation we develop such an understanding. In particular, we focus on collective behavior that emerges in liquid and solid water. At room temperatures, the thermophysical properties of water are quantified and rationalized with simple molecular models. A key feature of these models is the correct characterization of the competition between entropic forces of packing and the energetic preference for tetrahedral order. At cold temperatures, the properties of ice surfaces are studied with statistical field theory. The theory we develop for the long wavelength features of ice interfaces allows us to explain the existence of a premelting layer on the surface of ice and the stability of ice in confinement. In between these extremes, the dynamics of supercooled water are considered. A detailed theory for the early stages of coarsening is developed and used to explain the peculiar observation of a transient second liquid state of water. When coarsening dynamics are arrested, the result is the formation of a glassy states of water. We show that out-of-equilibrium the phase diagram for supercooled water exhibits a rich amount of structure, including a triple point between two glass phases of water and the liquid. At the end, we explore possible technological implications for the interplay between ordering and frustration in studies of water at metal interfaces.

Extreme value prediction of the wave-induced vertical bending moment in large container ships

DEFF Research Database (Denmark)

Andersen, Ingrid Marie Vincent; Jensen, Jørgen Juncher

2015-01-01

increase the extreme hull girder response significantly. Focus in the present paper is on the influence of the hull girder flexibility on the extreme response amidships, namely the wave-induced vertical bending moment (VBM) in hogging, and the prediction of the extreme value of the same. The analysis...... in the present paper is based on time series of full scale measurements from three large container ships of 8600, 9400 and 14000 TEU. When carrying out the extreme value estimation the peak-over-threshold (POT) method combined with an appropriate extreme value distribution is applied. The choice of a proper...... threshold level as well as the statistical correlation between clustered peaks influence the extreme value prediction and are taken into consideration in the present paper....

Outliers and Extremes: Dragon-Kings or Dragon-Fools?

Science.gov (United States)

Schertzer, D. J.; Tchiguirinskaia, I.; Lovejoy, S.

2012-12-01

Geophysics seems full of monsters like Victor Hugo's Court of Miracles and monstrous extremes have been statistically considered as outliers with respect to more normal events. However, a characteristic magnitude separating abnormal events from normal ones would be at odd with the generic scaling behaviour of nonlinear systems, contrary to "fat tailed" probability distributions and self-organized criticality. More precisely, it can be shown [1] how the apparent monsters could be mere manifestations of a singular measure mishandled as a regular measure. Monstrous fluctuations are the rule, not outliers and they are more frequent than usually thought up to the point that (theoretical) statistical moments can easily be infinite. The empirical estimates of the latter are erratic and diverge with sample size. The corresponding physics is that intense small scale events cannot be smoothed out by upscaling. However, based on a few examples, it has also been argued [2] that one should consider "genuine" outliers of fat tailed distributions so monstrous that they can be called "dragon-kings". We critically analyse these arguments, e.g. finite sample size and statistical estimates of the largest events, multifractal phase transition vs. more classical phase transition. We emphasize the fact that dragon-kings are not needed in order that the largest events become predictable. This is rather reminiscent of the Feast of Fools picturesquely described by Victor Hugo. [1] D. Schertzer, I. Tchiguirinskaia, S. Lovejoy et P. Hubert (2010): No monsters, no miracles: in nonlinear sciences hydrology is not an outlier! Hydrological Sciences Journal, 55 (6) 965 - 979. [2] D. Sornette (2009): Dragon-Kings, Black Swans and the Prediction of Crises. International Journal of Terraspace Science and Engineering 1(3), 1-17.

Sea Extremes: Integrated impact assessment in coastal climate adaptation

DEFF Research Database (Denmark)

Sørensen, Carlo Sass; Knudsen, Per; Broge, Niels

2016-01-01

protection measures, topography, and infrastructure to provide a more complete picture of the water-related impact from climate change at an exposed coastal location. Results show that future sea extremes evaluated from extreme value statistics may, indeed, have a large impact. The integrated effects from......We investigate effects of sea level rise and a change in precipitation pattern on coastal flooding hazards. Historic and present in situ and satellite data of water and groundwater levels, precipitation, vertical ground motion, geology,and geotechnical soil properties are combined with flood...... research advances and projections for the future are updated....

Aspects of statistical model for multifragmentation

International Nuclear Information System (INIS)

Bhattacharyya, P.; Das Gupta, S.; Mekjian, A. Z.

1999-01-01

We deal with two different aspects of an exactly soluble statistical model of fragmentation. First we show, using zero range force and finite temperature Thomas-Fermi theory, that a common link can be found between finite temperature mean field theory and the statistical fragmentation model. We show the latter naturally arises in the spinodal region. Next we show that although the exact statistical model is a canonical model and uses temperature, microcanonical results which use constant energy rather than constant temperature can also be obtained from the canonical model using saddle-point approximation. The methodology is extremely simple to implement and at least in all the examples studied in this work is very accurate. (c) 1999 The American Physical Society

Equilibrium statistical mechanics

CERN Document Server

Jackson, E Atlee

2000-01-01

Ideal as an elementary introduction to equilibrium statistical mechanics, this volume covers both classical and quantum methodology for open and closed systems. Introductory chapters familiarize readers with probability and microscopic models of systems, while additional chapters describe the general derivation of the fundamental statistical mechanics relationships. The final chapter contains 16 sections, each dealing with a different application, ordered according to complexity, from classical through degenerate quantum statistical mechanics. Key features include an elementary introduction t

Higher-Order Statistics for the Detection of Small Objects in a Noisy Background Application on Sonar Imaging

Directory of Open Access Journals (Sweden)

M. Amate

2007-01-01

Full Text Available An original algorithm for the detection of small objects in a noisy background is proposed. Its application to underwater objects detection by sonar imaging is addressed. This new method is based on the use of higher-order statistics (HOS that are locally estimated on the images. The proposed algorithm is divided into two steps. In a first step, HOS (skewness and kurtosis are estimated locally using a square sliding computation window. Small deterministic objects have different statistical properties from the background they are thus highlighted. The influence of the signal-to-noise ratio (SNR on the results is studied in the case of Gaussian noise. Mathematical expressions of the estimators and of the expected performances are derived and are experimentally confirmed. In a second step, the results are focused by a matched filter using a theoretical model. This enables the precise localization of the regions of interest. The proposed method generalizes to other statistical distributions and we derive the theoretical expressions of the HOS estimators in the case of a Weibull distribution (both when only noise is present or when a small deterministic object is present within the filtering window. This enables the application of the proposed technique to the processing of synthetic aperture sonar data containing underwater mines whose echoes have to be detected and located. Results on real data sets are presented and quantitatively evaluated using receiver operating characteristic (ROC curves.

Delivery of the extremely low-birth- weight vertex-presenting baby ...

African Journals Online (AJOL)

2010-12-02

Dec 2, 2010 ... rise in the caesarean section rate.1 This rise has been disproportionate to ... a possible extremely low-birth-weight infant the risks of mortality and short- and .... the US Health Statistics data from 1999 to 2000 using multivariate ...

Vulnerability assessment of Central-East Sardinia (Italy to extreme rainfall events

Directory of Open Access Journals (Sweden)

A. Bodini

2010-01-01

Full Text Available In Sardinia (Italy, the highest frequency of extreme events is recorded in the Central-East area (3–4 events per year. The presence of high and steep mountains near the sea on the central and south-eastern coast, causes an East-West precipitation gradient in autumn especially, due to hot and moist currents coming from Africa. Soil structure and utilization make this area highly vulnerable to flash flooding and landslides. The specific purpose of this work is to provide a description of the heavy rainfall phenomenon on a statistical basis. The analysis mainly focuses on i the existence of trends in heavy rainfall and ii the characterization of the distribution of extreme events. First, to study possible trends in extreme events a few indices have been analyzed by the linear regression test. The analysis has been carried out at annual and seasonal scales. Then, extreme values analysis has been carried out by fitting a Generalized Pareto Distribution (GPD to the data. As far as trends are concerned, different results are obtained at the two temporal scales: significant trends are obtained at the seasonal scale which are masked at the annual scale. By combining trend analysis and GPD analysis, the vulnerability of the study area to the occurrence of heavy rainfall has been characterized. Therefore, this work might support the improvement of land use planning and the application of suitable prevention systems. Future work will consider the extension of the analysis to all Sardinia and the application of statistical methods taking into account the spatial correlation of extreme events.

Variability of morphometric parameters of feet in various forms of lower extremities

Directory of Open Access Journals (Sweden)

Konnova O.V.

2014-12-01

Full Text Available Purpose: to identify the various forms of lower extremities variability of linear and angular parameters of feet in girls aged 17-19 years. Material and Methods. The object of the study included 242 students from Saratov State Medical University, 17—19 years. Foot digital plantography photometric device-software complex «Plantvizor» and measuring distances between sibling points of lower extremities to highlight their forms have been used as a method of research. Results. 8 forms of lower extremities, among which half per cent occurs in isolated form, valgus-direct from the mil-lennim clearance opening and a trapezoidal shape of lower extremities varus. In all forms of lower extremities morphometric parameters of feet and ratio of statistically significant differences in various forms of lower extremities have been studied. Conclusion. Anatomical basis for operational adjustment of axial disorders of tibiae and its influence on morphofunctional state of foot can be resulted from the study.

Arctic sea ice, Eurasia snow, and extreme winter haze in China.

Science.gov (United States)

Zou, Yufei; Wang, Yuhang; Zhang, Yuzhong; Koo, Ja-Ho

2017-03-01

The East China Plains (ECP) region experienced the worst haze pollution on record for January in 2013. We show that the unprecedented haze event is due to the extremely poor ventilation conditions, which had not been seen in the preceding three decades. Statistical analysis suggests that the extremely poor ventilation conditions are linked to Arctic sea ice loss in the preceding autumn and extensive boreal snowfall in the earlier winter. We identify the regional circulation mode that leads to extremely poor ventilation over the ECP region. Climate model simulations indicate that boreal cryospheric forcing enhances the regional circulation mode of poor ventilation in the ECP region and provides conducive conditions for extreme haze such as that of 2013. Consequently, extreme haze events in winter will likely occur at a higher frequency in China as a result of the changing boreal cryosphere, posing difficult challenges for winter haze mitigation but providing a strong incentive for greenhouse gas emission reduction.

Structure of extremely nanosized and confined In-O species in ordered porous materials

International Nuclear Information System (INIS)

Ramallo-Lopez, J.M.; Renteria, M.; Miro, E.E.; Requejo, F.G.; Traverse, A.

2003-01-01

Perturbed-angular correlation, x-ray absorption, and small-angle x-ray scattering spectroscopies were suitably combined to elucidate the local structure of highly diluted and dispersed InO x species confined in the porous of the ZSM5 zeolite. This novel approach allow us to determined the structure of extremely nanosized In-O species exchanged inside the 10-atom-ring channel of the zeolite, and to quantify the amount of In 2 O 3 crystallites deposited onto the external zeolite surface

Fractional statistics and the butterfly effect

International Nuclear Information System (INIS)

Gu, Yingfei; Qi, Xiao-Liang

2016-01-01

Fractional statistics and quantum chaos are both phenomena associated with the non-local storage of quantum information. In this article, we point out a connection between the butterfly effect in (1+1)-dimensional rational conformal field theories and fractional statistics in (2+1)-dimensional topologically ordered states. This connection comes from the characterization of the butterfly effect by the out-of-time-order-correlator proposed recently. We show that the late-time behavior of such correlators is determined by universal properties of the rational conformal field theory such as the modular S-matrix and conformal spins. Using the bulk-boundary correspondence between rational conformal field theories and (2+1)-dimensional topologically ordered states, we show that the late time behavior of out-of-time-order-correlators is intrinsically connected with fractional statistics in the topological order. We also propose a quantitative measure of chaos in a rational conformal field theory, which turns out to be determined by the topological entanglement entropy of the corresponding topological order.

Fractional statistics and the butterfly effect

Energy Technology Data Exchange (ETDEWEB)

Gu, Yingfei; Qi, Xiao-Liang [Department of Physics, Stanford University,Stanford, CA 94305 (United States)

2016-08-23

Fractional statistics and quantum chaos are both phenomena associated with the non-local storage of quantum information. In this article, we point out a connection between the butterfly effect in (1+1)-dimensional rational conformal field theories and fractional statistics in (2+1)-dimensional topologically ordered states. This connection comes from the characterization of the butterfly effect by the out-of-time-order-correlator proposed recently. We show that the late-time behavior of such correlators is determined by universal properties of the rational conformal field theory such as the modular S-matrix and conformal spins. Using the bulk-boundary correspondence between rational conformal field theories and (2+1)-dimensional topologically ordered states, we show that the late time behavior of out-of-time-order-correlators is intrinsically connected with fractional statistics in the topological order. We also propose a quantitative measure of chaos in a rational conformal field theory, which turns out to be determined by the topological entanglement entropy of the corresponding topological order.

Mediatized Extreme Right Activism and Discourse

DEFF Research Database (Denmark)

Peters, Rikke Alberg

2015-01-01

This paper presents a case study of the German neo-fascist network The Immortals (Die Unsterblichen) who in 2011 performed a flash-mob disseminated on YouTube for the so- called ‘Become Immortal’ campaign. The street protest was designed for and adapted to the specific characteristics of online...... activism. It is a good example of how new contentious action repertoires in which online and street activism intertwine have also spread to extreme right groups. Despite its neo-fascist and extreme right content the ‘Become Immortal’ campaign serves as an illustrative case for the study of mediated...... and mediatized activism. In order to analyse of the protest form, the visual aesthetics and the discourse of ‘The Immortals’, the paper mobilises two concepts from media and communication studies: mediation and mediatization. It will be argued that that the current transformation of the extreme right: that is...

A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation

Science.gov (United States)

Byun, K.; Hamlet, A. F.

2017-12-01

There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.

Does extreme precipitation intensity depend on the emissions scenario?

Science.gov (United States)

Pendergrass, Angeline; Lehner, Flavio; Sanderson, Benjamin; Xu, Yangyang

2016-04-01

The rate of increase of global-mean precipitation per degree surface temperature increase differs for greenhouse gas and aerosol forcings, and therefore depends on the change in composition of the emissions scenario used to drive climate model simulations for the remainder of the century. We investigate whether or not this is also the case for extreme precipitation simulated by a multi-model ensemble driven by four realistic emissions scenarios. In most models, the rate of increase of maximum annual daily rainfall per degree global warming in the multi-model ensemble is statistically indistinguishable across the four scenarios, whether this extreme precipitation is calculated globally, over all land, or over extra-tropical land. These results indicate that, in most models, extreme precipitation depends on the total amount of warming and does not depend on emissions scenario, in contrast to mean precipitation.

Probability distribution of extreme share returns in Malaysia

Science.gov (United States)

Zin, Wan Zawiah Wan; Safari, Muhammad Aslam Mohd; Jaaman, Saiful Hafizah; Yie, Wendy Ling Shin

2014-09-01

The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively.

Invited Article: Visualisation of extreme value events in optical communications

Science.gov (United States)

Derevyanko, Stanislav; Redyuk, Alexey; Vergeles, Sergey; Turitsyn, Sergei

2018-06-01

Fluctuations of a temporal signal propagating along long-haul transoceanic scale fiber links can be visualised in the spatio-temporal domain drawing visual analogy with ocean waves. Substantial overlapping of information symbols or use of multi-frequency signals leads to strong statistical deviations of local peak power from an average signal power level. We consider long-haul optical communication systems from this unusual angle, treating them as physical systems with a huge number of random statistical events, including extreme value fluctuations that potentially might affect the quality of data transmission. We apply the well-established concepts of adaptive wavefront shaping used in imaging through turbid medium to detect the detrimental phase modulated sequences in optical communications that can cause extreme power outages (rare optical waves of ultra-high amplitude) during propagation down the ultra-long fiber line. We illustrate the concept by a theoretical analysis of rare events of high-intensity fluctuations—optical freak waves, taking as an example an increasingly popular optical frequency division multiplexing data format where the problem of high peak to average power ratio is the most acute. We also show how such short living extreme value spikes in the optical data streams are affected by nonlinearity and demonstrate the negative impact of such events on the system performance.

Example of a Non-standard Extreme Value Law

Czech Academy of Sciences Publication Activity Database

Haydn, N.; Kupsa, Michal

2015-01-01

Roč. 35, č. 6 (2015), s. 1902-1912 ISSN 0143-3857 Institutional support: RVO:67985556 Keywords : extreme-value law * rotations of unit circle * non-mixing systems * discrete law * Gumbel distribution * Weibull distribution * Frechet distribution * return times Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.983, year: 2015 http://library.utia.cas.cz/separaty/2014/SI/kupsa-0434480.pdf

The JEM-EUSO mission to explore the extreme Universe

International Nuclear Information System (INIS)

Kajino, Fumiyoshi

2010-01-01

Accommodated on the Japanese Experiment Module (JEM) of the International Space Station (ISS), the Extreme Universe Space Observatory JEM-EUSO will utilize the Earth's atmosphere as a giant detector of the extreme energy cosmic rays; the most energetic particles coming from the Universe. Looking downward the Earth from Space, JEM-EUSO will detect such particles by observing the fluorescence and Cherenkov photons produced during their pass in the atmosphere. The main objective of JEM-EUSO is doing astronomy and astrophysics through the particle channel with extreme energies above several times 10 19 eV with a significant statistics beyond the Greisen-Zatsepin-Kuzmin (GZK) cut-off. Moreover, JEM-EUSO could observe extremely high energy neutrinos. JEM-EUSO has been designed to operate for more than 3 years onboard the ISS orbiting around the Earth every 90 min at an altitude of about 400 km. JAXA has selected JEM-EUSO as one of the mission candidates of the second phase utilization of JEM/EF for the launch in mid 2010s.

Extreme waves at Filyos, southern Black Sea

Directory of Open Access Journals (Sweden)

E. Bilyay

2011-03-01

Full Text Available A wave measurement project was carried out for a new port planned in Filyos, in the Western Black Sea region of Turkey. The measurement at a depth of 12.5 m lasted for a period of two years and 7949 records were obtained. During the analysis, it was noticed that there were 209 records in which H/H_s ratio was higher than 2.0. These higher waves in a record are called extreme waves in this study. Although the purpose of wave measurement is not to investigate extreme waves, it is believed that studying these unexpected waves could be interesting. Therefore, detailed statistical and spectral analyses on the extreme waves were done for the records. The analyses results show that the distribution of surface profiles of the records containing extreme waves deviates from Gaussian distribution with the negative skewness changing between –0.01 and –0.4 and with the high kurtosis in the range of 3.1–4.2. Although the probability of occurrence of the extreme waves is over-predicted by the Rayleigh distribution, a higher ratio of H_s/η_rms indicates that the wave height distribution can be represented by Rayleigh. The average value of the slope of the frequency spectrum at the high frequency range is proportional to f^–9 which is much steeper than the typical wind-wave frequency power law, f^{–4, –5}. The directional spreading is measured with the parameter S_max and it is in the range of 5–70 for the extreme wave records. The wave and current interaction was also investigated and it was found that in most cases, extreme waves occur when the wave and the current are almost aligned. Furthermore, it is observed that extreme waves appear within a group of high waves.

Causes of Glacier Melt Extremes in the Alps Since 1949

Science.gov (United States)

Thibert, E.; Dkengne Sielenou, P.; Vionnet, V.; Eckert, N.; Vincent, C.

2018-01-01

Recent record-breaking glacier melt values are attributable to peculiar extreme events and long-term warming trends that shift averages upward. Analyzing one of the world's longest mass balance series with extreme value statistics, we show that detrending melt anomalies makes it possible to disentangle these effects, leading to a fairer evaluation of the return period of melt extreme values such as 2003, and to characterize them by a more realistic bounded behavior. Using surface energy balance simulations, we show that three independent drivers control melt: global radiation, latent heat, and the amount of snow at the beginning of the melting season. Extremes are governed by large deviations in global radiation combined with sensible heat. Long-term trends are driven by the lengthening of melt duration due to earlier and longer-lasting melting of ice along with melt intensification caused by trends in long-wave irradiance and latent heat due to higher air moisture.

Statistical Pattern Recognition

CERN Document Server

Webb, Andrew R

2011-01-01

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

(When and where) Do extreme climate events trigger extreme ecosystem responses? - Development and initial results of a holistic analysis framework

Science.gov (United States)

Hauber, Eva K.; Donner, Reik V.

2015-04-01

In the context of ongoing climate change, extremes are likely to increase in magnitude and frequency. One of the most important consequences of these changes is that the associated ecological risks and impacts are potentially rising as well. In order to better anticipate and understand these impacts, it therefore becomes more and more crucial to understand the general connection between climate extremes and the response and functionality of ecosystems. Among other region of the world, Europe presents an excellent test case for studies concerning the interaction between climate and biosphere, since it lies in the transition region between cold polar and warm tropical air masses and thus covers a great variety of different climatic zones and associated terrestrial ecosystems. The large temperature differences across the continent make this region particularly interesting for investigating the effects of climate change on biosphere-climate interactions. However, previously used methods for defining an extreme event typically disregard the necessity of taking seasonality as well as seasonal variance appropriately into account. Furthermore, most studies have focused on the impacts of individual extreme events instead of considering a whole inventory of extremes with their respective spatio-temporal extents. In order to overcome the aforementioned research gaps, this work introduces a new approach to studying climate-biosphere interactions associated with extreme events, which comprises three consecutive steps: (1) Since Europe exhibits climatic conditions characterized by marked seasonality, a novel method is developed to define extreme events taking into account the seasonality in all quantiles of the probability distribution of the respective variable of interest. This is achieved by considering kernel density estimates individually for each observation date during the year, including the properly weighted information from adjacent dates. By this procedure, we obtain

Extreme pressure differences at 0900 NZST and winds across New Zealand

Science.gov (United States)

Salinger, M. James; Griffiths, Georgina M.; Gosai, Ashmita

2005-07-01

Trends in extremes in station daily sea-level pressure differences at 0900 NZST are examined, and extreme daily wind gusts, across New Zealand, since the 1960s. Annual time series were examined (with indices of magnitude and frequency over threshold percentiles) from the daily indices selected. These follow from earlier indices of normalized monthly mean sea-level pressure differences between station pairs, except the daily indices are not normalized. The frequency statistics quantify the number of extreme zonal (westerly and easterly), or extreme meridional (southerly or northerly), pressure gradient events. The frequency and magnitude of extreme westerly episodes has increased slightly over New Zealand, with a significant increase in the westerly extremes to the south of New Zealand. In contrast, the magnitude and frequency of easterly extremes has decreased over New Zealand, but increased to the south, with some trends weakly significant. The frequency and magnitude of daily southerly extremes has decreased significantly in the region.Extreme daily wind gust events at key climate stations in New Zealand and at Hobart, Australia, are highly likely to be associated with an extreme daily pressure difference. The converse was less likely to hold: extreme wind gusts were not always observed on days with extreme daily pressure difference, probably due to the strong influence that topography has on localized station winds. Significant correlations exist between the frequency indices and both annual-average mean sea-level pressures around the Australasian region and annual-average sea surface temperature (SST) anomalies in the Southern Hemisphere. These correlations are generally stronger for indices of extreme westerly or extreme southerly airflows. Annual-average pressures in the Tasman Sea or Southern Ocean are highly correlated to zonal indices (frequency of extreme westerlies). SST anomalies in the NINO3 region or on either side of the South Island are

RELIGIOUS EXTREMISM AS A CHALLENGE TO TERTIARY ...

African Journals Online (AJOL)

IK

2016-07-01

Jul 1, 2016 ... agenda and manipulate their gullible followers in order to impose their .... So far 165 children, some of them not up to 9 months old, have been .... If extremism may be easily implemented in the Nigerian soil, with the dire.

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

Science.gov (United States)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

Exactly soluble local bosonic cocycle models, statistical transmutation, and simplest time-reversal symmetric topological orders in 3+1 dimensions

Science.gov (United States)

Wen, Xiao-Gang

2017-05-01

We propose a generic construction of exactly soluble local bosonic models that realize various topological orders with gappable boundaries. In particular, we construct an exactly soluble bosonic model that realizes a (3+1)-dimensional [(3+1)D] Z2-gauge theory with emergent fermionic Kramers doublet. We show that the emergence of such a fermion will cause the nucleation of certain topological excitations in space-time without pin+ structure. The exactly soluble model also leads to a statistical transmutation in (3+1)D. In addition, we construct exactly soluble bosonic models that realize 2 types of time-reversal symmetry-enriched Z2 topological orders in 2+1 dimensions, and 20 types of simplest time-reversal symmetry-enriched topological (SET) orders which have only one nontrivial pointlike and stringlike topological excitation. Many physical properties of those topological states are calculated using the exactly soluble models. We find that some time-reversal SET orders have pointlike excitations that carry Kramers doublet, a fractionalized time-reversal symmetry. We also find that some Z2 SET orders have stringlike excitations that carry anomalous (nononsite) Z2 symmetry, which can be viewed as a fractionalization of Z2 symmetry on strings. Our construction is based on cochains and cocycles in algebraic topology, which is very versatile. In principle, it can also realize emergent topological field theory beyond the twisted gauge theory.

New Closed-Form Results on Ordered Statistics of Partial Sums of Gamma Random Variables and its Application to Performance Evaluation in the Presence of Nakagami Fading

KAUST Repository

Nam, Sung Sik

2017-06-19

Complex wireless transmission systems require multi-dimensional joint statistical techniques for performance evaluation. Here, we first present the exact closed-form results on order statistics of any arbitrary partial sums of Gamma random variables with the closedform results of core functions specialized for independent and identically distributed Nakagami-m fading channels based on a moment generating function-based unified analytical framework. These both exact closed-form results have never been published in the literature. In addition, as a feasible application example in which our new offered derived closed-form results can be applied is presented. In particular, we analyze the outage performance of the finger replacement schemes over Nakagami fading channels as an application of our method. Note that these analysis results are directly applicable to several applications, such as millimeter-wave communication systems in which an antenna diversity scheme operates using an finger replacement schemes-like combining scheme, and other fading scenarios. Note also that the statistical results can provide potential solutions for ordered statistics in any other research topics based on Gamma distributions or other advanced wireless communications research topics in the presence of Nakagami fading.

STATLIB, Interactive Statistics Program Library of Tutorial System

International Nuclear Information System (INIS)

Anderson, H.E.

1986-01-01

1 - Description of program or function: STATLIB is a conversational statistical program library developed in conjunction with a Sandia National Laboratories applied statistics course intended for practicing engineers and scientists. STATLIB is a group of 15 interactive, argument-free, statistical routines. Included are analysis of sensitivity tests; sample statistics for the normal, exponential, hypergeometric, Weibull, and extreme value distributions; three models of multiple regression analysis; x-y data plots; exact probabilities for RxC tables; n sets of m permuted integers in the range 1 to m; simple linear regression and correlation; K different random integers in the range m to n; and Fisher's exact test of independence for a 2 by 2 contingency table. Forty-five other subroutines in the library support the basic 15

On the identification of Dragon Kings among extreme-valued outliers

Science.gov (United States)

Riva, M.; Neuman, S. P.; Guadagnini, A.

2013-07-01

Extreme values of earth, environmental, ecological, physical, biological, financial and other variables often form outliers to heavy tails of empirical frequency distributions. Quite commonly such tails are approximated by stretched exponential, log-normal or power functions. Recently there has been an interest in distinguishing between extreme-valued outliers that belong to the parent population of most data in a sample and those that do not. The first type, called Gray Swans by Nassim Nicholas Taleb (often confused in the literature with Taleb's totally unknowable Black Swans), is drawn from a known distribution of the tails which can thus be extrapolated beyond the range of sampled values. However, the magnitudes and/or space-time locations of unsampled Gray Swans cannot be foretold. The second type of extreme-valued outliers, termed Dragon Kings by Didier Sornette, may in his view be sometimes predicted based on how other data in the sample behave. This intriguing prospect has recently motivated some authors to propose statistical tests capable of identifying Dragon Kings in a given random sample. Here we apply three such tests to log air permeability data measured on the faces of a Berea sandstone block and to synthetic data generated in a manner statistically consistent with these measurements. We interpret the measurements to be, and generate synthetic data that are, samples from α-stable sub-Gaussian random fields subordinated to truncated fractional Gaussian noise (tfGn). All these data have frequency distributions characterized by power-law tails with extreme-valued outliers about the tail edges.

On the identification of Dragon Kings among extreme-valued outliers

Directory of Open Access Journals (Sweden)

M. Riva

2013-07-01

Full Text Available Extreme values of earth, environmental, ecological, physical, biological, financial and other variables often form outliers to heavy tails of empirical frequency distributions. Quite commonly such tails are approximated by stretched exponential, log-normal or power functions. Recently there has been an interest in distinguishing between extreme-valued outliers that belong to the parent population of most data in a sample and those that do not. The first type, called Gray Swans by Nassim Nicholas Taleb (often confused in the literature with Taleb's totally unknowable Black Swans, is drawn from a known distribution of the tails which can thus be extrapolated beyond the range of sampled values. However, the magnitudes and/or space–time locations of unsampled Gray Swans cannot be foretold. The second type of extreme-valued outliers, termed Dragon Kings by Didier Sornette, may in his view be sometimes predicted based on how other data in the sample behave. This intriguing prospect has recently motivated some authors to propose statistical tests capable of identifying Dragon Kings in a given random sample. Here we apply three such tests to log air permeability data measured on the faces of a Berea sandstone block and to synthetic data generated in a manner statistically consistent with these measurements. We interpret the measurements to be, and generate synthetic data that are, samples from α-stable sub-Gaussian random fields subordinated to truncated fractional Gaussian noise (tfGn. All these data have frequency distributions characterized by power-law tails with extreme-valued outliers about the tail edges.

Statistical complexity without explicit reference to underlying probabilities

Science.gov (United States)

Pennini, F.; Plastino, A.

2018-06-01

We show that extremely simple systems of a not too large number of particles can be simultaneously thermally stable and complex. To such an end, we extend the statistical complexity's notion to simple configurations of non-interacting particles, without appeal to probabilities, and discuss configurational properties.

A Fractional Lower Order Statistics-Based MIMO Detection Method in Impulse Noise for Power Line Channel

Directory of Open Access Journals (Sweden)

CHEN, Z.

2014-11-01

Full Text Available Impulse noise in power line communication (PLC channel seriously degrades the performance of Multiple-Input Multiple-Output (MIMO system. To remedy this problem, a MIMO detection method based on fractional lower order statistics (FLOS for PLC channel with impulse noise is proposed in this paper. The alpha stable distribution is used to model impulse noise, and FLOS is applied to construct the criteria of MIMO detection. Then the optimal detection solution is obtained by recursive least squares algorithm. Finally, the transmitted signals in PLC MIMO system are restored with the obtained detection matrix. The proposed method does not require channel estimation and has low computational complexity. The simulation results show that the proposed method has a better PLC MIMO detection performance than the existing ones under impulsive noise environment.

Prediction and reconstruction of future and missing unobservable modified Weibull lifetime based on generalized order statistics

Directory of Open Access Journals (Sweden)

Amany E. Aly

2016-04-01

Full Text Available When a system consisting of independent components of the same type, some appropriate actions may be done as soon as a portion of them have failed. It is, therefore, important to be able to predict later failure times from earlier ones. One of the well-known failure distributions commonly used to model component life, is the modified Weibull distribution (MWD. In this paper, two pivotal quantities are proposed to construct prediction intervals for future unobservable lifetimes based on generalized order statistics (gos from MWD. Moreover, a pivotal quantity is developed to reconstruct missing observations at the beginning of experiment. Furthermore, Monte Carlo simulation studies are conducted and numerical computations are carried out to investigate the efficiency of presented results. Finally, two illustrative examples for real data sets are analyzed.

Return period curves for extreme 5-min rainfall amounts at the Barcelona urban network

Science.gov (United States)

Lana, X.; Casas-Castillo, M. C.; Serra, C.; Rodríguez-Solà, R.; Redaño, A.; Burgueño, A.; Martínez, M. D.

2018-03-01

Heavy rainfall episodes are relatively common in the conurbation of Barcelona and neighbouring cities (NE Spain), usually due to storms generated by convective phenomena in summer and eastern and south-eastern advections in autumn. Prevention of local flood episodes and right design of urban drainage have to take into account the rainfall intensity spread instead of a simple evaluation of daily rainfall amounts. The database comes from 5-min rain amounts recorded by tipping buckets in the Barcelona urban network along the years 1994-2009. From these data, extreme 5-min rain amounts are selected applying the peaks-over-threshold method for thresholds derived from both 95% percentile and the mean excess plot. The return period curves are derived from their statistical distribution for every gauge, describing with detail expected extreme 5-min rain amounts across the urban network. These curves are compared with those derived from annual extreme time series. In this way, areas in Barcelona submitted to different levels of flood risk from the point of view of rainfall intensity are detected. Additionally, global time trends on extreme 5-min rain amounts are quantified for the whole network and found as not statistically significant.

Higher-order organisation of extremely amplified, potentially functional and massively methylated 5S rDNA in European pikes (Esox sp.).

Science.gov (United States)

Symonová, Radka; Ocalewicz, Konrad; Kirtiklis, Lech; Delmastro, Giovanni Battista; Pelikánová, Šárka; Garcia, Sonia; Kovařík, Aleš

2017-05-18

Pikes represent an important genus (Esox) harbouring a pre-duplication karyotype (2n = 2x = 50) of economically important salmonid pseudopolyploids. Here, we have characterized the 5S ribosomal RNA genes (rDNA) in Esox lucius and its closely related E. cisalpinus using cytogenetic, molecular and genomic approaches. Intragenomic homogeneity and copy number estimation was carried out using Illumina reads. The higher-order structure of rDNA arrays was investigated by the analysis of long PacBio reads. Position of loci on chromosomes was determined by FISH. DNA methylation was analysed by methylation-sensitive restriction enzymes. The 5S rDNA loci occupy exclusively (peri)centromeric regions on 30-38 acrocentric chromosomes in both E. lucius and E. cisalpinus. The large number of loci is accompanied by extreme amplification of genes (>20,000 copies), which is to the best of our knowledge one of the highest copy number of rRNA genes in animals ever reported. Conserved secondary structures of predicted 5S rRNAs indicate that most of the amplified genes are potentially functional. Only few SNPs were found in genic regions indicating their high homogeneity while intergenic spacers were more heterogeneous and several families were identified. Analysis of 10-30 kb-long molecules sequenced by the PacBio technology (containing about 40% of total 5S rDNA) revealed that the vast majority (96%) of genes are organised in large several kilobase-long blocks. Dispersed genes or short tandems were less common (4%). The adjacent 5S blocks were directly linked, separated by intervening DNA and even inverted. The 5S units differing in the intergenic spacers formed both homogeneous and heterogeneous (mixed) blocks indicating variable degree of homogenisation between the loci. Both E. lucius and E. cisalpinus 5S rDNA was heavily methylated at CG dinucleotides. Extreme amplification of 5S rRNA genes in the Esox genome occurred in the absence of significant pseudogenisation

Report from the 4th Workshop on Extremely Large Databases

Directory of Open Access Journals (Sweden)

Jacek Becla

2011-02-01

Full Text Available Academic and industrial users are increasingly facing the challenge of petabytes of data, but managing and analyzing such large data sets still remains a daunting task. The 4th Extremely Large Databases workshop was organized to examine the needs of communities under-represented at the past workshops facing these issues. Approaches to big data statistical analytics as well as emerging opportunities related to emerging hardware technologies were also debated. Writable extreme scale databases and the science benchmark were discussed. This paper is the final report of the discussions and activities at this workshop.

Spatial extreme value analysis to project extremes of large-scale indicators for severe weather.

Science.gov (United States)

Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

2013-09-01

Concurrently high values of the maximum potential wind speed of updrafts ( W max ) and 0-6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd.

Is there a statistical mechanics of turbulence?

International Nuclear Information System (INIS)

Kraichnan, R.H.; Chen, S.Y.

1988-09-01

The statistical-mechanical treatment of turbulence is made questionable by strong nonlinearity and strong disequilibrium that result in the creation of ordered structures imbedded in disorder. Model systems are described which may provide some hope that a compact, yet faithful, statistical description of turbulence nevertheless is possible. Some essential dynamic features of the models are captured by low-order statistical approximations despite strongly non-Gaussian behavior. 31 refs., 5 figs

Climatic extremes improve predictions of spatial patterns of tree species

Science.gov (United States)

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

Science.gov (United States)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2016-04-01

Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

Test the Overall Significance of p-values by Using Joint Tail Probability of Ordered p-values as Test Statistic

OpenAIRE

Fang, Yongxiang; Wit, Ernst

2008-01-01

Fisher’s combined probability test is the most commonly used method to test the overall significance of a set independent p-values. However, it is very obviously that Fisher’s statistic is more sensitive to smaller p-values than to larger p-value and a small p-value may overrule the other p-values and decide the test result. This is, in some cases, viewed as a flaw. In order to overcome this flaw and improve the power of the test, the joint tail probability of a set p-values is proposed as a ...

Age related neuromuscular changes in sEMG of m. Tibialis Anterior using higher order statistics (Gaussianity & linearity test).

Science.gov (United States)

Siddiqi, Ariba; Arjunan, Sridhar P; Kumar, Dinesh K

2016-08-01

Age-associated changes in the surface electromyogram (sEMG) of Tibialis Anterior (TA) muscle can be attributable to neuromuscular alterations that precede strength loss. We have used our sEMG model of the Tibialis Anterior to interpret the age-related changes and compared with the experimental sEMG. Eighteen young (20-30 years) and 18 older (60-85 years) performed isometric dorsiflexion at 6 different percentage levels of maximum voluntary contractions (MVC), and their sEMG from the TA muscle was recorded. Six different age-related changes in the neuromuscular system were simulated using the sEMG model at the same MVCs as the experiment. The maximal power of the spectrum, Gaussianity and Linearity Test Statistics were computed from the simulated and experimental sEMG. A correlation analysis at α=0.05 was performed between the simulated and experimental age-related change in the sEMG features. The results show the loss in motor units was distinguished by the Gaussianity and Linearity test statistics; while the maximal power of the PSD distinguished between the muscular factors. The simulated condition of 40% loss of motor units with halved the number of fast fibers best correlated with the age-related change observed in the experimental sEMG higher order statistical features. The simulated aging condition found by this study corresponds with the moderate motor unit remodelling and negligible strength loss reported in literature for the cohorts aged 60-70 years.

Introduction to the special issue: Observed and projected changes in weather and climate extremes

Directory of Open Access Journals (Sweden)

John E. Hay

2016-03-01

Full Text Available This Special Issue documents not only the more recent progress made in detecting and attributing changes in temperature and precipitation extremes in the observational record, but also in projecting changes in such extremes at regional and local scales. It also deals with the impacts and other consequences and implications of both the historic and anticipated changes in extreme weather and climate events. Impact assessments using both dynamical downscaling and statistical modelling for two tropical cyclones are reported, as well as for storm surge and extreme wave changes. The Special Issue concludes with a consideration of some policy implications and practical applications arising from our relatively robust understanding of how the build up of greenhouse gases in the Earth’s atmosphere affects weather and climate extremes.

Detection of non-stationarity in precipitation extremes using a max-stable process model

Science.gov (United States)

Westra, S.; Sisson, S.

2011-12-01

The question of how extreme precipitation will change under a future climate represents an urgent research problem, not least because of the significant societal impacts that would result from an increase in precipitation-induced flooding. To better constrain future projections, an important line of evidence comes from statistical assessments of change to extreme precipitation in the observational record, as a significant amount of warming since pre-industrial times has already taken place. In this study we address this problem by applying a max-stable process model to evaluate whether extreme precipitation at sub-daily and daily timescales has changed at various locations around Australia. This max-stable process approach, which was developed to simulate spatial fields comprising observations from multiple point locations, significantly increases the precision of a statistical inference compared to standard univariate methods. Applying the technique to a field of annual maxima derived from 30 sub-daily gauges in east Australia from 1965 to 2005, we find a statistically significant increase of 18% for 6-minute rainfall over this period, with smaller increases for longer duration events. We also find an increase of 5.6% and 22.5% per degree of Australian land surface temperature and global sea surface temperature at 6-minute durations, respectively, again with smaller scaling relationships for longer durations. In contrast, limited change could be observed in daily rainfall at most locations, with the exception of a statistically significant decline of 7.4% per degree land surface temperature in southwest Western Australia. These results suggest both the importance of better understanding changes to precipitation at the sub-daily timescale, as well as the need to more precisely simulate temporal variability by accounting for the spatial nature of precipitation in any statistical model.

Statistics-Based Compression of Global Wind Fields

KAUST Repository

Jeong, Jaehong

2017-02-07

Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth\\'s orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

Statistics-Based Compression of Global Wind Fields

KAUST Repository

Jeong, Jaehong; Castruccio, Stefano; Crippa, Paola; Genton, Marc G.

2017-01-01

Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth's orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

Joint fundamental frequency and order estimation using optimal filtering

Directory of Open Access Journals (Sweden)

Jakobsson Andreas

2011-01-01

Full Text Available Abstract In this paper, the problem of jointly estimating the number of harmonics and the fundamental frequency of periodic signals is considered. We show how this problem can be solved using a number of methods that either are or can be interpreted as filtering methods in combination with a statistical model selection criterion. The methods in question are the classical comb filtering method, a maximum likelihood method, and some filtering methods based on optimal filtering that have recently been proposed, while the model selection criterion is derived herein from the maximum a posteriori principle. The asymptotic properties of the optimal filtering methods are analyzed and an order-recursive efficient implementation is derived. Finally, the estimators have been compared in computer simulations that show that the optimal filtering methods perform well under various conditions. It has previously been demonstrated that the optimal filtering methods perform extremely well with respect to fundamental frequency estimation under adverse conditions, and this fact, combined with the new results on model order estimation and efficient implementation, suggests that these methods form an appealing alternative to classical methods for analyzing multi-pitch signals.

Butterflies, Black swans and Dragon kings: How to use the Dynamical Systems Theory to build a "zoology" of mid-latitude circulation atmospheric extremes?

Science.gov (United States)

Faranda, D.; Yiou, P.; Alvarez-Castro, M. C. M.

2015-12-01

A combination of dynamical systems and statistical techniques allows for a robust assessment of the dynamical properties of the mid-latitude atmospheric circulation. Extremes at different spatial and time scales are not only associated to exceptionally intense weather structures (e.g. extra-tropical cyclones) but also to rapid changes of circulation regimes (thunderstorms, supercells) or the extreme persistence of weather structure (heat waves, cold spells). We will show how the dynamical systems theory of recurrence combined to the extreme value theory can take into account the spatial and temporal dependence structure of the mid-latitude circulation structures and provide information on the statistics of extreme events.

Taub-NUT black holes in third order Lovelock gravity

International Nuclear Information System (INIS)

Hendi, S.H.; Dehghani, M.H.

2008-01-01

We consider the existence of Taub-NUT solutions in third order Lovelock gravity with cosmological constant, and obtain the general form of these solutions in eight dimensions. We find that, as in the case of Gauss-Bonnet gravity and in contrast with the Taub-NUT solutions of Einstein gravity, the metric function depends on the specific form of the base factors on which one constructs the circle fibration. Thus, one may say that the independence of the NUT solutions on the geometry of the base space is not a robust feature of all generally covariant theories of gravity and is peculiar to Einstein gravity. We find that when Einstein gravity admits non-extremal NUT solutions with no curvature singularity at r=N, then there exists a non-extremal NUT solution in third order Lovelock gravity. In 8-dimensional spacetime, this happens when the metric of the base space is chosen to be CP 3 . Indeed, third order Lovelock gravity does not admit non-extreme NUT solutions with any other base space. This is another property which is peculiar to Einstein gravity. We also find that the third order Lovelock gravity admits extremal NUT solution when the base space is T 2 xT 2 xT 2 or S 2 xT 2 xT 2 . We have extended these observations to two conjectures about the existence of NUT solutions in Lovelock gravity in any even-dimensional spacetime

Estimation of initiating event frequency for external flood events by extreme value theorem

International Nuclear Information System (INIS)

Chowdhury, Sourajyoti; Ganguly, Rimpi; Hari, Vibha

2017-01-01

External flood is an important common cause initiating event in nuclear power plants (NPPs). It may potentially lead to severe core damage (SCD) by first causing the failure of the systems required for maintaining the heat sinks and then by contributing to failures of engineered systems designed to mitigate such failures. The sample NPP taken here is twin 220 MWe Indian standard pressurized heavy water reactor (PHWR) situated inland. A comprehensive in-house Level-1 internal event PSA for full power had already been performed. External flood assessment was further conducted in area of external hazard risk assessment in response to post-Fukushima measures taken in nuclear industries. The present paper describes the methodology to calculate initiating event (IE) frequency for external flood events for the sample inland Indian NPP. General extreme value (GEV) theory based on maximum likelihood method (MLM) and order statistics approach (OSA) is used to analyse the rainfall data for the site. Thousand-year return level and necessary return periods for extreme rainfall are evaluated. These results along with plant-specific topographical calculations quantitatively establish that external flooding resulting from upstream dam break, river flooding and heavy rainfall (flash flood) would be unlikely for the sample NPP in consideration.

Identifying climate analogues for precipitation extremes for Denmark based on RCM simulations from the ENSEMBLES database.

Science.gov (United States)

Arnbjerg-Nielsen, K; Funder, S G; Madsen, H

2015-01-01

Climate analogues, also denoted Space-For-Time, may be used to identify regions where the present climatic conditions resemble conditions of a past or future state of another location or region based on robust climate variable statistics in combination with projections of how these statistics change over time. The study focuses on assessing climate analogues for Denmark based on current climate data set (E-OBS) observations as well as the ENSEMBLES database of future climates with the aim of projecting future precipitation extremes. The local present precipitation extremes are assessed by means of intensity-duration-frequency curves for urban drainage design for the relevant locations being France, the Netherlands, Belgium, Germany, the United Kingdom, and Denmark. Based on this approach projected increases of extreme precipitation by 2100 of 9 and 21% are expected for 2 and 10 year return periods, respectively. The results should be interpreted with caution as the best region to represent future conditions for Denmark is the coastal areas of Northern France, for which only little information is available with respect to present precipitation extremes.

Wind and wave extremes over the world oceans from very large ensembles

Science.gov (United States)

Breivik, Øyvind; Aarnes, Ole Johan; Abdalla, Saleh; Bidlot, Jean-Raymond; Janssen, Peter A. E. M.

2014-07-01

Global return values of marine wind speed and significant wave height are estimated from very large aggregates of archived ensemble forecasts at +240 h lead time. Long lead time ensures that the forecasts represent independent draws from the model climate. Compared with ERA-Interim, a reanalysis, the ensemble yields higher return estimates for both wind speed and significant wave height. Confidence intervals are much tighter due to the large size of the data set. The period (9 years) is short enough to be considered stationary even with climate change. Furthermore, the ensemble is large enough for nonparametric 100 year return estimates to be made from order statistics. These direct return estimates compare well with extreme value estimates outside areas with tropical cyclones. Like any method employing modeled fields, it is sensitive to tail biases in the numerical model, but we find that the biases are moderate outside areas with tropical cyclones.

First Order Description of Black Holes in Moduli Space

CERN Document Server

Andrianopoli, Laura; Orazi, Emanuele; Trigiante, Mario

2007-01-01

We show that the second order field equations characterizing extremal solutions for spherically symmetric, stationary black holes are in fact implied by a system of first order equations given in terms of a prepotential W. This confirms and generalizes the results in hep-th/0702088. When the black holes are solutions of extended supergravities we are able to find an explicit expression for the prepotentials which reproduce all the attractors of the four dimensional N>2 theories. We discuss a possible extension of our considerations to the non extremal case.

Order no 000004/PRN/ME/P/DS from January 21, 2014 provides for the organization and attributions of divisions and departments of the Statistics Directorate of the Ministry of Energy and Oil

International Nuclear Information System (INIS)

Foumakoye, Gado

2014-01-01

This order provides for the organization and attributions of divisions and departments of the Statistics Directorate of the Ministry of Energy and Oil. This direction has two divisions namely Division for Energy Statistics and Division for Oil Statistics . Energy Statistics Division includes the following services: Service collection and data analysis for energy statistics and the service of production, dissemination and conservation of energy statics. The division for Oil Statistics includes the Service collection and data analysis for energy statistics and the service of production, dissemination and conservation of energy statistics. [fr

Observed and simulated hydrologic response for a first-order catchment during extreme rainfall 3 years after wildfire disturbance

Science.gov (United States)

Ebel, Brian A.; Rengers, Francis K.; Tucker, Gregory E.

2016-01-01

Hydrologic response to extreme rainfall in disturbed landscapes is poorly understood because of the paucity of measurements. A unique opportunity presented itself when extreme rainfall in September 2013 fell on a headwater catchment (i.e., soil-hydraulic properties, soil saturation from subsurface sensors, and estimated peak runoff during the extreme rainfall with numerical simulations of runoff generation and subsurface hydrologic response during this event. The simulations were used to explore differences in runoff generation between the wildfire-affected headwater catchment, a simulated unburned case, and for uniform versus spatially variable parameterizations of soil-hydraulic properties that affect infiltration and runoff generation in burned landscapes. Despite 3 years of elapsed time since the 2010 wildfire, observations and simulations pointed to substantial surface runoff generation in the wildfire-affected headwater catchment by the infiltration-excess mechanism while no surface runoff was generated in the unburned case. The surface runoff generation was the result of incomplete recovery of soil-hydraulic properties in the burned area, suggesting recovery takes longer than 3 years. Moreover, spatially variable soil-hydraulic property parameterizations produced longer duration but lower peak-flow infiltration-excess runoff, compared to uniform parameterization, which may have important hillslope sediment export and geomorphologic implications during long duration, extreme rainfall. The majority of the simulated surface runoff in the spatially variable cases came from connected near-channel contributing areas, which was a substantially smaller contributing area than the uniform simulations.

Integer Set Compression and Statistical Modeling

DEFF Research Database (Denmark)

Larsson, N. Jesper

2014-01-01

enumeration of elements may be arbitrary or random, but where statistics is kept in order to estimate probabilities of elements. We present a recursive subset-size encoding method that is able to benefit from statistics, explore the effects of permuting the enumeration order based on element probabilities......Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher compression performance. In this work, we address the case where...

A Generalized Framework for Non-Stationary Extreme Value Analysis

Science.gov (United States)

Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.

2017-12-01

Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA

Comparison of different statistical downscaling methods to estimate changes in hourly extreme precipitation using RCM projections from ENSEMBLES

DEFF Research Database (Denmark)

Sunyer Pinya, Maria Antonia; Gregersen, Ida Bülow; Rosbjerg, Dan

2015-01-01

change method for extreme events, a weather generator combined with a disaggregation method and a climate analogue method. All three methods rely on different assumptions and use different outputs from the regional climate models (RCMs). The results of the three methods point towards an increase...... in extreme precipitation but the magnitude of the change varies depending on the RCM used and the spatial location. In general, a similar mean change is obtained for the three methods. This adds confidence in the results as each method uses different information from the RCMs. The results of this study...

Spatial variation in extreme water levels in the Baltic Sea – North Sea transition from tide gauge records

DEFF Research Database (Denmark)

Sørensen, Carlo Sass; Andersen, Ole Baltazar; Knudsen, Per

events.Knowledge about extremes is essential for climate adaptation, design, and planning purposes. In an ongoing research project we seek to develop more robust and objective statistics for Denmark. This includes a revisit to all tide gauge stations’ (TG) data and exploring methods for extreme value...

A training tool for lower extremity amputees

NARCIS (Netherlands)

Neutelings, I.M.P.; Hengeveld, B.J.

2015-01-01

Abstract People with a prosthetic limb miss a sense of touch at this particular part of their body. The work described in this paper focuses on providing people with a lower extremity amputation with an alternative sensory stimulus in order to help them experience what they can no longer feel. To

Prevailing trends of climatic extremes across Indus-Delta of Sindh-Pakistan

Science.gov (United States)

Abbas, Farhat; Rehman, Iqra; Adrees, Muhammad; Ibrahim, Muhammad; Saleem, Farhan; Ali, Shafaqat; Rizwan, Muhammad; Salik, Muhammad Raza

2018-02-01

This study examines the variability and change in the patterns of climatic extremes experienced in Indus-Delta of Sindh province of Pakistan, comprising regions of Karachi, Badin, Mohenjodaro, and Rohri. The homogenized daily minimum and maximum temperature and precipitation data for a 36-year period were used to calculate 13 and 11 indices of temperature and precipitation extremes with the help of RClimDex, a program written in the statistical software package R. A non-parametric Mann-Kendall test and Sen's slope estimates were used to determine the statistical significance and magnitude of the calculated trend. Temperatures of summer days and tropical nights increased in the region with overall significant warming trends for monthly maximum temperature as well as for warm days and nights reflecting dry conditions in the study area. The warm extremes and nighttime temperature indices showed greater trends than cold extremes and daytime indices depicting an overall warming trends in the Delta. Historic decrease in the acreage of major crops and over 33% decrease in agriculture credit for Sindh are the indicators of adverse impacts of warmer and drier weather on Sindh agriculture. Trends reported for Karachi and Badin are expected to decrease rice cultivation, hatching of fisheries, and mangroves forest surrounding these cities. Increase in the prevailing temperature trends will lead to increasingly hotter and drier summers resulting to constraints on cotton, wheat, and rice yield in Rohri and Mohenjodaro areas due to increased crop water requirements that may be met with additional groundwater pumping; nonetheless, the depleted groundwater resources would have a direct impact on the region's economy.

Estimating extreme river discharges in Europe through a Bayesian network

Science.gov (United States)

Paprotny, Dominik; Morales-Nápoles, Oswaldo

2017-06-01

Large-scale hydrological modelling of flood hazards requires adequate extreme discharge data. In practise, models based on physics are applied alongside those utilizing only statistical analysis. The former require enormous computational power, while the latter are mostly limited in accuracy and spatial coverage. In this paper we introduce an alternate, statistical approach based on Bayesian networks (BNs), a graphical model for dependent random variables. We use a non-parametric BN to describe the joint distribution of extreme discharges in European rivers and variables representing the geographical characteristics of their catchments. Annual maxima of daily discharges from more than 1800 river gauges (stations with catchment areas ranging from 1.4 to 807 000 km2) were collected, together with information on terrain, land use and local climate. The (conditional) correlations between the variables are modelled through copulas, with the dependency structure defined in the network. The results show that using this method, mean annual maxima and return periods of discharges could be estimated with an accuracy similar to existing studies using physical models for Europe and better than a comparable global statistical model. Performance of the model varies slightly between regions of Europe, but is consistent between different time periods, and remains the same in a split-sample validation. Though discharge prediction under climate change is not the main scope of this paper, the BN was applied to a large domain covering all sizes of rivers in the continent both for present and future climate, as an example. Results show substantial variation in the influence of climate change on river discharges. The model can be used to provide quick estimates of extreme discharges at any location for the purpose of obtaining input information for hydraulic modelling.

Random cyclic stress-strain responses of a stainless steel pipe-weld metal. I. A statistical investigation

International Nuclear Information System (INIS)

Zhao, Y.X.; Wang, J.N.

2000-01-01

For pt.II see ibid., vol.199, p.315-26, 2000. This paper pays a special attention to the issue that there is a significant scatter of the stress-strain responses of a nuclear engineering material, 1Cr18Ni9Ti stainless steel pipe-weld metal. Statistical investigation is made to the cyclic stress amplitudes of this material. Three considerations are given. They consist of the total fit, the consistency with fatigue physics and the safety in practice of the seven commonly used statistical distributions, namely Weibull (two- and three-parameter), normal, lognormal, extreme minimum value, extreme maximum value and exponential. Results reveal that the data follow meanwhile the seven distributions but the local effects of the distributions yield a significant difference. Any of the normal, lognormal, extreme minimum value and extreme maximum value distributions might be an appropriate assumed distribution for characterizing the data. The normal and extreme minimum models are excellent. Other distributions do not fit the data as they violate two or three of the mentioned considerations. (orig.)

Effects of land cover change on temperature and rainfall extremes in multi-model ensemble simulations

Directory of Open Access Journals (Sweden)

A. J. Pitman

2012-11-01

Full Text Available The impact of historical land use induced land cover change (LULCC on regional-scale climate extremes is examined using four climate models within the Land Use and Climate, IDentification of robust impacts project. To assess those impacts, multiple indices based on daily maximum and minimum temperatures and daily precipitation were used. We contrast the impact of LULCC on extremes with the impact of an increase in atmospheric CO₂ from 280 ppmv to 375 ppmv. In general, consistent changes in both high and low temperature extremes are similar to the simulated change in mean temperature caused by LULCC and are restricted to regions of intense modification. The impact of LULCC on both means and on most temperature extremes is statistically significant. While the magnitude of the LULCC-induced change in the extremes can be of similar magnitude to the response to the change in CO₂, the impacts of LULCC are much more geographically isolated. For most models, the impacts of LULCC oppose the impact of the increase in CO₂ except for one model where the CO₂-caused changes in the extremes are amplified. While we find some evidence that individual models respond consistently to LULCC in the simulation of changes in rainfall and rainfall extremes, LULCC's role in affecting rainfall is much less clear and less commonly statistically significant, with the exception of a consistent impact over South East Asia. Since the simulated response of mean and extreme temperatures to LULCC is relatively large, we conclude that unless this forcing is included, we risk erroneous conclusions regarding the drivers of temperature changes over regions of intense LULCC.

Adaptive sampling based on the cumulative distribution function of order statistics to delineate heavy-metal contaminated soils using kriging

International Nuclear Information System (INIS)

Juang, K.-W.; Lee, D.-Y.; Teng, Y.-L.

2005-01-01

Correctly classifying 'contaminated' areas in soils, based on the threshold for a contaminated site, is important for determining effective clean-up actions. Pollutant mapping by means of kriging is increasingly being used for the delineation of contaminated soils. However, those areas where the kriged pollutant concentrations are close to the threshold have a high possibility for being misclassified. In order to reduce the misclassification due to the over- or under-estimation from kriging, an adaptive sampling using the cumulative distribution function of order statistics (CDFOS) was developed to draw additional samples for delineating contaminated soils, while kriging. A heavy-metal contaminated site in Hsinchu, Taiwan was used to illustrate this approach. The results showed that compared with random sampling, adaptive sampling using CDFOS reduced the kriging estimation errors and misclassification rates, and thus would appear to be a better choice than random sampling, as additional sampling is required for delineating the 'contaminated' areas. - A sampling approach was derived for drawing additional samples while kriging

Small violations of particle statistics

International Nuclear Information System (INIS)

Greenberg, O.W.

1992-01-01

This paper reports on the particle statistics menagerie for identical particles (in 3 + 1 dimensions) which consists of fermions (all states totally antisymmetric), bosons (all states totally symmetric), parafermions of order p (all representations of the symmetric group with Young tableaux having at most p boxes in a row) and parabosons of order p (all representations with at most p boxes in a column). p = 1 for parafermions is the same as Fermi, and p = 1 for parabosons is the same as Bose. These possibilities were derived in a general way by Doplicher, Haag and Roberts, who found one other case, infinite statistics for which all representations of the symmetric group occur, but did not give an algebra which leads to this statistics

EXTREME MAXIMUM AND MINIMUM AIR TEMPERATURE IN MEDİTERRANEAN COASTS IN TURKEY

Directory of Open Access Journals (Sweden)

Barbaros Gönençgil

2016-01-01

Full Text Available In this study, we determined extreme maximum and minimum temperatures in both summer and winter seasons at the stations in the Mediterranean coastal areas of Turkey.In the study, the data of 24 meteorological stations for the daily maximum and minimumtemperatures of the period from 1970–2010 were used. From this database, a set of four extreme temperature indices applied warm (TX90 and cold (TN10 days and warm spells (WSDI and cold spell duration (CSDI. The threshold values were calculated for each station to determine the temperatures that were above and below the seasonal norms in winter and summer. The TX90 index displays a positive statistically significant trend, while TN10 display negative nonsignificant trend. The occurrence of warm spells shows statistically significant increasing trend while the cold spells shows significantly decreasing trend over the Mediterranean coastline in Turkey.

Control of extreme events in the bubbling onset of wave turbulence.

Science.gov (United States)

Galuzio, P P; Viana, R L; Lopes, S R

2014-04-01

We show the existence of an intermittent transition from temporal chaos to turbulence in a spatially extended dynamical system, namely, the forced and damped one-dimensional nonlinear Schrödinger equation. For some values of the forcing parameter, the system dynamics intermittently switches between ordered states and turbulent states, which may be seen as extreme events in some contexts. In a Fourier phase space, the intermittency takes place due to the loss of transversal stability of unstable periodic orbits embedded in a low-dimensional subspace. We mapped these transversely unstable regions and perturbed the system in order to significantly reduce the occurrence of extreme events of turbulence.

On the computation of the higher order statistics of the channel capacity for amplify-and-forward multihop transmission

KAUST Repository

Yilmaz, Ferkan; Tabassum, Hina; Alouini, Mohamed-Slim

2014-01-01

Higher order statistics (HOS) of the channel capacity provide useful information regarding the level of reliability of signal transmission at a particular rate. In this paper, we propose a novel and unified analysis, which is based on the moment-generating function (MGF) approach, to efficiently and accurately compute the HOS of the channel capacity for amplify-and-forward (AF) multihop transmission over generalized fading channels. More precisely, our easy-to-use and tractable mathematical formalism requires only the reciprocal MGFs of the transmission hop signal-to-noise ratio (SNR). Numerical and simulation results, which are performed to exemplify the usefulness of the proposed MGF-based analysis, are shown to be in perfect agreement. © 2013 IEEE.

Prevalence of lower extremity venous duplication

Directory of Open Access Journals (Sweden)

Simpson William

2010-01-01

Full Text Available Purpose: This retrospective study was performed to determine the prevalence of lower extremity venous duplication using duplex ultrasound in the patient population of a large urban medical center. Materials and Methods: The reports of all lower extremity venous ultrasound examinations performed at our institution between January 1, 2002 and December 31, 2002 were reviewed. Ultrasound examinations that were performed for purposes other than the detection of lower extremity deep vein thrombosis were excluded. The prevalence of duplication and its specific location were recorded. In addition, the prevalence of thrombus and its specific location were also recorded. Results: A total of 3118 exams were performed in 2664 patients. Of the 2664 patients, 2311 had only one examination performed during the study period; 353 patients had more than one examination performed. We found that 10.1% of patients (270/2664 had at least one venous segment duplicated and 5.4% of patients (143/2664 had a thrombus in at least one venous segment. There was a statistically significant difference in the prevalence of both duplication and thrombus with a change in venous segment. Only 0.4% of patients (11/2664 had thrombus within a duplicated segment. Of those who had more than one examination performed, 15.3% (54/353 had the same venous segment(s seen on one examination but not another. Conclusion: Lower extremity venous duplication is a frequent anatomic variant that is seen in 10.1% of patients, but it may not be as common as is generally believed. It can result in a false negative result for deep vein thrombosis.

Statistics for non-statisticians

CERN Document Server

Madsen, Birger Stjernholm

2016-01-01

This book was written for those who need to know how to collect, analyze and present data. It is meant to be a first course for practitioners, a book for private study or brush-up on statistics, and supplementary reading for general statistics classes. The book is untraditional, both with respect to the choice of topics and the presentation: Topics were determined by what is most useful for practical statistical work, and the presentation is as non-mathematical as possible. The book contains many examples using statistical functions in spreadsheets. In this second edition, new topics have been included e.g. within the area of statistical quality control, in order to make the book even more useful for practitioners working in industry. .

A spatial and nonstationary model for the frequency of extreme rainfall events

DEFF Research Database (Denmark)

Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

2013-01-01

of extreme rainfall events, a statistical model is tested for this purpose. The model is built on the theory of generalized linear models and uses Poisson regression solved by generalized estimation equations. Spatial and temporal explanatory variables can be included simultaneously, and their relative...

Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

Science.gov (United States)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2018-03-01

Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

Mandelbrot's Extremism

NARCIS (Netherlands)

Beirlant, J.; Schoutens, W.; Segers, J.J.J.

2004-01-01

In the sixties Mandelbrot already showed that extreme price swings are more likely than some of us think or incorporate in our models.A modern toolbox for analyzing such rare events can be found in the field of extreme value theory.At the core of extreme value theory lies the modelling of maxima

Modified Distribution-Free Goodness-of-Fit Test Statistic.

Science.gov (United States)

Chun, So Yeon; Browne, Michael W; Shapiro, Alexander

2018-03-01

Covariance structure analysis and its structural equation modeling extensions have become one of the most widely used methodologies in social sciences such as psychology, education, and economics. An important issue in such analysis is to assess the goodness of fit of a model under analysis. One of the most popular test statistics used in covariance structure analysis is the asymptotically distribution-free (ADF) test statistic introduced by Browne (Br J Math Stat Psychol 37:62-83, 1984). The ADF statistic can be used to test models without any specific distribution assumption (e.g., multivariate normal distribution) of the observed data. Despite its advantage, it has been shown in various empirical studies that unless sample sizes are extremely large, this ADF statistic could perform very poorly in practice. In this paper, we provide a theoretical explanation for this phenomenon and further propose a modified test statistic that improves the performance in samples of realistic size. The proposed statistic deals with the possible ill-conditioning of the involved large-scale covariance matrices.

A new Class of Extremal Composites

DEFF Research Database (Denmark)

Sigmund, Ole

2000-01-01

microstructure belonging to the new class of composites has maximum bulk modulus and lower shear modulus than any previously known composite. Inspiration for the new composite class comes from a numerical topology design procedure which solves the inverse homogenization problem of distributing two isotropic......The paper presents a new class of two-phase isotropic composites with extremal bulk modulus. The new class consists of micro geometrics for which exact solutions can be proven and their bulk moduli are shown to coincide with the Hashin-Shtrikman bounds. The results hold for two and three dimensions...... and for both well- and non-well-ordered isotropic constituent phases. The new class of composites constitutes an alternative to the three previously known extremal composite classes: finite rank laminates, composite sphere assemblages and Vigdergauz microstructures. An isotropic honeycomb-like hexagonal...

Trends and periodicity of daily temperature and precipitation extremes during 1960-2013 in Hunan Province, central south China

Science.gov (United States)

Chen, Ajiao; He, Xinguang; Guan, Huade; Cai, Yi

2018-04-01

In this study, the trends and periodicity in climate extremes are examined in Hunan Province over the period 1960-2013 on the basis of 27 extreme climate indices calculated from daily temperature and precipitation records at 89 meteorological stations. The results show that in the whole province, temperature extremes exhibit a warming trend with more than 50% stations being statistically significant for 7 out of 16 temperature indices, and the nighttime temperature increases faster than the daytime temperature at the annual scale. The changes in most extreme temperature indices show strongly coherent spatial patterns. Moreover, the change rates of almost all temperature indices in north Hunan are greater than those of other regions. However, the statistically significant changes in indices of extreme precipitation are observed at fewer stations than in extreme temperature indices, forming less spatially coherent patterns. Positive trends in indices of extreme precipitation show that the amount and intensity of extreme precipitation events are generally increasing in both annual and seasonal scales, whereas the significant downward trend in consecutive wet days indicates that the precipitation becomes more even over the study period. Analysis of changes in probability distributions of extreme indices for 1960-1986 and 1987-2013 also demonstrates a remarkable shift toward warmer condition and increasing tendency in the amount and intensity of extreme precipitation during the past decades. The variations in extreme climate indices exhibit inconstant frequencies in the wavelet power spectrum. Among the 16 temperature indices, 2 of them show significant 1-year periodic oscillation and 7 of them exhibit significant 4-year cycle during some certain periods. However, significant periodic oscillations can be found in all of the precipitation indices. Wet-day precipitation and three absolute precipitation indices show significant 1-year cycle and other seven provide

[Lower extremity amputation rates in diabetic patients].

Science.gov (United States)

Cisneros-González, Nelly; Ascencio-Montiel, Iván Jesús; Libreros-Bango, Vita Norma; Rodríguez-Vázquez, Héctor; Campos-Hernández, Ángel; Dávila-Torres, Javier; Kumate-Rodríguez, Jesús; Borja-Aburto, Víctor Hugo

2016-01-01

The lower extremity amputations diminish the quality of life of patients with Diabetes Mellitus (DM). The aim of this study was to describe the lower extremity amputation rates in subjects with DM in the Mexican Social Security Institute (IMSS), comparing 2004 and 2013. A comparative cross-sectional study was done. Amputations were identified from the hospital records of System of Medical Statistics (DataMart). The DM patient census was obtained from the System of Integral Attention to Health. Major and minor amputations rates were expressed per 100,000 DM patients. We observed 2 334 340 and 3 416 643 DM patients during 2004 and 2013, respectively. The average age at the time of the amputation was similar in 2004 and 2013 (61.7 and 65.6 years old for minor and major amputations respectively). The major amputations rates were 100.9 and 111.1 per 100 000 subjects with DM in during 2004 and 2013 (p = 0.001); while minor amputations rates were 168.8 and 162.5 per 100 000 subjects with DM in during 2004 and 2013 respectively (p = 0.069). The lower extremity amputations rates at IMSS are very high compared with that reported in developed countries. The major amputations rate increased in 2013 compared with 2004.

Data Literacy is Statistical Literacy

Science.gov (United States)

Gould, Robert

2017-01-01

Past definitions of statistical literacy should be updated in order to account for the greatly amplified role that data now play in our lives. Experience working with high-school students in an innovative data science curriculum has shown that teaching statistical literacy, augmented by data literacy, can begin early.

Graph theory applied to noise and vibration control in statistical energy analysis models.

Science.gov (United States)

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.

Climate change impact assessment of extreme precipitation on urban flash floods – case study, Aarhus, Denmark

DEFF Research Database (Denmark)

Madsen, Henrik; Sunyer Pinya, Maria Antonia; Rosbjerg, Dan

projections for estimation of changes in extreme rainfall characteristics. Climate model projections from 20 regional climate models (RCM) from the ENSEMBLES data archive were used in the analysis. Two different estimation methods were applied, using, respectively, a direct estimation of the changes...... in the extreme value statistics of the RCM data, and application of a stochastic weather generator fitted to the changes in rainfall characteristics from the RCM data. The results show a large variability in the projected changes in extreme precipitation between the different RCMs and the two estimation methods...

77 FR 51693 - Milk in the Mideast Marketing Area; Order Amending the Order

Science.gov (United States)

2012-08-27

... can be supplied without data processing equipment or a trained statistical staff. Thus, the... DEPARTMENT OF AGRICULTURE Agricultural Marketing Service 7 CFR Part 1033 [Doc. No. AO-11-0333; AMS-DA-11-0067; DA-11-04] Milk in the Mideast Marketing Area; Order Amending the Order AGENCY...

Multifractal Conceptualisation of Hydro-Meteorological Extremes

Science.gov (United States)

Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.

2009-04-01

Hydrology and more generally sciences involved in water resources management, technological or operational developments face a fundamental difficulty: the extreme variability of hydro-meteorological fields. It clearly appears today that this variability is a function of the observation scale and yield hydro-meteorological hazards. Throughout the world, the development of multifractal theory offers new techniques for handling such non-classical variability over wide ranges of time and space scales. The resulting stochastic simulations with a very limited number of parameters well reproduce the long range dependencies and the clustering of rainfall extremes often yielding fat tailed (i.e., an algebraic type) probability distributions. The goal of this work was to investigate the ability of using very short or incomplete data records for reliable statistical predictions of the extremes. In particular we discuss how to evaluate the uncertainty in the empirical or semi-analytical multifractal outcomes. We consider three main aspects of the evaluation, such as the scaling adequacy, the multifractal parameter estimation error and the quantile estimation error. We first use the multiplicative cascade model to generate long series of multifractal data. The simulated samples had to cover the range of the universal multifractal parameters widely available in the scientific literature for the rainfall and river discharges. Using these long multifractal series and their sub-samples, we defined a metric for parameter estimation error. Then using the sets of estimated parameters, we obtained the quantile values for a range of excedance probabilities from 5% to 0.01%. Plotting the error bars on a quantile plot enable an approximation of confidence intervals that would be particularly important for the predictions of multifractal extremes. We finally illustrate the efficiency of such concept on its application to a large database (more than 16000 selected stations over USA and

Metaheuristic approaches to order sequencing on a unidirectional picking line

Directory of Open Access Journals (Sweden)

AP de Villiers

2013-06-01

Full Text Available In this paper the sequencing of orders on a unidirectional picking line is considered. The aim of the order sequencing is to minimise the number of cycles travelled by a picker within the picking line to complete all orders. A tabu search, simulated annealing, genetic algorithm, generalised extremal optimisation and a random local search are presented as possible solution approaches. Computational results based on real life data instances are presented for these metaheuristics and compared to the performance of a lower bound and the solutions used in practise. The random local search exhibits the best overall solution quality, however, the generalised extremal optimisation approach delivers comparable results in considerably shorter computational times.

Statistical characterization of pitting corrosion process and life prediction

International Nuclear Information System (INIS)

Sheikh, A.K.; Younas, M.

1995-01-01

In order to prevent corrosion failures of machines and structures, it is desirable to know in advance when the corrosion damage will take place, and appropriate measures are needed to mitigate the damage. The corrosion predictions are needed both at development as well as operational stage of machines and structures. There are several forms of corrosion process through which varying degrees of damage can occur. Under certain conditions these corrosion processes at alone and in other set of conditions, several of these processes may occur simultaneously. For a certain type of machine elements and structures, such as gears, bearing, tubes, pipelines, containers, storage tanks etc., are particularly prone to pitting corrosion which is an insidious form of corrosion. The corrosion predictions are usually based on experimental results obtained from test coupons and/or field experiences of similar machines or parts of a structure. Considerable scatter is observed in corrosion processes. The probabilities nature and kinetics of pitting process makes in necessary to use statistical method to forecast the residual life of machine of structures. The focus of this paper is to characterization pitting as a time-dependent random process, and using this characterization the prediction of life to reach a critical level of pitting damage can be made. Using several data sets from literature on pitting corrosion, the extreme value modeling of pitting corrosion process, the evolution of the extreme value distribution in time, and their relationship to the reliability of machines and structure are explained. (author)

Simulated trends of extreme climate indices for the Carpathian basin using outputs of different regional climate models

Science.gov (United States)

Pongracz, R.; Bartholy, J.; Szabo, P.; Pieczka, I.; Torma, C. S.

2009-04-01

Regional climatological effects of global warming may be recognized not only in shifts of mean temperature and precipitation, but in the frequency or intensity changes of different climate extremes. Several climate extreme indices are analyzed and compared for the Carpathian basin (located in Central/Eastern Europe) following the guidelines suggested by the joint WMO-CCl/CLIVAR Working Group on climate change detection. Our statistical trend analysis includes the evaluation of several extreme temperature and precipitation indices, e.g., the numbers of severe cold days, winter days, frost days, cold days, warm days, summer days, hot days, extremely hot days, cold nights, warm nights, the intra-annual extreme temperature range, the heat wave duration, the growing season length, the number of wet days (using several threshold values defining extremes), the maximum number of consecutive dry days, the highest 1-day precipitation amount, the greatest 5-day rainfall total, the annual fraction due to extreme precipitation events, etc. In order to evaluate the future trends (2071-2100) in the Carpathian basin, daily values of meteorological variables are obtained from the outputs of various regional climate model (RCM) experiments accomplished in the frame of the completed EU-project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). Horizontal resolution of the applied RCMs is 50 km. Both scenarios A2 and B2 are used to compare past and future trends of the extreme climate indices for the Carpathian basin. Furthermore, fine-resolution climate experiments of two additional RCMs adapted and run at the Department of Meteorology, Eotvos Lorand University are used to extend the trend analysis of climate extremes for the Carpathian basin. (1) Model PRECIS (run at 25 km horizontal resolution) was developed at the UK Met Office, Hadley Centre, and it uses the boundary conditions from the HadCM3 GCM. (2) Model Reg

Uncertainties in hydrological extremes projections and its effects on decision-making processes in an Amazonian sub-basin.

Science.gov (United States)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lazaro Siqueira Junior, Jose

2013-04-01

Uncertainties in Climate Change projections are affected by irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process. Such uncertainties affect the impact studies, complicating the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. Through these kinds of analyses it is possible to identify critical issues, which must be deeper studied. For this study we used several future's projections from General Circulation Models to feed a Hydrological Model, applied to the Amazonian sub-basin of Ji-Paraná. Hydrological Model integrations are performed for present historical time (1970-1990) and for future period (2010-2100). Extreme values analyses are performed to each simulated time series and results are compared with extremes events in present time. A simple approach to identify potential vulnerabilities consists of evaluating the hydrologic system response to climate variability and extreme events observed in the past, comparing them with the conditions projected for the future. Thus it is possible to identify critical issues that need attention and more detailed studies. For the goal of this work, we used socio-economic data from Brazilian Institute of Geography and Statistics, the Operator of the National Electric System, the Brazilian National Water Agency and scientific and press published information. This information is used to characterize impacts associated to extremes hydrological events in the basin during the present historical time and to evaluate potential impacts in the future face to the different hydrological projections. Results show inter-model variability results in a broad dispersion on projected extreme's values. The impact of such dispersion is differentiated for different aspects of socio-economic and natural systems and must be carefully

Modeling of Dissipation Element Statistics in Turbulent Non-Premixed Jet Flames

Science.gov (United States)

Denker, Dominik; Attili, Antonio; Boschung, Jonas; Hennig, Fabian; Pitsch, Heinz

2017-11-01

The dissipation element (DE) analysis is a method for analyzing and compartmentalizing turbulent scalar fields. DEs can be described by two parameters, namely the Euclidean distance l between their extremal points and the scalar difference in the respective points Δϕ . The joint probability density function (jPDF) of these two parameters P(Δϕ , l) is expected to suffice for a statistical reconstruction of the scalar field. In addition, reacting scalars show a strong correlation with these DE parameters in both premixed and non-premixed flames. Normalized DE statistics show a remarkable invariance towards changes in Reynolds numbers. This feature of DE statistics was exploited in a Boltzmann-type evolution equation based model for the probability density function (PDF) of the distance between the extremal points P(l) in isotropic turbulence. Later, this model was extended for the jPDF P(Δϕ , l) and then adapted for the use in free shear flows. The effect of heat release on the scalar scales and DE statistics is investigated and an extended model for non-premixed jet flames is introduced, which accounts for the presence of chemical reactions. This new model is validated against a series of DNS of temporally evolving jet flames. European Research Council Project ``Milestone''.

Two sample Bayesian prediction intervals for order statistics based on the inverse exponential-type distributions using right censored sample

Directory of Open Access Journals (Sweden)

M.M. Mohie El-Din

2011-10-01

Full Text Available In this paper, two sample Bayesian prediction intervals for order statistics (OS are obtained. This prediction is based on a certain class of the inverse exponential-type distributions using a right censored sample. A general class of prior density functions is used and the predictive cumulative function is obtained in the two samples case. The class of the inverse exponential-type distributions includes several important distributions such the inverse Weibull distribution, the inverse Burr distribution, the loglogistic distribution, the inverse Pareto distribution and the inverse paralogistic distribution. Special cases of the inverse Weibull model such as the inverse exponential model and the inverse Rayleigh model are considered.

STATCAT, Statistical Analysis of Parametric and Non-Parametric Data

International Nuclear Information System (INIS)

David, Hugh

1990-01-01

1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required

A compliant mechanism for inspecting extremely confined spaces

Science.gov (United States)

Mascareñas, David; Moreu, Fernando; Cantu, Precious; Shields, Daniel; Wadden, Jack; El Hadedy, Mohamed; Farrar, Charles

2017-11-01

We present a novel, compliant mechanism that provides the capability to navigate extremely confined spaces for the purpose of infrastructure inspection. Extremely confined spaces are commonly encountered during infrastructure inspection. Examples of such spaces can include pipes, conduits, and ventilation ducts. Often these infrastructure features go uninspected simply because there is no viable way to access their interior. In addition, it is not uncommon for extremely confined spaces to possess a maze-like architecture that must be selectively navigated in order to properly perform an inspection. Efforts by the imaging sensor community have resulted in the development of imaging sensors on the millimeter length scale. Due to their compact size, they are able to inspect many extremely confined spaces of interest, however, the means to deliver these sensors to the proper location to obtain the desired images are lacking. To address this problem, we draw inspiration from the field of endoscopic surgery. Specifically we consider the work that has already been done to create long flexible needles that are capable of being steered through the human body. These devices are typically referred to as ‘steerable needles.’ Steerable needle technology is not directly applicable to the problem of navigating maze-like arrangements of extremely confined spaces, but it does provide guidance on how this problem should be approached. Specifically, the super-elastic nitinol tubing material that allows steerable needles to operate is also appropriate for the problem of navigating maze-like arrangements of extremely confined spaces. Furthermore, the portion of the mechanism that enters the extremely confined space is completely mechanical in nature. The mechanical nature of the device is an advantage when the extremely confined space features environmental hazards such as radiation that could degrade an electromechanically operated mechanism. Here, we present a compliant mechanism

How extreme is extreme hourly precipitation?

Science.gov (United States)

Papalexiou, Simon Michael; Dialynas, Yannis G.; Pappas, Christoforos

2016-04-01

The importance of accurate representation of precipitation at fine time scales (e.g., hourly), directly associated with flash flood events, is crucial in hydrological design and prediction. The upper part of a probability distribution, known as the distribution tail, determines the behavior of extreme events. In general, and loosely speaking, tails can be categorized in two families: the subexponential and the hyperexponential family, with the first generating more intense and more frequent extremes compared to the latter. In past studies, the focus has been mainly on daily precipitation, with the Gamma distribution being the most popular model. Here, we investigate the behaviour of tails of hourly precipitation by comparing the upper part of empirical distributions of thousands of records with three general types of tails corresponding to the Pareto, Lognormal, and Weibull distributions. Specifically, we use thousands of hourly rainfall records from all over the USA. The analysis indicates that heavier-tailed distributions describe better the observed hourly rainfall extremes in comparison to lighter tails. Traditional representations of the marginal distribution of hourly rainfall may significantly deviate from observed behaviours of extremes, with direct implications on hydroclimatic variables modelling and engineering design.

Extreme events in total ozone over Arosa: Application of extreme value theory and fingerprints of atmospheric dynamics and chemistry and their effects on mean values and long-term changes

Science.gov (United States)

Rieder, Harald E.; Staehelin, Johannes; Maeder, Jörg A.; Peter, Thomas; Ribatet, Mathieu; Davison, Anthony C.; Stübi, Rene; Weihs, Philipp; Holawe, Franz

2010-05-01

In this study tools from extreme value theory (e.g. Coles, 2001; Ribatet, 2007) are applied for the first time in the field of stratospheric ozone research, as statistical analysis showed that previously used concepts assuming a Gaussian distribution (e.g. fixed deviations from mean values) of total ozone data do not address the internal data structure concerning extremes adequately. The study illustrates that tools based on extreme value theory are appropriate to identify ozone extremes and to describe the tails of the world's longest total ozone record (Arosa, Switzerland - for details see Staehelin et al., 1998a,b) (Rieder et al., 2010a). A daily moving threshold was implemented for consideration of the seasonal cycle in total ozone. The frequency of days with extreme low (termed ELOs) and extreme high (termed EHOs) total ozone and the influence of those on mean values and trends is analyzed for Arosa total ozone time series. The results show (a) an increase in ELOs and (b) a decrease in EHOs during the last decades and (c) that the overall trend during the 1970s and 1980s in total ozone is strongly dominated by changes in these extreme events. After removing the extremes, the time series shows a strongly reduced trend (reduction by a factor of 2.5 for trend in annual mean). Furthermore, it is shown that the fitted model represents the tails of the total ozone data set with very high accuracy over the entire range (including absolute monthly minima and maxima). Also the frequency distribution of ozone mini-holes (using constant thresholds) can be calculated with high accuracy. Analyzing the tails instead of a small fraction of days below constant thresholds provides deeper insight in time series properties. Excursions in the frequency of extreme events reveal "fingerprints" of dynamical factors such as ENSO or NAO, and chemical factors, such as cold Arctic vortex ozone losses, as well as major volcanic eruptions of the 20th century (e.g. Gunung Agung, El Chich

The extremity function index (EFI), a disability severity measure for neuromuscular diseases : psychometric evaluation

NARCIS (Netherlands)

Bos, Isaac; Wynia, Klaske; Drost, Gea; Almansa, Josué; Kuks, Joannes

2017-01-01

OBJECTIVE: To adapt and to combine the self-report Upper Extremity Functional Index and Lower Extremity Function Scale, for the assessment of disability severity in patients with a neuromuscular disease and to examine its psychometric properties in order to make it suitable for indicating disease

Numerical tools to predict the environmental loads for offshore structures under extreme weather conditions

Science.gov (United States)

Wu, Yanling

2018-05-01

In this paper, the extreme waves were generated using the open source computational fluid dynamic (CFD) tools — OpenFOAM and Waves2FOAM — using linear and nonlinear NewWave input. They were used to conduct the numerical simulation of the wave impact process. Numerical tools based on first-order (with and without stretching) and second-order NewWave are investigated. The simulation to predict force loading for the offshore platform under the extreme weather condition is implemented and compared.

Strong laws for L- and U-statistics

NARCIS (Netherlands)

Aaronson, J; Burton, R; Dehling, H; Gilat, D; Hill, T; Weiss, B

Strong laws of large numbers are given for L-statistics (linear combinations of order statistics) and for U-statistics (averages of kernels of random samples) for ergodic stationary processes, extending classical theorems; of Hoeffding and of Helmers for lid sequences. Examples are given to show

Probing dark energy models with extreme pairwise velocities of galaxy clusters from the DEUS-FUR simulations

Science.gov (United States)

Bouillot, Vincent R.; Alimi, Jean-Michel; Corasaniti, Pier-Stefano; Rasera, Yann

2015-06-01

Observations of colliding galaxy clusters with high relative velocity probe the tail of the halo pairwise velocity distribution with the potential of providing a powerful test of cosmology. As an example it has been argued that the discovery of the Bullet Cluster challenges standard Λ cold dark matter (ΛCDM) model predictions. Halo catalogues from N-body simulations have been used to estimate the probability of Bullet-like clusters. However, due to simulation volume effects previous studies had to rely on a Gaussian extrapolation of the pairwise velocity distribution to high velocities. Here, we perform a detail analysis using the halo catalogues from the Dark Energy Universe Simulation Full Universe Runs (DEUS-FUR), which enables us to resolve the high-velocity tail of the distribution and study its dependence on the halo mass definition, redshift and cosmology. Building upon these results, we estimate the probability of Bullet-like systems in the framework of Extreme Value Statistics. We show that the tail of extreme pairwise velocities significantly deviates from that of a Gaussian, moreover it carries an imprint of the underlying cosmology. We find the Bullet Cluster probability to be two orders of magnitude larger than previous estimates, thus easing the tension with the ΛCDM model. Finally, the comparison of the inferred probabilities for the different DEUS-FUR cosmologies suggests that observations of extreme interacting clusters can provide constraints on dark energy models complementary to standard cosmological tests.

Gravo-Aeroelastic Scaling for Extreme-Scale Wind Turbines

Energy Technology Data Exchange (ETDEWEB)

Fingersh, Lee J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Loth, Eric [University of Virginia; Kaminski, Meghan [University of Virginia; Qin, Chao [University of Virginia; Griffith, D. Todd [Sandia National Laboratories

2017-06-09

A scaling methodology is described in the present paper for extreme-scale wind turbines (rated at 10 MW or more) that allow their sub-scale turbines to capture their key blade dynamics and aeroelastic deflections. For extreme-scale turbines, such deflections and dynamics can be substantial and are primarily driven by centrifugal, thrust and gravity forces as well as the net torque. Each of these are in turn a function of various wind conditions, including turbulence levels that cause shear, veer, and gust loads. The 13.2 MW rated SNL100-03 rotor design, having a blade length of 100-meters, is herein scaled to the CART3 wind turbine at NREL using 25% geometric scaling and blade mass and wind speed scaled by gravo-aeroelastic constraints. In order to mimic the ultralight structure on the advanced concept extreme-scale design the scaling results indicate that the gravo-aeroelastically scaled blades for the CART3 are be three times lighter and 25% longer than the current CART3 blades. A benefit of this scaling approach is that the scaled wind speeds needed for testing are reduced (in this case by a factor of two), allowing testing under extreme gust conditions to be much more easily achieved. Most importantly, this scaling approach can investigate extreme-scale concepts including dynamic behaviors and aeroelastic deflections (including flutter) at an extremely small fraction of the full-scale cost.

Clinical application of lower extremity CTA and lower extremity perfusion CT as a method of diagnostic for lower extremity atherosclerotic obliterans

Energy Technology Data Exchange (ETDEWEB)

Moon, Il Bong; Dong, Kyung Rae [Dept. Radiological Technology, Gwangju Health University, Gwangju (Korea, Republic of); Goo, Eun Hoe [Dept. Radiological Science, Cheongju University, Cheongju (Korea, Republic of)

2016-11-15

The purpose of this study was to assess clinical application of lower extremity CTA and lower extremity perfusion CT as a method of diagnostic for lower extremity atherosclerotic obliterans. From January to July 2016, 30 patients (mean age, 68) were studied with lower extremity CTA and lower extremity perfusion CT. 128 channel multi-detector row CT scans were acquired with a CT scanner (SOMATOM Definition Flash, Siemens medical solution, Germany) of lower extremity perfusion CT and lower extremity CTA. Acquired images were reconstructed with 3D workstation (Leonardo, Siemens, Germany). Site of lower extremity arterial occlusive and stenosis lesions were detected superficial femoral artery 36.6%, popliteal artery 23.4%, external iliac artery 16.7%, common femoral artery 13.3%, peroneal artery 10%. The mean total DLP comparison of lower extremity perfusion CT and lower extremity CTA, 650 mGy-cm and 675 mGy-cm, respectively. Lower extremity perfusion CT and lower extremity CTA were realized that were never be two examination that were exactly the same legions. Future through the development of lower extremity perfusion CT soft ware programs suggest possible clinical applications.

Thermodynamics of extremal rotating thin shells in an extremal BTZ spacetime and the extremal black hole entropy

Science.gov (United States)

Lemos, José P. S.; Minamitsuji, Masato; Zaslavskii, Oleg B.

2017-02-01

In a (2 +1 )-dimensional spacetime with a negative cosmological constant, the thermodynamics and the entropy of an extremal rotating thin shell, i.e., an extremal rotating ring, are investigated. The outer and inner regions with respect to the shell are taken to be the Bañados-Teitelbom-Zanelli (BTZ) spacetime and the vacuum ground state anti-de Sitter spacetime, respectively. By applying the first law of thermodynamics to the extremal thin shell, one shows that the entropy of the shell is an arbitrary well-behaved function of the gravitational area A+ alone, S =S (A+). When the thin shell approaches its own gravitational radius r+ and turns into an extremal rotating BTZ black hole, it is found that the entropy of the spacetime remains such a function of A+, both when the local temperature of the shell at the gravitational radius is zero and nonzero. It is thus vindicated by this analysis that extremal black holes, here extremal BTZ black holes, have different properties from the corresponding nonextremal black holes, which have a definite entropy, the Bekenstein-Hawking entropy S (A+)=A/+4G , where G is the gravitational constant. It is argued that for extremal black holes, in particular for extremal BTZ black holes, one should set 0 ≤S (A+)≤A/+4G;i.e., the extremal black hole entropy has values in between zero and the maximum Bekenstein-Hawking entropy A/+4 G . Thus, rather than having just two entropies for extremal black holes, as previous results have debated, namely, 0 and A/+4 G , it is shown here that extremal black holes, in particular extremal BTZ black holes, may have a continuous range of entropies, limited by precisely those two entropies. Surely, the entropy that a particular extremal black hole picks must depend on past processes, notably on how it was formed. A remarkable relation between the third law of thermodynamics and the impossibility for a massive body to reach the velocity of light is also found. In addition, in the procedure, it

Stabilised frequency of extreme positive Indian Ocean Dipole under 1.5 °C warming.

Science.gov (United States)

Cai, Wenju; Wang, Guojian; Gan, Bolan; Wu, Lixin; Santoso, Agus; Lin, Xiaopei; Chen, Zhaohui; Jia, Fan; Yamagata, Toshio

2018-04-12

Extreme positive Indian Ocean Dipole (pIOD) affects weather, agriculture, ecosystems, and public health worldwide, particularly when exacerbated by an extreme El Niño. The Paris Agreement aims to limit warming below 2 °C and ideally below 1.5 °C in global mean temperature (GMT), but how extreme pIOD will respond to this target is unclear. Here we show that the frequency increases linearly as the warming proceeds, and doubles at 1.5 °C warming from the pre-industrial level (statistically significant above the 90% confidence level), underscored by a strong intermodel agreement with 11 out of 13 models producing an increase. However, in sharp contrast to a continuous increase in extreme El Niño frequency long after GMT stabilisation, the extreme pIOD frequency peaks as the GMT stabilises. The contrasting response corresponds to a 50% reduction in frequency of an extreme El Niño preceded by an extreme pIOD from that projected under a business-as-usual scenario.

Optimal heavy tail estimation – Part 1: Order selection

Directory of Open Access Journals (Sweden)

M. Mudelsee

2017-12-01

Full Text Available The tail probability, P, of the distribution of a variable is important for risk analysis of extremes. Many variables in complex geophysical systems show heavy tails, where P decreases with the value, x, of a variable as a power law with a characteristic exponent, α. Accurate estimation of α on the basis of data is currently hindered by the problem of the selection of the order, that is, the number of largest x values to utilize for the estimation. This paper presents a new, widely applicable, data-adaptive order selector, which is based on computer simulations and brute force search. It is the first in a set of papers on optimal heavy tail estimation. The new selector outperforms competitors in a Monte Carlo experiment, where simulated data are generated from stable distributions and AR(1 serial dependence. We calculate error bars for the estimated α by means of simulations. We illustrate the method on an artificial time series. We apply it to an observed, hydrological time series from the River Elbe and find an estimated characteristic exponent of 1.48 ± 0.13. This result indicates finite mean but infinite variance of the statistical distribution of river runoff.

A Statistical Methodology for Determination of Safety Systems Actuation Setpoints Based on Extreme Value Statistics

Directory of Open Access Journals (Sweden)

D. R. Novog

2008-01-01

Full Text Available This paper provides a novel and robust methodology for determination of nuclear reactor trip setpoints which accounts for uncertainties in input parameters and models, as well as accounting for the variations in operating states that periodically occur. Further it demonstrates that in performing best estimate and uncertainty calculations, it is critical to consider the impact of all fuel channels and instrumentation in the integration of these uncertainties in setpoint determination. This methodology is based on the concept of a true trip setpoint, which is the reactor setpoint that would be required in an ideal situation where all key inputs and plant responses were known, such that during the accident sequence a reactor shutdown will occur which just prevents the acceptance criteria from being exceeded. Since this true value cannot be established, the uncertainties in plant simulations and plant measurements as well as operational variations which lead to time changes in the true value of initial conditions must be considered. This paper presents the general concept used to determine the actuation setpoints considering the uncertainties and changes in initial conditions, and allowing for safety systems instrumentation redundancy. The results demonstrate unique statistical behavior with respect to both fuel and instrumentation uncertainties which has not previously been investigated.

Flooding hazards from sea extremes and subsidence

DEFF Research Database (Denmark)

Sørensen, Carlo; Vognsen, Karsten; Broge, Niels

2015-01-01

of tide gauge records, statistics that allow also for projections of SLR, meteorological variability, and extremes with a very low probability of occurrence are provided. Land movement is researched with a focus on short term surface height variability in the groundwater-ocean interface that, together...... with longer term processes, may cause substantial subsidence and impact future water management and adaptation strategies in flood prone coastal areas. Field studies’ results from repeated precise levelling, GPS setups, and ocean and groundwater level monitoring in Thyborøn and Aarhus are integrated...

Extreme climate in China. Facts, simulation and projection

Energy Technology Data Exchange (ETDEWEB)

Wang, Hui-Jun; Sun, Jian-Qi; Chen, Huo-Po; Zhu, Ya-Li; Zhang, Ying; Jiang, Da-Bang; Lang, Xian-Mei; Fan, Ke; Yu, En-Tao [Chinese Academy of Sciences, Beijing (China). Inst. of Atmospheric Physics; Yang, Song [NOAA Climate Prediction Center, Camp Springs, MD (United States)

2012-06-15

In this paper, studies on extreme climate in China including extreme temperature and precipitation, dust weather activity, tropical cyclone activity, intense snowfall and cold surge activity, floods, and droughts are reviewed based on the peer-reviewed publications in recent decades. The review is focused first on the climatological features, variability, and trends in the past half century and then on simulations and projections based on global and regional climate models. As the annual mean surface air temperature (SAT) increased throughout China, heat wave intensity and frequency overall increased in the past half century, with a large rate after the 1980s. The daily or yearly minimum SAT increased more significantly than the mean or maximum SAT. The long-term change in precipitation is predominantly characterized by the so-called southern flood and northern drought pattern in eastern China and by the overall increase over Northwest China. The interdecadal variation of monsoon, represented by the monsoon weakening in the end of 1970s, is largely responsible for this change in mean precipitation. Precipitation-related extreme events (e.g., heavy rainfall and intense snowfall) have become more frequent and intense generally over China in the recent years, with large spatial features. Dust weather activity, however, has become less frequent over northern China in the recent years, as result of weakened cold surge activity, reinforced precipitation, and improved vegetation condition. State-of-the-art climate models are capable of reproducing some features of the mean climate and extreme climate events. However, discrepancies among models in simulating and projecting the mean and extreme climate are also demonstrated by many recent studies. Regional models with higher resolutions often perform better than global models. To predict and project climate variations and extremes, many new approaches and schemes based on dynamical models, statistical methods, or their

Comparison on the Analysis on PM10 Data based on Average and Extreme Series

Directory of Open Access Journals (Sweden)

Mohd Amin Nor Azrita

2018-01-01

Full Text Available The main concern in environmental issue is on extreme phenomena (catastrophic instead of common events. However, most statistical approaches are concerned primarily with the centre of a distribution or on the average value rather than the tail of the distribution which contains the extreme observations. The concept of extreme value theory affords attention to the tails of distribution where standard models are proved unreliable to analyse extreme series. High level of particulate matter (PM10 is a common environmental problem which causes various impacts to human health and material damages. If the main concern is on extreme events, then extreme value analysis provides the best result with significant evidence. The monthly average and monthly maxima PM10 data for Perlis from 2003 to 2014 were analysed. Forecasting for average data is made by Holt-Winters method while return level determine the predicted value of extreme events that occur on average once in a certain period. The forecasting from January 2015 to December 2016 for average data found that the highest forecasted value is 58.18 (standard deviation 18.45 on February 2016 while return level achieved 253.76 units for 24 months (2015-2016 return periods.

Statistical modeling of CMIP5 projected changes in extreme wet spells over China in the late 21st century

Science.gov (United States)

Zhu, Lianhua; Li, Yun; Jiang, Zhihong

2017-08-01

The observed intensity, frequency, and duration (IFD) of summer wet spells, defined here as extreme events with one or more consecutive days in which daily precipitation exceeds a given threshold (the 95th percentile), and their future changes in RCP4.5 and RCP8.5 in the late 21st century over China, are investigated by using the wet spell model (WSM) and by extending the point process approach to extreme value analysis. Wet spell intensity is modeled by a conditional generalized Pareto distribution, frequency by a Poisson distribution, and duration by a geometric distribution, respectively. The WSM is able to realistically model summer extreme rainfall spells during 1961-2005, as verified with observations at 553 stations throughout China. To minimize the impact of systematic biases over China in the global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), five best GCMs are selected based on their performance to reproduce observed wet spell IFD and average precipitation during the historical period. Furthermore, a quantile-quantile scaling correction procedure is proposed and applied to produce ensemble projections of wet spell IFD and corresponding probability distributions. The results show that in the late 21st century, most of China will experience more extreme rainfall and less low-intensity rainfall. The intensity and frequency of wet spells are projected to increase considerably, while the duration of wet spells will increase but to a much less extent. The IFD changes in RCP8.5 are in general much larger than those in RCP4.5.

Progression of disease preceding lower extremity amputation in Denmark

DEFF Research Database (Denmark)

Jensen, Pia Søe; Petersen, Janne; Kirketerp-Møller, Klaus

2017-01-01

OBJECTIVES: Patients with non-traumatic lower extremity amputation are characterised by high age, multi-morbidity and polypharmacy and long-term complications of atherosclerosis and diabetes. To ensure early identification of patients at risk of amputation, we need to gain knowledge about...... the progression of diseases related to lower extremity amputations during the years preceding the amputation. DESIGN: A retrospective population-based national registry study. SETTING: The study includes data on demographics, diagnoses, surgery, medications and healthcare services from five national registries....... Data were retrieved from 14 years before until 1 year after the amputation. Descriptive statistics were used to describe the progression of diseases and use of medication and healthcare services. PARTICIPANTS: An unselected cohort of patients (≥50 years; n=2883) subjected to a primary non...

Overshooting Effects in Nonequilibrium Ordering Dynamics

DEFF Research Database (Denmark)

Gilhøj, Henriette; Jeppesen, Claus; Mouritsen, Ole G.

1995-01-01

Using Monte Carlo simulation on the simplest possible statistical mechanical model, the two-dimensional, nonconserved kinetic Ising model that undergoes an order-disorder transition, we show that the local order of the ordering domains, subsequent to a temperature quench, transiently overshoots...

Extreme value distributions

CERN Document Server

Ahsanullah, Mohammad

2016-01-01

The aim of the book is to give a through account of the basic theory of extreme value distributions. The book cover a wide range of materials available to date. The central ideas and results of extreme value distributions are presented. The book rwill be useful o applied statisticians as well statisticians interrested to work in the area of extreme value distributions.vmonograph presents the central ideas and results of extreme value distributions.The monograph gives self-contained of theory and applications of extreme value distributions.

Evaluation of precipitation extremes over the Asian domain: observation and modelling studies

Science.gov (United States)

Kim, In-Won; Oh, Jaiho; Woo, Sumin; Kripalani, R. H.

2018-04-01

In this study, a comparison in the precipitation extremes as exhibited by the seven reference datasets is made to ascertain whether the inferences based on these datasets agree or they differ. These seven datasets, roughly grouped in three categories i.e. rain-gauge based (APHRODITE, CPC-UNI), satellite-based (TRMM, GPCP1DD) and reanalysis based (ERA-Interim, MERRA, and JRA55), having a common data period 1998-2007 are considered. Focus is to examine precipitation extremes in the summer monsoon rainfall over South Asia, East Asia and Southeast Asia. Measures of extreme precipitation include the percentile thresholds, frequency of extreme precipitation events and other quantities. Results reveal that the differences in displaying extremes among the datasets are small over South Asia and East Asia but large differences among the datasets are displayed over the Southeast Asian region including the maritime continent. Furthermore, precipitation data appear to be more consistent over East Asia among the seven datasets. Decadal trends in extreme precipitation are consistent with known results over South and East Asia. No trends in extreme precipitation events are exhibited over Southeast Asia. Outputs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulation data are categorized as high, medium and low-resolution models. The regions displaying maximum intensity of extreme precipitation appear to be dependent on model resolution. High-resolution models simulate maximum intensity of extreme precipitation over the Indian sub-continent, medium-resolution models over northeast India and South China and the low-resolution models over Bangladesh, Myanmar and Thailand. In summary, there are differences in displaying extreme precipitation statistics among the seven datasets considered here and among the 29 CMIP5 model data outputs.

[The research protocol VI: How to choose the appropriate statistical test. Inferential statistics].

Science.gov (United States)

Flores-Ruiz, Eric; Miranda-Novales, María Guadalupe; Villasís-Keever, Miguel Ángel

2017-01-01

The statistical analysis can be divided in two main components: descriptive analysis and inferential analysis. An inference is to elaborate conclusions from the tests performed with the data obtained from a sample of a population. Statistical tests are used in order to establish the probability that a conclusion obtained from a sample is applicable to the population from which it was obtained. However, choosing the appropriate statistical test in general poses a challenge for novice researchers. To choose the statistical test it is necessary to take into account three aspects: the research design, the number of measurements and the scale of measurement of the variables. Statistical tests are divided into two sets, parametric and nonparametric. Parametric tests can only be used if the data show a normal distribution. Choosing the right statistical test will make it easier for readers to understand and apply the results.

The research protocol VI: How to choose the appropriate statistical test. Inferential statistics

Directory of Open Access Journals (Sweden)

Eric Flores-Ruiz

2017-10-01

Full Text Available The statistical analysis can be divided in two main components: descriptive analysis and inferential analysis. An inference is to elaborate conclusions from the tests performed with the data obtained from a sample of a population. Statistical tests are used in order to establish the probability that a conclusion obtained from a sample is applicable to the population from which it was obtained. However, choosing the appropriate statistical test in general poses a challenge for novice researchers. To choose the statistical test it is necessary to take into account three aspects: the research design, the number of measurements and the scale of measurement of the variables. Statistical tests are divided into two sets, parametric and nonparametric. Parametric tests can only be used if the data show a normal distribution. Choosing the right statistical test will make it easier for readers to understand and apply the results.

Software challenges in extreme scale systems

International Nuclear Information System (INIS)

Sarkar, Vivek; Harrod, William; Snavely, Allan E

2009-01-01

Computer systems anticipated in the 2015 - 2020 timeframe are referred to as Extreme Scale because they will be built using massive multi-core processors with 100's of cores per chip. The largest capability Extreme Scale system is expected to deliver Exascale performance of the order of 10 18 operations per second. These systems pose new critical challenges for software in the areas of concurrency, energy efficiency and resiliency. In this paper, we discuss the implications of the concurrency and energy efficiency challenges on future software for Extreme Scale Systems. From an application viewpoint, the concurrency and energy challenges boil down to the ability to express and manage parallelism and locality by exploring a range of strong scaling and new-era weak scaling techniques. For expressing parallelism and locality, the key challenges are the ability to expose all of the intrinsic parallelism and locality in a programming model, while ensuring that this expression of parallelism and locality is portable across a range of systems. For managing parallelism and locality, the OS-related challenges include parallel scalability, spatial partitioning of OS and application functionality, direct hardware access for inter-processor communication, and asynchronous rather than interrupt-driven events, which are accompanied by runtime system challenges for scheduling, synchronization, memory management, communication, performance monitoring, and power management. We conclude by discussing the importance of software-hardware co-design in addressing the fundamental challenges for application enablement on Extreme Scale systems.

Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

DEFF Research Database (Denmark)

Sunyer Pinya, Maria Antonia; Hundecha, Y.; Lawrence, D.

impact studies. Four methods are based on change factors and four are bias correction methods. The change factor methods perturb the observations according to changes in precipitation properties estimated from the Regional Climate Models (RCMs). The bias correction methods correct the output from...... the RCMs. The eight methods are used to downscale precipitation output from fifteen RCMs from the ENSEMBLES project for eleven catchments in Europe. The performance of the bias correction methods depends on the catchment, but in all cases they represent an improvement compared to RCM output. The overall...... results point to an increase in extreme precipitation in all the catchments in winter and in most catchments in summer. For each catchment, the results tend to agree on the direction of the change but differ in the magnitude. These differences can be mainly explained due to differences in the RCMs....

Compliance strategy for statistically based neutron overpower protection safety analysis methodology

International Nuclear Information System (INIS)

Holliday, E.; Phan, B.; Nainer, O.

2009-01-01

The methodology employed in the safety analysis of the slow Loss of Regulation (LOR) event in the OPG and Bruce Power CANDU reactors, referred to as Neutron Overpower Protection (NOP) analysis, is a statistically based methodology. Further enhancement to this methodology includes the use of Extreme Value Statistics (EVS) for the explicit treatment of aleatory and epistemic uncertainties, and probabilistic weighting of the initial core states. A key aspect of this enhanced NOP methodology is to demonstrate adherence, or compliance, with the analysis basis. This paper outlines a compliance strategy capable of accounting for the statistical nature of the enhanced NOP methodology. (author)

Regional tendencies of extreme wind characteristics in Hungary

Science.gov (United States)

Radics, Dr.; Bartholy, Dr.; Péliné

2009-09-01

Human activities have substantial effects on climate system. It has already accepted that change in the long-term climatic mean state will have significant consequences in the global economy and society, but the most important effects of climate change may come from changes in the intensity and frequency of climatic extremes. It is therefore of great interest to document the extremes of surface wind that could assist in estimating the regional effects of climate change. The research presented is based on 34-year-long (1975-2008) wind (speed, direction, and wind gust) data sets of 36 Hungarian synoptic meteorological stations. After processing (including digitalisation of old instrumental records, quality control and homogenisation of wind time series) the measured wind data sets, time series and complex wind climate analysis were carried out. Spatial and temporal distributions of mean and extreme wind climate characteristics were estimated, wind extremes and trends were interpolated and mapped over the country. Finally, measured and reanalysed (ERA40) wind data were compared over Hungary, in order to verify not only the validity of ERA40 reanalysed data sets, but the adaptability of climate simulation results in estimation of regional climate change effects.

Microscopic cascading of second-order molecular nonlinearity: New design principles for enhancing third-order nonlinearity.

Science.gov (United States)

Baev, Alexander; Autschbach, Jochen; Boyd, Robert W; Prasad, Paras N

2010-04-12

Herein, we develop a phenomenological model for microscopic cascading and substantiate it with ab initio calculations. It is shown that the concept of local microscopic cascading of a second-order nonlinearity can lead to a third-order nonlinearity, without introducing any new loss mechanisms that could limit the usefulness of our approach. This approach provides a new molecular design protocol, in which the current great successes achieved in producing molecules with extremely large second-order nonlinearity can be used in a supra molecular organization in a preferred orientation to generate very large third-order response magnitudes. The results of density functional calculations for a well-known second-order molecule, (para)nitroaniline, show that a head-to-tail dimer configuration exhibits enhanced third-order nonlinearity, in agreement with the phenomenological model which suggests that such an arrangement will produce cascading due to local field effects.

Hobsbawm y el siglo XX: A propósito de Age of Extremes

Directory of Open Access Journals (Sweden)

Roy Hora

1998-06-01

Full Text Available This essay analyses Age of Extremes, Eric Hobsbawm's last book. Age of Extremes is discussed in the context of Hobsbawm's approach to XIX and XX century world history. Hobsbawm's intellectual and political commitments are also taken into consideration in order to understand the way in which he examines and describes modern world history.

Statistical Optics

Science.gov (United States)

Goodman, Joseph W.

2000-07-01

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I RIchard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Cuthbert Daniel Fitting Equations to Data: Computer Analysis of Multifactor Data, Second Edition Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research

Possible future changes in South East Australian frost frequency: an inter-comparison of statistical downscaling approaches