Computation of the Complex Probability Function

Energy Technology Data Exchange (ETDEWEB)

Trainer, Amelia Jo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ledwith, Patrick John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-08-22

The complex probability function is important in many areas of physics and many techniques have been developed in an attempt to compute it for some z quickly and e ciently. Most prominent are the methods that use Gauss-Hermite quadrature, which uses the roots of the n^th degree Hermite polynomial and corresponding weights to approximate the complex probability function. This document serves as an overview and discussion of the use, shortcomings, and potential improvements on the Gauss-Hermite quadrature for the complex probability function.

An Alternative Version of Conditional Probabilities and Bayes' Rule: An Application of Probability Logic

Science.gov (United States)

Satake, Eiki; Amato, Philip P.

2008-01-01

This paper presents an alternative version of formulas of conditional probabilities and Bayes' rule that demonstrate how the truth table of elementary mathematical logic applies to the derivations of the conditional probabilities of various complex, compound statements. This new approach is used to calculate the prior and posterior probabilities…

Maximum Entropy and Probability Kinematics Constrained by Conditionals

Directory of Open Access Journals (Sweden)

Stefan Lukits

2015-03-01

Full Text Available Two open questions of inductive reasoning are solved: (1 does the principle of maximum entropy (PME give a solution to the obverse Majerník problem; and (2 isWagner correct when he claims that Jeffrey’s updating principle (JUP contradicts PME? Majerník shows that PME provides unique and plausible marginal probabilities, given conditional probabilities. The obverse problem posed here is whether PME also provides such conditional probabilities, given certain marginal probabilities. The theorem developed to solve the obverse Majerník problem demonstrates that in the special case introduced by Wagner PME does not contradict JUP, but elegantly generalizes it and offers a more integrated approach to probability updating.

Conditional probabilities in Ponzano-Regge minisuperspace

International Nuclear Information System (INIS)

Petryk, Roman; Schleich, Kristin

2003-01-01

We examine the Hartle-Hawking no-boundary initial state for the Ponzano-Regge formulation of gravity in three dimensions. We consider the behavior of conditional probabilities and expectation values for geometrical quantities in this initial state for a simple minisuperspace model consisting of a two-parameter set of anisotropic geometries on a 2-sphere boundary. We find dependence on the cutoff used in the construction of Ponzano-Regge amplitudes for expectation values of edge lengths. However, these expectation values are cutoff independent when computed in certain, but not all, conditional probability distributions. Conditions that yield cutoff independent expectation values are those that constrain the boundary geometry to a finite range of edge lengths. We argue that such conditions have a correspondence to fixing a range of local time, as classically associated with the area of a surface for spatially closed cosmologies. Thus these results may hint at how classical spacetime emerges from quantum amplitudes

Probability in reasoning: a developmental test on conditionals.

Science.gov (United States)

Barrouillet, Pierre; Gauffroy, Caroline

2015-04-01

Probabilistic theories have been claimed to constitute a new paradigm for the psychology of reasoning. A key assumption of these theories is captured by what they call the Equation, the hypothesis that the meaning of the conditional is probabilistic in nature and that the probability of If p then q is the conditional probability, in such a way that P(if p then q)=P(q|p). Using the probabilistic truth-table task in which participants are required to evaluate the probability of If p then q sentences, the present study explored the pervasiveness of the Equation through ages (from early adolescence to adulthood), types of conditionals (basic, causal, and inducements) and contents. The results reveal that the Equation is a late developmental achievement only endorsed by a narrow majority of educated adults for certain types of conditionals depending on the content they involve. Age-related changes in evaluating the probability of all the conditionals studied closely mirror the development of truth-value judgements observed in previous studies with traditional truth-table tasks. We argue that our modified mental model theory can account for this development, and hence for the findings related with the probability task, which do not consequently support the probabilistic approach of human reasoning over alternative theories. Copyright © 2014 Elsevier B.V. All rights reserved.

Retrocausality and conditional probability

International Nuclear Information System (INIS)

Stuart, C.I.J.M.

1989-01-01

Costa de Beauregard has proposed that physical causality be identified with conditional probability. The proposal is shown to be vulnerable on two accounts. The first, though mathematically trivial, seems to be decisive so far as the current formulation of the proposal is concerned. The second lies in a physical inconsistency which seems to have its source in a Copenhagenlike disavowal of realism in quantum mechanics. 6 refs. (Author)

Conditional probability on MV-algebras

Czech Academy of Sciences Publication Activity Database

Kroupa, Tomáš

2005-01-01

Roč. 149, č. 2 (2005), s. 369-381 ISSN 0165-0114 R&D Projects: GA AV ČR IAA2075302 Institutional research plan: CEZ:AV0Z10750506 Keywords : conditional probability * tribe * MV-algebra Subject RIV: BA - General Mathematics Impact factor: 1.039, year: 2005

Statistical learning of action: the role of conditional probability.

Science.gov (United States)

Meyer, Meredith; Baldwin, Dare

2011-12-01

Identification of distinct units within a continuous flow of human action is fundamental to action processing. Such segmentation may rest in part on statistical learning. In a series of four experiments, we examined what types of statistics people can use to segment a continuous stream involving many brief, goal-directed action elements. The results of Experiment 1 showed no evidence for sensitivity to conditional probability, whereas Experiment 2 displayed learning based on joint probability. In Experiment 3, we demonstrated that additional exposure to the input failed to engender sensitivity to conditional probability. However, the results of Experiment 4 showed that a subset of adults-namely, those more successful at identifying actions that had been seen more frequently than comparison sequences-were also successful at learning conditional-probability statistics. These experiments help to clarify the mechanisms subserving processing of intentional action, and they highlight important differences from, as well as similarities to, prior studies of statistical learning in other domains, including language.

Probability distribution of magnetization in the one-dimensional Ising model: effects of boundary conditions

Energy Technology Data Exchange (ETDEWEB)

Antal, T [Physics Department, Simon Fraser University, Burnaby, BC V5A 1S6 (Canada); Droz, M [Departement de Physique Theorique, Universite de Geneve, CH 1211 Geneva 4 (Switzerland); Racz, Z [Institute for Theoretical Physics, Eoetvoes University, 1117 Budapest, Pazmany setany 1/a (Hungary)

2004-02-06

Finite-size scaling functions are investigated both for the mean-square magnetization fluctuations and for the probability distribution of the magnetization in the one-dimensional Ising model. The scaling functions are evaluated in the limit of the temperature going to zero (T {yields} 0), the size of the system going to infinity (N {yields} {infinity}) while N[1 - tanh(J/k{sub B}T)] is kept finite (J being the nearest neighbour coupling). Exact calculations using various boundary conditions (periodic, antiperiodic, free, block) demonstrate explicitly how the scaling functions depend on the boundary conditions. We also show that the block (small part of a large system) magnetization distribution results are identical to those obtained for free boundary conditions.

Toward a generalized probability theory: conditional probabilities

International Nuclear Information System (INIS)

Cassinelli, G.

1979-01-01

The main mathematical object of interest in the quantum logic approach to the foundations of quantum mechanics is the orthomodular lattice and a set of probability measures, or states, defined by the lattice. This mathematical structure is studied per se, independently from the intuitive or physical motivation of its definition, as a generalized probability theory. It is thought that the building-up of such a probability theory could eventually throw light on the mathematical structure of Hilbert-space quantum mechanics as a particular concrete model of the generalized theory. (Auth.)

Computing exact bundle compliance control charts via probability generating functions.

Science.gov (United States)

Chen, Binchao; Matis, Timothy; Benneyan, James

2016-06-01

Compliance to evidenced-base practices, individually and in 'bundles', remains an important focus of healthcare quality improvement for many clinical conditions. The exact probability distribution of composite bundle compliance measures used to develop corresponding control charts and other statistical tests is based on a fairly large convolution whose direct calculation can be computationally prohibitive. Various series expansions and other approximation approaches have been proposed, each with computational and accuracy tradeoffs, especially in the tails. This same probability distribution also arises in other important healthcare applications, such as for risk-adjusted outcomes and bed demand prediction, with the same computational difficulties. As an alternative, we use probability generating functions to rapidly obtain exact results and illustrate the improved accuracy and detection over other methods. Numerical testing across a wide range of applications demonstrates the computational efficiency and accuracy of this approach.

Path probability of stochastic motion: A functional approach

Science.gov (United States)

Hattori, Masayuki; Abe, Sumiyoshi

2016-06-01

The path probability of a particle undergoing stochastic motion is studied by the use of functional technique, and the general formula is derived for the path probability distribution functional. The probability of finding paths inside a tube/band, the center of which is stipulated by a given path, is analytically evaluated in a way analogous to continuous measurements in quantum mechanics. Then, the formalism developed here is applied to the stochastic dynamics of stock price in finance.

A note on iterated function systems with discontinuous probabilities

International Nuclear Information System (INIS)

Jaroszewska, Joanna

2013-01-01

Highlights: ► Certain iterated function system with discontinuous probabilities is discussed. ► Existence of an invariant measure via the Schauder–Tychonov theorem is established. ► Asymptotic stability of the system under examination is proved. -- Abstract: We consider an example of an iterated function system with discontinuous probabilities. We prove that it posses an invariant probability measure. We also prove that it is asymptotically stable provided probabilities are positive

Probability and stochastic modeling

CERN Document Server

Rotar, Vladimir I

2012-01-01

Basic NotionsSample Space and EventsProbabilitiesCounting TechniquesIndependence and Conditional ProbabilityIndependenceConditioningThe Borel-Cantelli TheoremDiscrete Random VariablesRandom Variables and VectorsExpected ValueVariance and Other Moments. Inequalities for DeviationsSome Basic DistributionsConvergence of Random Variables. The Law of Large NumbersConditional ExpectationGenerating Functions. Branching Processes. Random Walk RevisitedBranching Processes Generating Functions Branching Processes Revisited More on Random WalkMarkov ChainsDefinitions and Examples. Probability Distributions of Markov ChainsThe First Step Analysis. Passage TimesVariables Defined on a Markov ChainErgodicity and Stationary DistributionsA Classification of States and ErgodicityContinuous Random VariablesContinuous DistributionsSome Basic Distributions Continuous Multivariate Distributions Sums of Independent Random Variables Conditional Distributions and ExpectationsDistributions in the General Case. SimulationDistribution F...

A probability evaluation method of early deterioration condition for the critical components of wind turbine generator systems

DEFF Research Database (Denmark)

Hu, Y.; Li, H.; Liao, X

2016-01-01

method of early deterioration condition for critical components based only on temperature characteristic parameters. First, the dynamic threshold of deterioration degree function was proposed by analyzing the operational data between temperature and rotor speed. Second, a probability evaluation method...... of early deterioration condition was presented. Finally, two cases showed the validity of the proposed probability evaluation method in detecting early deterioration condition and in tracking their further deterioration for the critical components.......This study determines the early deterioration condition of critical components for a wind turbine generator system (WTGS). Due to the uncertainty nature of the fluctuation and intermittence of wind, early deterioration condition evaluation poses a challenge to the traditional vibration...

Proposal for Modified Damage Probability Distribution Functions

DEFF Research Database (Denmark)

Pedersen, Preben Terndrup; Hansen, Peter Friis

1996-01-01

Immidiately following the Estonia disaster, the Nordic countries establishe a project entitled "Safety of Passenger/RoRo Vessels" As part of this project the present proposal for modified damage stability probability distribution functions has been developed. and submitted to "Sub-committee on st......Immidiately following the Estonia disaster, the Nordic countries establishe a project entitled "Safety of Passenger/RoRo Vessels" As part of this project the present proposal for modified damage stability probability distribution functions has been developed. and submitted to "Sub...

Off-critical local height probabilities on a plane and critical partition functions on a cylinder

Directory of Open Access Journals (Sweden)

Omar Foda

2018-03-01

Full Text Available We compute off-critical local height probabilities in regime-III restricted solid-on-solid models in a 4N-quadrant spiral geometry, with periodic boundary conditions in the angular direction, and fixed boundary conditions in the radial direction, as a function of N, the winding number of the spiral, and τ, the departure from criticality of the model, and observe that the result depends only on the product Nτ. In the limit N→1, τ→τ0, such that τ0 is finite, we recover the off-critical local height probability on a plane, τ0-away from criticality. In the limit N→∞, τ→0, such that Nτ=τ0 is finite, and following a conformal transformation, we obtain a critical partition function on a cylinder of aspect-ratio τ0. We conclude that the off-critical local height probability on a plane, τ0-away from criticality, is equal to a critical partition function on a cylinder of aspect-ratio τ0, in agreement with a result of Saleur and Bauer.

Modeling highway travel time distribution with conditional probability models

Energy Technology Data Exchange (ETDEWEB)

Oliveira Neto, Francisco Moraes [ORNL; Chin, Shih-Miao [ORNL; Hwang, Ho-Ling [ORNL; Han, Lee [University of Tennessee, Knoxville (UTK)

2014-01-01

ABSTRACT Under the sponsorship of the Federal Highway Administration's Office of Freight Management and Operations, the American Transportation Research Institute (ATRI) has developed performance measures through the Freight Performance Measures (FPM) initiative. Under this program, travel speed information is derived from data collected using wireless based global positioning systems. These telemetric data systems are subscribed and used by trucking industry as an operations management tool. More than one telemetric operator submits their data dumps to ATRI on a regular basis. Each data transmission contains truck location, its travel time, and a clock time/date stamp. Data from the FPM program provides a unique opportunity for studying the upstream-downstream speed distributions at different locations, as well as different time of the day and day of the week. This research is focused on the stochastic nature of successive link travel speed data on the continental United States Interstates network. Specifically, a method to estimate route probability distributions of travel time is proposed. This method uses the concepts of convolution of probability distributions and bivariate, link-to-link, conditional probability to estimate the expected distributions for the route travel time. Major contribution of this study is the consideration of speed correlation between upstream and downstream contiguous Interstate segments through conditional probability. The established conditional probability distributions, between successive segments, can be used to provide travel time reliability measures. This study also suggests an adaptive method for calculating and updating route travel time distribution as new data or information is added. This methodology can be useful to estimate performance measures as required by the recent Moving Ahead for Progress in the 21st Century Act (MAP 21).

Decision making generalized by a cumulative probability weighting function

Science.gov (United States)

dos Santos, Lindomar Soares; Destefano, Natália; Martinez, Alexandre Souto

2018-01-01

Typical examples of intertemporal decision making involve situations in which individuals must choose between a smaller reward, but more immediate, and a larger one, delivered later. Analogously, probabilistic decision making involves choices between options whose consequences differ in relation to their probability of receiving. In Economics, the expected utility theory (EUT) and the discounted utility theory (DUT) are traditionally accepted normative models for describing, respectively, probabilistic and intertemporal decision making. A large number of experiments confirmed that the linearity assumed by the EUT does not explain some observed behaviors, as nonlinear preference, risk-seeking and loss aversion. That observation led to the development of new theoretical models, called non-expected utility theories (NEUT), which include a nonlinear transformation of the probability scale. An essential feature of the so-called preference function of these theories is that the probabilities are transformed by decision weights by means of a (cumulative) probability weighting function, w(p) . We obtain in this article a generalized function for the probabilistic discount process. This function has as particular cases mathematical forms already consecrated in the literature, including discount models that consider effects of psychophysical perception. We also propose a new generalized function for the functional form of w. The limiting cases of this function encompass some parametric forms already proposed in the literature. Far beyond a mere generalization, our function allows the interpretation of probabilistic decision making theories based on the assumption that individuals behave similarly in the face of probabilities and delays and is supported by phenomenological models.

Probability functions in the context of signed involutive meadows

NARCIS (Netherlands)

Bergstra, J.A.; Ponse, A.

2016-01-01

The Kolmogorov axioms for probability functions are placed in the context of signed meadows. A completeness theorem is stated and proven for the resulting equational theory of probability calculus. Elementary definitions of probability theory are restated in this framework.

A generalized electron energy probability function for inductively coupled plasmas under conditions of nonlocal electron kinetics

Science.gov (United States)

Mouchtouris, S.; Kokkoris, G.

2018-01-01

A generalized equation for the electron energy probability function (EEPF) of inductively coupled Ar plasmas is proposed under conditions of nonlocal electron kinetics and diffusive cooling. The proposed equation describes the local EEPF in a discharge and the independent variable is the kinetic energy of electrons. The EEPF consists of a bulk and a depleted tail part and incorporates the effect of the plasma potential, Vp, and pressure. Due to diffusive cooling, the break point of the EEPF is eVp. The pressure alters the shape of the bulk and the slope of the tail part. The parameters of the proposed EEPF are extracted by fitting to measure EEPFs (at one point in the reactor) at different pressures. By coupling the proposed EEPF with a hybrid plasma model, measurements in the gaseous electronics conference reference reactor concerning (a) the electron density and temperature and the plasma potential, either spatially resolved or at different pressure (10-50 mTorr) and power, and (b) the ion current density of the electrode, are well reproduced. The effect of the choice of the EEPF on the results is investigated by a comparison to an EEPF coming from the Boltzmann equation (local electron kinetics approach) and to a Maxwellian EEPF. The accuracy of the results and the fact that the proposed EEPF is predefined renders its use a reliable alternative with a low computational cost compared to stochastic electron kinetic models at low pressure conditions, which can be extended to other gases and/or different electron heating mechanisms.

Probability distribution functions for intermittent scrape-off layer plasma fluctuations

Science.gov (United States)

Theodorsen, A.; Garcia, O. E.

2018-03-01

A stochastic model for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas has been constructed based on a super-position of uncorrelated pulses arriving according to a Poisson process. In the most common applications of the model, the pulse amplitudes are assumed exponentially distributed, supported by conditional averaging of large-amplitude fluctuations in experimental measurement data. This basic assumption has two potential limitations. First, statistical analysis of measurement data using conditional averaging only reveals the tail of the amplitude distribution to be exponentially distributed. Second, exponentially distributed amplitudes leads to a positive definite signal which cannot capture fluctuations in for example electric potential and radial velocity. Assuming pulse amplitudes which are not positive definite often make finding a closed form for the probability density function (PDF) difficult, even if the characteristic function remains relatively simple. Thus estimating model parameters requires an approach based on the characteristic function, not the PDF. In this contribution, the effect of changing the amplitude distribution on the moments, PDF and characteristic function of the process is investigated and a parameter estimation method using the empirical characteristic function is presented and tested on synthetically generated data. This proves valuable for describing intermittent fluctuations of all plasma parameters in the boundary region of magnetized plasmas.

Foundations of probability

International Nuclear Information System (INIS)

Fraassen, B.C. van

1979-01-01

The interpretation of probabilities in physical theories are considered, whether quantum or classical. The following points are discussed 1) the functions P(μ, Q) in terms of which states and propositions can be represented, are classical (Kolmogoroff) probabilities, formally speaking, 2) these probabilities are generally interpreted as themselves conditional, and the conditions are mutually incompatible where the observables are maximal and 3) testing of the theory typically takes the form of confronting the expectation values of observable Q calculated with probability measures P(μ, Q) for states μ; hence, of comparing the probabilities P(μ, Q)(E) with the frequencies of occurrence of the corresponding events. It seems that even the interpretation of quantum mechanics, in so far as it concerns what the theory says about the empirical (i.e. actual, observable) phenomena, deals with the confrontation of classical probability measures with observable frequencies. This confrontation is studied. (Auth./C.F.)

Statistical models based on conditional probability distributions

International Nuclear Information System (INIS)

Narayanan, R.S.

1991-10-01

We present a formulation of statistical mechanics models based on conditional probability distribution rather than a Hamiltonian. We show that it is possible to realize critical phenomena through this procedure. Closely linked with this formulation is a Monte Carlo algorithm, in which a configuration generated is guaranteed to be statistically independent from any other configuration for all values of the parameters, in particular near the critical point. (orig.)

On Farmer's line, probability density functions, and overall risk

International Nuclear Information System (INIS)

Munera, H.A.; Yadigaroglu, G.

1986-01-01

Limit lines used to define quantitative probabilistic safety goals can be categorized according to whether they are based on discrete pairs of event sequences and associated probabilities, on probability density functions (pdf's), or on complementary cumulative density functions (CCDFs). In particular, the concept of the well-known Farmer's line and its subsequent reinterpretations is clarified. It is shown that Farmer's lines are pdf's and, therefore, the overall risk (defined as the expected value of the pdf) that they represent can be easily calculated. It is also shown that the area under Farmer's line is proportional to probability, while the areas under CCDFs are generally proportional to expected value

Wigner function and the probability representation of quantum states

Directory of Open Access Journals (Sweden)

Man’ko Margarita A.

2014-01-01

Full Text Available The relation of theWigner function with the fair probability distribution called tomographic distribution or quantum tomogram associated with the quantum state is reviewed. The connection of the tomographic picture of quantum mechanics with the integral Radon transform of the Wigner quasidistribution is discussed. The Wigner–Moyal equation for the Wigner function is presented in the form of kinetic equation for the tomographic probability distribution both in quantum mechanics and in the classical limit of the Liouville equation. The calculation of moments of physical observables in terms of integrals with the state tomographic probability distributions is constructed having a standard form of averaging in the probability theory. New uncertainty relations for the position and momentum are written in terms of optical tomograms suitable for directexperimental check. Some recent experiments on checking the uncertainty relations including the entropic uncertainty relations are discussed.

Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization

Science.gov (United States)

Cavagnaro, Daniel R.; Pitt, Mark A.; Gonzalez, Richard; Myung, Jay I.

2014-01-01

Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments to investigate the extent to which different parametric forms of the probability weighting function can be discriminated using adaptive design optimization, a computer-based methodology that identifies and exploits model differences for the purpose of model discrimination. The simulation experiments show that the correct (data-generating) form can be conclusively discriminated from its competitors. The results of an empirical experiment reveal heterogeneity between participants in terms of the functional form, with two models (Prelec-2, Linear in Log Odds) emerging as the most common best-fitting models. The findings shed light on assumptions underlying these models. PMID:24453406

Conditional Probability Analysis: A Statistical Tool for Environmental Analysis.

Science.gov (United States)

The use and application of environmental conditional probability analysis (CPA) is relatively recent. The first presentation using CPA was made in 2002 at the New England Association of Environmental Biologists Annual Meeting in Newport. Rhode Island. CPA has been used since the...

Conditional probability of the tornado missile impact given a tornado occurrence

International Nuclear Information System (INIS)

Goodman, J.; Koch, J.E.

1982-01-01

Using an approach based on statistical mechanics, an expression for the probability of the first missile strike is developed. The expression depends on two generic parameters (injection probability eta(F) and height distribution psi(Z,F)), which are developed in this study, and one plant specific parameter (number of potential missiles N/sub p/). The expression for the joint probability of simultaneous impact of muitiple targets is also developed. This espression is applicable to calculation of the probability of common cause failure due to tornado missiles. It is shown that the probability of the first missile strike can be determined using a uniform missile distribution model. It is also shown that the conditional probability of the second strike, given the first, is underestimated by the uniform model. The probability of the second strike is greatly increased if the missiles are in clusters large enough to cover both targets

Study on conditional probability of surface rupture: effect of fault dip and width of seismogenic layer

Science.gov (United States)

Inoue, N.

2017-12-01

The conditional probability of surface ruptures is affected by various factors, such as shallow material properties, process of earthquakes, ground motions and so on. Toda (2013) pointed out difference of the conditional probability of strike and reverse fault by considering the fault dip and width of seismogenic layer. This study evaluated conditional probability of surface rupture based on following procedures. Fault geometry was determined from the randomly generated magnitude based on The Headquarters for Earthquake Research Promotion (2017) method. If the defined fault plane was not saturated in the assumed width of the seismogenic layer, the fault plane depth was randomly provided within the seismogenic layer. The logistic analysis was performed to two data sets: surface displacement calculated by dislocation methods (Wang et al., 2003) from the defined source fault, the depth of top of the defined source fault. The estimated conditional probability from surface displacement indicated higher probability of reverse faults than that of strike faults, and this result coincides to previous similar studies (i.e. Kagawa et al., 2004; Kataoka and Kusakabe, 2005). On the contrary, the probability estimated from the depth of the source fault indicated higher probability of thrust faults than that of strike and reverse faults, and this trend is similar to the conditional probability of PFDHA results (Youngs et al., 2003; Moss and Ross, 2011). The probability of combined simulated results of thrust and reverse also shows low probability. The worldwide compiled reverse fault data include low fault dip angle earthquake. On the other hand, in the case of Japanese reverse fault, there is possibility that the conditional probability of reverse faults with less low dip angle earthquake shows low probability and indicates similar probability of strike fault (i.e. Takao et al., 2013). In the future, numerical simulation by considering failure condition of surface by the source

Probability function of breaking-limited surface elevation. [wind generated waves of ocean

Science.gov (United States)

Tung, C. C.; Huang, N. E.; Yuan, Y.; Long, S. R.

1989-01-01

The effect of wave breaking on the probability function of surface elevation is examined. The surface elevation limited by wave breaking zeta sub b(t) is first related to the original wave elevation zeta(t) and its second derivative. An approximate, second-order, nonlinear, non-Gaussian model for zeta(t) of arbitrary but moderate bandwidth is presented, and an expression for the probability density function zeta sub b(t) is derived. The results show clearly that the effect of wave breaking on the probability density function of surface elevation is to introduce a secondary hump on the positive side of the probability density function, a phenomenon also observed in wind wave tank experiments.

Real analysis and probability

CERN Document Server

Ash, Robert B; Lukacs, E

1972-01-01

Real Analysis and Probability provides the background in real analysis needed for the study of probability. Topics covered range from measure and integration theory to functional analysis and basic concepts of probability. The interplay between measure theory and topology is also discussed, along with conditional probability and expectation, the central limit theorem, and strong laws of large numbers with respect to martingale theory.Comprised of eight chapters, this volume begins with an overview of the basic concepts of the theory of measure and integration, followed by a presentation of var

The force distribution probability function for simple fluids by density functional theory.

Science.gov (United States)

Rickayzen, G; Heyes, D M

2013-02-28

Classical density functional theory (DFT) is used to derive a formula for the probability density distribution function, P(F), and probability distribution function, W(F), for simple fluids, where F is the net force on a particle. The final formula for P(F) ∝ exp(-AF(2)), where A depends on the fluid density, the temperature, and the Fourier transform of the pair potential. The form of the DFT theory used is only applicable to bounded potential fluids. When combined with the hypernetted chain closure of the Ornstein-Zernike equation, the DFT theory for W(F) agrees with molecular dynamics computer simulations for the Gaussian and bounded soft sphere at high density. The Gaussian form for P(F) is still accurate at lower densities (but not too low density) for the two potentials, but with a smaller value for the constant, A, than that predicted by the DFT theory.

Probability-density-function characterization of multipartite entanglement

International Nuclear Information System (INIS)

Facchi, P.; Florio, G.; Pascazio, S.

2006-01-01

We propose a method to characterize and quantify multipartite entanglement for pure states. The method hinges upon the study of the probability density function of bipartite entanglement and is tested on an ensemble of qubits in a variety of situations. This characterization is also compared to several measures of multipartite entanglement

Optimizing an objective function under a bivariate probability model

NARCIS (Netherlands)

X. Brusset; N.M. Temme (Nico)

2007-01-01

htmlabstractThe motivation of this paper is to obtain an analytical closed form of a quadratic objective function arising from a stochastic decision process with bivariate exponential probability distribution functions that may be dependent. This method is applicable when results need to be

Robust functional statistics applied to Probability Density Function shape screening of sEMG data.

Science.gov (United States)

Boudaoud, S; Rix, H; Al Harrach, M; Marin, F

2014-01-01

Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.

Structure functions are not parton probabilities

International Nuclear Information System (INIS)

Brodsky, Stanley J.; Hoyer, Paul; Sannino, Francesco; Marchal, Nils; Peigne, Stephane

2002-01-01

The common view that structure functions measured in deep inelastic lepton scattering are determined by the probability of finding quarks and gluons in the target is not correct in gauge theory. We show that gluon exchange between the fast, outgoing partons and target spectators, which is usually assumed to be an irrelevant gauge artifact, affects the leading twist structure functions in a profound way. This observation removes the apparent contradiction between the projectile (eikonal) and target (parton model) views of diffractive and small x B phenomena. The diffractive scattering of the fast outgoing quarks on spectators in the target causes shadowing in the DIS cross section. Thus the depletion of the nuclear structure functions is not intrinsic to the wave function of the nucleus, but is a coherent effect arising from the destructive interference of diffractive channels induced by final state interactions. This is consistent with the Glauber-Gribov interpretation of shadowing as a rescattering effect

Prospect evaluation as a function of numeracy and probability denominator.

Science.gov (United States)

Millroth, Philip; Juslin, Peter

2015-05-01

This study examines how numeracy and probability denominator (a direct-ratio probability, a relative frequency with denominator 100, a relative frequency with denominator 10,000) affect the evaluation of prospects in an expected-value based pricing task. We expected that numeracy would affect the results due to differences in the linearity of number perception and the susceptibility to denominator neglect with different probability formats. An analysis with functional measurement verified that participants integrated value and probability into an expected value. However, a significant interaction between numeracy and probability format and subsequent analyses of the parameters of cumulative prospect theory showed that the manipulation of probability denominator changed participants' psychophysical response to probability and value. Standard methods in decision research may thus confound people's genuine risk attitude with their numerical capacities and the probability format used. Copyright © 2015 Elsevier B.V. All rights reserved.

Visualization techniques for spatial probability density function data

Directory of Open Access Journals (Sweden)

Udeepta D Bordoloi

2006-01-01

Full Text Available Novel visualization methods are presented for spatial probability density function data. These are spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We use clustering as a means to reduce the information contained in these datasets; and present two different ways of interpreting and clustering the data. The clustering methods are used on two datasets, and the results are discussed with the help of visualization techniques designed for the spatial probability data.

INVESTIGATION OF INFLUENCE OF ENCODING FUNCTION COMPLEXITY ON DISTRIBUTION OF ERROR MASKING PROBABILITY

Directory of Open Access Journals (Sweden)

A. B. Levina

2016-03-01

Full Text Available Error detection codes are mechanisms that enable robust delivery of data in unreliable communication channels and devices. Unreliable channels and devices are error-prone objects. Respectively, error detection codes allow detecting such errors. There are two classes of error detecting codes - classical codes and security-oriented codes. The classical codes have high percentage of detected errors; however, they have a high probability to miss an error in algebraic manipulation. In order, security-oriented codes are codes with a small Hamming distance and high protection to algebraic manipulation. The probability of error masking is a fundamental parameter of security-oriented codes. A detailed study of this parameter allows analyzing the behavior of the error-correcting code in the case of error injection in the encoding device. In order, the complexity of the encoding function plays an important role in the security-oriented codes. Encoding functions with less computational complexity and a low probability of masking are the best protection of encoding device against malicious acts. This paper investigates the influence of encoding function complexity on the error masking probability distribution. It will be shownthat the more complex encoding function reduces the maximum of error masking probability. It is also shown in the paper that increasing of the function complexity changes the error masking probability distribution. In particular, increasing of computational complexity decreases the difference between the maximum and average value of the error masking probability. Our resultshave shown that functions with greater complexity have smoothed maximums of error masking probability, which significantly complicates the analysis of error-correcting code by attacker. As a result, in case of complex encoding function the probability of the algebraic manipulation is reduced. The paper discusses an approach how to measure the error masking

An Alternative Teaching Method of Conditional Probabilities and Bayes' Rule: An Application of the Truth Table

Science.gov (United States)

Satake, Eiki; Vashlishan Murray, Amy

2015-01-01

This paper presents a comparison of three approaches to the teaching of probability to demonstrate how the truth table of elementary mathematical logic can be used to teach the calculations of conditional probabilities. Students are typically introduced to the topic of conditional probabilities--especially the ones that involve Bayes' rule--with…

Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States

Science.gov (United States)

Fram, Miranda S.; Belitz, Kenneth

2011-01-01

We use data from 1626 groundwater samples collected in California, primarily from public drinking water supply wells, to investigate the distribution of perchlorate in deep groundwater under natural conditions. The wells were sampled for the California Groundwater Ambient Monitoring and Assessment Priority Basin Project. We develop a logistic regression model for predicting probabilities of detecting perchlorate at concentrations greater than multiple threshold concentrations as a function of climate (represented by an aridity index) and potential anthropogenic contributions of perchlorate (quantified as an anthropogenic score, AS). AS is a composite categorical variable including terms for nitrate, pesticides, and volatile organic compounds. Incorporating water-quality parameters in AS permits identification of perturbation of natural occurrence patterns by flushing of natural perchlorate salts from unsaturated zones by irrigation recharge as well as addition of perchlorate from industrial and agricultural sources. The data and model results indicate low concentrations (0.1-0.5 μg/L) of perchlorate occur under natural conditions in groundwater across a wide range of climates, beyond the arid to semiarid climates in which they mostly have been previously reported. The probability of detecting perchlorate at concentrations greater than 0.1 μg/L under natural conditions ranges from 50-70% in semiarid to arid regions of California and the Southwestern United States to 5-15% in the wettest regions sampled (the Northern California coast). The probability of concentrations above 1 μg/L under natural conditions is low (generally <3%).

Uncertainty plus prior equals rational bias: an intuitive Bayesian probability weighting function.

Science.gov (United States)

Fennell, John; Baddeley, Roland

2012-10-01

Empirical research has shown that when making choices based on probabilistic options, people behave as if they overestimate small probabilities, underestimate large probabilities, and treat positive and negative outcomes differently. These distortions have been modeled using a nonlinear probability weighting function, which is found in several nonexpected utility theories, including rank-dependent models and prospect theory; here, we propose a Bayesian approach to the probability weighting function and, with it, a psychological rationale. In the real world, uncertainty is ubiquitous and, accordingly, the optimal strategy is to combine probability statements with prior information using Bayes' rule. First, we show that any reasonable prior on probabilities leads to 2 of the observed effects; overweighting of low probabilities and underweighting of high probabilities. We then investigate 2 plausible kinds of priors: informative priors based on previous experience and uninformative priors of ignorance. Individually, these priors potentially lead to large problems of bias and inefficiency, respectively; however, when combined using Bayesian model comparison methods, both forms of prior can be applied adaptively, gaining the efficiency of empirical priors and the robustness of ignorance priors. We illustrate this for the simple case of generic good and bad options, using Internet blogs to estimate the relevant priors of inference. Given this combined ignorant/informative prior, the Bayesian probability weighting function is not only robust and efficient but also matches all of the major characteristics of the distortions found in empirical research. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Determination of the failure probability in the weld region of ap-600 vessel for transient condition

International Nuclear Information System (INIS)

Wahyono, I.P.

1997-01-01

Failure probability in the weld region of AP-600 vessel was determined for transient condition scenario. The type of transient is increase of the heat removal from primary cooling system due to sudden opening of safety valves or steam relief valves on the secondary cooling system or the steam generator. Temperature and pressure in the vessel was considered as the base of deterministic calculation of the stress intensity factor. Calculation of film coefficient of the convective heat transfers is a function of the transient time and water parameter. Pressure, material temperature, flaw depth and transient time are variables for the stress intensity factor. Failure probability consideration was done by using the above information in regard with the flaw and probability distributions of Octavia II and Marshall. Calculation of the failure probability by probability fracture mechanic simulation is applied on the weld region. Failure of the vessel is assumed as a failure of the weld material with one crack which stress intensity factor applied is higher than the critical stress intensity factor. VISA II code (Vessel Integrity Simulation Analysis II) was used for deterministic calculation and simulation. Failure probability of the material is 1.E-5 for Octavia II distribution and 4E-6 for marshall distribution for each transient event postulated. The failure occurred at the 1.7th menit of the initial transient under 12.53 ksi of the pressure

Entanglement probabilities of polymers: a white noise functional approach

International Nuclear Information System (INIS)

Bernido, Christopher C; Carpio-Bernido, M Victoria

2003-01-01

The entanglement probabilities for a highly flexible polymer to wind n times around a straight polymer are evaluated using white noise analysis. To introduce the white noise functional approach, the one-dimensional random walk problem is taken as an example. The polymer entanglement scenario, viewed as a random walk on a plane, is then treated and the entanglement probabilities are obtained for a magnetic flux confined along the straight polymer, and a case where an entangled polymer is subjected to the potential V = f-dot(s)θ. In the absence of the magnetic flux and the potential V, the entanglement probabilities reduce to a result obtained by Wiegel

INTERACTIVE VISUALIZATION OF PROBABILITY AND CUMULATIVE DENSITY FUNCTIONS

KAUST Repository

Potter, Kristin; Kirby, Robert Michael; Xiu, Dongbin; Johnson, Chris R.

2012-01-01

The probability density function (PDF), and its corresponding cumulative density function (CDF), provide direct statistical insight into the characterization of a random process or field. Typically displayed as a histogram, one can infer probabilities of the occurrence of particular events. When examining a field over some two-dimensional domain in which at each point a PDF of the function values is available, it is challenging to assess the global (stochastic) features present within the field. In this paper, we present a visualization system that allows the user to examine two-dimensional data sets in which PDF (or CDF) information is available at any position within the domain. The tool provides a contour display showing the normed difference between the PDFs and an ansatz PDF selected by the user and, furthermore, allows the user to interactively examine the PDF at any particular position. Canonical examples of the tool are provided to help guide the reader into the mapping of stochastic information to visual cues along with a description of the use of the tool for examining data generated from an uncertainty quantification exercise accomplished within the field of electrophysiology.

Uncertainty plus Prior Equals Rational Bias: An Intuitive Bayesian Probability Weighting Function

Science.gov (United States)

Fennell, John; Baddeley, Roland

2012-01-01

Empirical research has shown that when making choices based on probabilistic options, people behave as if they overestimate small probabilities, underestimate large probabilities, and treat positive and negative outcomes differently. These distortions have been modeled using a nonlinear probability weighting function, which is found in several…

Calculation of the Incremental Conditional Core Damage Probability on the Extension of Allowed Outage Time

International Nuclear Information System (INIS)

Kang, Dae Il; Han, Sang Hoon

2006-01-01

RG 1.177 requires that the conditional risk (incremental conditional core damage probability and incremental conditional large early release probability: ICCDP and ICLERP), given that a specific component is out of service (OOS), be quantified for a permanent change of the allowed outage time (AOT) of a safety system. An AOT is the length of time that a particular component or system is permitted to be OOS while the plant is operating. The ICCDP is defined as: ICCDP = [(conditional CDF with the subject equipment OOS)- (baseline CDF with nominal expected equipment unavailabilities)] [duration of the single AOT under consideration]. Any event enabling the component OOS can initiate the time clock for the limiting condition of operation for a nuclear power plant. Thus, the largest ICCDP among the ICCDPs estimated from any occurrence of the basic events for the component fault tree should be selected for determining whether the AOT can be extended or not. If the component is under a preventive maintenance, the conditional risk can be straightforwardly calculated without changing the CCF probability. The main concern is the estimations of the CCF probability because there are the possibilities of the failures of other similar components due to the same root causes. The quantifications of the risk, given that a subject equipment is in a failed state, are performed by setting the identified event of subject equipment to TRUE. The CCF probabilities are also changed according to the identified failure cause. In the previous studies, however, the ICCDP was quantified with the consideration of the possibility of a simultaneous occurrence of two CCF events. Based on the above, we derived the formulas of the CCF probabilities for the cases where a specific component is in a failed state and we presented sample calculation results of the ICCDP for the low pressure safety injection system (LPSIS) of Ulchin Unit 3

Using Dynamic Geometry Software for Teaching Conditional Probability with Area-Proportional Venn Diagrams

Science.gov (United States)

Radakovic, Nenad; McDougall, Douglas

2012-01-01

This classroom note illustrates how dynamic visualization can be used to teach conditional probability and Bayes' theorem. There are two features of the visualization that make it an ideal pedagogical tool in probability instruction. The first feature is the use of area-proportional Venn diagrams that, along with showing qualitative relationships,…

Modulation Based on Probability Density Functions

Science.gov (United States)

Williams, Glenn L.

2009-01-01

A proposed method of modulating a sinusoidal carrier signal to convey digital information involves the use of histograms representing probability density functions (PDFs) that characterize samples of the signal waveform. The method is based partly on the observation that when a waveform is sampled (whether by analog or digital means) over a time interval at least as long as one half cycle of the waveform, the samples can be sorted by frequency of occurrence, thereby constructing a histogram representing a PDF of the waveform during that time interval.

Class dependency of fuzzy relational database using relational calculus and conditional probability

Science.gov (United States)

Deni Akbar, Mohammad; Mizoguchi, Yoshihiro; Adiwijaya

2018-03-01

In this paper, we propose a design of fuzzy relational database to deal with a conditional probability relation using fuzzy relational calculus. In the previous, there are several researches about equivalence class in fuzzy database using similarity or approximate relation. It is an interesting topic to investigate the fuzzy dependency using equivalence classes. Our goal is to introduce a formulation of a fuzzy relational database model using the relational calculus on the category of fuzzy relations. We also introduce general formulas of the relational calculus for the notion of database operations such as ’projection’, ’selection’, ’injection’ and ’natural join’. Using the fuzzy relational calculus and conditional probabilities, we introduce notions of equivalence class, redundant, and dependency in the theory fuzzy relational database.

Numerical Loading of a Maxwellian Probability Distribution Function

International Nuclear Information System (INIS)

Lewandowski, J.L.V.

2003-01-01

A renormalization procedure for the numerical loading of a Maxwellian probability distribution function (PDF) is formulated. The procedure, which involves the solution of three coupled nonlinear equations, yields a numerically loaded PDF with improved properties for higher velocity moments. This method is particularly useful for low-noise particle-in-cell simulations with electron dynamics

Approximation of Measurement Results of “Emergency” Signal Reception Probability

Directory of Open Access Journals (Sweden)

Gajda Stanisław

2017-08-01

Full Text Available The intended aim of this article is to present approximation results of the exemplary measurements of EMERGENCY signal reception probability. The probability is under-stood as a distance function between the aircraft and a ground-based system under established conditions. The measurements were approximated using the properties of logistic functions. This probability, as a distance function, enables to determine the range of the EMERGENCY signal for a pre-set confidence level.

ERF/ERFC, Calculation of Error Function, Complementary Error Function, Probability Integrals

International Nuclear Information System (INIS)

Vogel, J.E.

1983-01-01

1 - Description of problem or function: ERF and ERFC are used to compute values of the error function and complementary error function for any real number. They may be used to compute other related functions such as the normal probability integrals. 4. Method of solution: The error function and complementary error function are approximated by rational functions. Three such rational approximations are used depending on whether - x .GE.4.0. In the first region the error function is computed directly and the complementary error function is computed via the identity erfc(x)=1.0-erf(x). In the other two regions the complementary error function is computed directly and the error function is computed from the identity erf(x)=1.0-erfc(x). The error function and complementary error function are real-valued functions of any real argument. The range of the error function is (-1,1). The range of the complementary error function is (0,2). 5. Restrictions on the complexity of the problem: The user is cautioned against using ERF to compute the complementary error function by using the identity erfc(x)=1.0-erf(x). This subtraction may cause partial or total loss of significance for certain values of x

Blue functions: probability and current density propagators in non-relativistic quantum mechanics

International Nuclear Information System (INIS)

Withers, L P Jr

2011-01-01

Like a Green function to propagate a particle's wavefunction in time, a Blue function is introduced to propagate the particle's probability and current density. Accordingly, the complete Blue function has four components. They are constructed from path integrals involving a quantity like the action that we call the motion. The Blue function acts on the displaced probability density as the kernel of an integral operator. As a result, we find that the Wigner density occurs as an expression for physical propagation. We also show that, in quantum mechanics, the displaced current density is conserved bilocally (in two places at one time), as expressed by a generalized continuity equation. (paper)

Secondary School Students' Reasoning about Conditional Probability, Samples, and Sampling Procedures

Science.gov (United States)

Prodromou, Theodosia

2016-01-01

In the Australian mathematics curriculum, Year 12 students (aged 16-17) are asked to solve conditional probability problems that involve the representation of the problem situation with two-way tables or three-dimensional diagrams and consider sampling procedures that result in different correct answers. In a small exploratory study, we…

Conditional probability of intense rainfall producing high ground concentrations from radioactive plumes

International Nuclear Information System (INIS)

Wayland, J.R.

1977-03-01

The overlap of the expanding plume of radioactive material from a hypothetical nuclear accident with rainstorms over dense population areas is considered. The conditional probability of the occurrence of hot spots from intense cellular rainfall is presented

Fitting the Probability Distribution Functions to Model Particulate Matter Concentrations

International Nuclear Information System (INIS)

El-Shanshoury, Gh.I.

2017-01-01

The main objective of this study is to identify the best probability distribution and the plotting position formula for modeling the concentrations of Total Suspended Particles (TSP) as well as the Particulate Matter with an aerodynamic diameter<10 μm (PM 10 ). The best distribution provides the estimated probabilities that exceed the threshold limit given by the Egyptian Air Quality Limit value (EAQLV) as well the number of exceedance days is estimated. The standard limits of the EAQLV for TSP and PM 10 concentrations are 24-h average of 230 μg/m 3 and 70 μg/m 3 , respectively. Five frequency distribution functions with seven formula of plotting positions (empirical cumulative distribution functions) are compared to fit the average of daily TSP and PM 10 concentrations in year 2014 for Ain Sokhna city. The Quantile-Quantile plot (Q-Q plot) is used as a method for assessing how closely a data set fits a particular distribution. A proper probability distribution that represents the TSP and PM 10 has been chosen based on the statistical performance indicator values. The results show that Hosking and Wallis plotting position combined with Frechet distribution gave the highest fit for TSP and PM 10 concentrations. Burr distribution with the same plotting position follows Frechet distribution. The exceedance probability and days over the EAQLV are predicted using Frechet distribution. In 2014, the exceedance probability and days for TSP concentrations are 0.052 and 19 days, respectively. Furthermore, the PM 10 concentration is found to exceed the threshold limit by 174 days

The effect of conditional probability of chord progression on brain response: an MEG study.

Directory of Open Access Journals (Sweden)

Seung-Goo Kim

Full Text Available BACKGROUND: Recent electrophysiological and neuroimaging studies have explored how and where musical syntax in Western music is processed in the human brain. An inappropriate chord progression elicits an event-related potential (ERP component called an early right anterior negativity (ERAN or simply an early anterior negativity (EAN in an early stage of processing the musical syntax. Though the possible underlying mechanism of the EAN is assumed to be probabilistic learning, the effect of the probability of chord progressions on the EAN response has not been previously explored explicitly. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, the empirical conditional probabilities in a Western music corpus were employed as an approximation of the frequencies in previous exposure of participants. Three types of chord progression were presented to musicians and non-musicians in order to examine the correlation between the probability of chord progression and the neuromagnetic response using magnetoencephalography (MEG. Chord progressions were found to elicit early responses in a negatively correlating fashion with the conditional probability. Observed EANm (as a magnetic counterpart of the EAN component responses were consistent with the previously reported EAN responses in terms of latency and location. The effect of conditional probability interacted with the effect of musical training. In addition, the neural response also correlated with the behavioral measures in the non-musicians. CONCLUSIONS/SIGNIFICANCE: Our study is the first to reveal the correlation between the probability of chord progression and the corresponding neuromagnetic response. The current results suggest that the physiological response is a reflection of the probabilistic representations of the musical syntax. Moreover, the results indicate that the probabilistic representation is related to the musical training as well as the sensitivity of an individual.

Impact of proof test interval and coverage on probability of failure of safety instrumented function

International Nuclear Information System (INIS)

Jin, Jianghong; Pang, Lei; Hu, Bin; Wang, Xiaodong

2016-01-01

Highlights: • Introduction of proof test coverage makes the calculation of the probability of failure for SIF more accurate. • The probability of failure undetected by proof test is independently defined as P TIF and calculated. • P TIF is quantified using reliability block diagram and simple formula of PFD avg . • Improving proof test coverage and adopting reasonable test period can reduce the probability of failure for SIF. - Abstract: Imperfection of proof test can result in the safety function failure of safety instrumented system (SIS) at any time in its life period. IEC61508 and other references ignored or only elementarily analyzed the imperfection of proof test. In order to further study the impact of the imperfection of proof test on the probability of failure for safety instrumented function (SIF), the necessity of proof test and influence of its imperfection on system performance was first analyzed theoretically. The probability of failure for safety instrumented function resulted from the imperfection of proof test was defined as probability of test independent failures (P TIF ), and P TIF was separately calculated by introducing proof test coverage and adopting reliability block diagram, with reference to the simplified calculation formula of average probability of failure on demand (PFD avg ). Research results show that: the shorter proof test period and the higher proof test coverage indicate the smaller probability of failure for safety instrumented function. The probability of failure for safety instrumented function which is calculated by introducing proof test coverage will be more accurate.

Quantum probability measures and tomographic probability densities

NARCIS (Netherlands)

Amosov, GG; Man'ko, [No Value

2004-01-01

Using a simple relation of the Dirac delta-function to generalized the theta-function, the relationship between the tomographic probability approach and the quantum probability measure approach with the description of quantum states is discussed. The quantum state tomogram expressed in terms of the

Diagnostic probability function for acute coronary heart disease garnered from experts' tacit knowledge.

Science.gov (United States)

Steurer, Johann; Held, Ulrike; Miettinen, Olli S

2013-11-01

Knowing about a diagnostic probability requires general knowledge about the way in which the probability depends on the diagnostic indicators involved in the specification of the case at issue. Diagnostic probability functions (DPFs) are generally unavailable at present. Our objective was to illustrate how diagnostic experts' case-specific tacit knowledge about diagnostic probabilities could be garnered in the form of DPFs. Focusing on diagnosis of acute coronary heart disease (ACHD), we presented doctors with extensive experience in hospitals' emergency departments a set of hypothetical cases specified in terms of an inclusive set of diagnostic indicators. We translated the medians of these experts' case-specific probabilities into a logistic DPF for ACHD. The principal result was the experts' typical diagnostic probability for ACHD as a joint function of the set of diagnostic indicators. A related result of note was the finding that the experts' probabilities in any given case had a surprising degree of variability. Garnering diagnostic experts' case-specific tacit knowledge about diagnostic probabilities in the form of DPFs is feasible to accomplish. Thus, once the methodology of this type of work has been "perfected," practice-guiding diagnostic expert systems can be developed. Copyright © 2013 Elsevier Inc. All rights reserved.

Quantum-correlation breaking channels, quantum conditional probability and Perron-Frobenius theory

Science.gov (United States)

Chruściński, Dariusz

2013-03-01

Using the quantum analog of conditional probability and classical Bayes theorem we discuss some aspects of particular entanglement breaking channels: quantum-classical and classical-classical channels. Applying the quantum analog of Perron-Frobenius theorem we generalize the recent result of Korbicz et al. (2012) [8] on full and spectrum broadcasting from quantum-classical channels to arbitrary quantum channels.

Quantum-correlation breaking channels, quantum conditional probability and Perron–Frobenius theory

International Nuclear Information System (INIS)

Chruściński, Dariusz

2013-01-01

Using the quantum analog of conditional probability and classical Bayes theorem we discuss some aspects of particular entanglement breaking channels: quantum–classical and classical–classical channels. Applying the quantum analog of Perron–Frobenius theorem we generalize the recent result of Korbicz et al. (2012) [8] on full and spectrum broadcasting from quantum–classical channels to arbitrary quantum channels.

Modelling the Probability Density Function of IPTV Traffic Packet Delay Variation

Directory of Open Access Journals (Sweden)

Michal Halas

2012-01-01

Full Text Available This article deals with modelling the Probability density function of IPTV traffic packet delay variation. The use of this modelling is in an efficient de-jitter buffer estimation. When an IP packet travels across a network, it experiences delay and its variation. This variation is caused by routing, queueing systems and other influences like the processing delay of the network nodes. When we try to separate these at least three types of delay variation, we need a way to measure these types separately. This work is aimed to the delay variation caused by queueing systems which has the main implications to the form of the Probability density function.

Relationship between the Wigner function and the probability density function in quantum phase space representation

International Nuclear Information System (INIS)

Li Qianshu; Lue Liqiang; Wei Gongmin

2004-01-01

This paper discusses the relationship between the Wigner function, along with other related quasiprobability distribution functions, and the probability density distribution function constructed from the wave function of the Schroedinger equation in quantum phase space, as formulated by Torres-Vega and Frederick (TF). At the same time, a general approach in solving the wave function of the Schroedinger equation of TF quantum phase space theory is proposed. The relationship of the wave functions between the TF quantum phase space representation and the coordinate or momentum representation is thus revealed

Eliciting conditional and unconditional rank correlations from conditional probabilities

International Nuclear Information System (INIS)

Morales, O.; Kurowicka, D.; Roelen, A.

2008-01-01

Causes of uncertainties may be interrelated and may introduce dependencies. Ignoring these dependencies may lead to large errors. A number of graphical models in probability theory such as dependence trees, vines and (continuous) Bayesian belief nets [Cooke RM. Markov and entropy properties of tree and vine-dependent variables. In: Proceedings of the ASA section on Bayesian statistical science, 1997; Kurowicka D, Cooke RM. Distribution-free continuous Bayesian belief nets. In: Proceedings of mathematical methods in reliability conference, 2004; Bedford TJ, Cooke RM. Vines-a new graphical model for dependent random variables. Ann Stat 2002; 30(4):1031-68; Kurowicka D, Cooke RM. Uncertainty analysis with high dimensional dependence modelling. New York: Wiley; 2006; Hanea AM, et al. Hybrid methods for quantifying and analyzing Bayesian belief nets. In: Proceedings of the 2005 ENBIS5 conference, 2005; Shachter RD, Kenley CR. Gaussian influence diagrams. Manage Sci 1998; 35(5) .] have been developed to capture dependencies between random variables. The input for these models are various marginal distributions and dependence information, usually in the form of conditional rank correlations. Often expert elicitation is required. This paper focuses on dependence representation, and dependence elicitation. The techniques presented are illustrated with an application from aviation safety

Conditional Independence in Applied Probability.

Science.gov (United States)

Pfeiffer, Paul E.

This material assumes the user has the background provided by a good undergraduate course in applied probability. It is felt that introductory courses in calculus, linear algebra, and perhaps some differential equations should provide the requisite experience and proficiency with mathematical concepts, notation, and argument. The document is…

Probability laws related to the Jacobi theta and Riemann zeta function and Brownian excursions

OpenAIRE

Biane, P.; Pitman, J.; Yor, M.

1999-01-01

This paper reviews known results which connect Riemann's integral representations of his zeta function, involving Jacobi's theta function and its derivatives, to some particular probability laws governing sums of independent exponential variables. These laws are related to one-dimensional Brownian motion and to higher dimensional Bessel processes. We present some characterizations of these probability laws, and some approximations of Riemann's zeta function which are related to these laws.

On the Hitting Probability of Max-Stable Processes

OpenAIRE

Hofmann, Martin

2012-01-01

The probability that a max-stable process {\\eta} in C[0, 1] with identical marginal distribution function F hits x \\in R with 0 < F (x) < 1 is the hitting probability of x. We show that the hitting probability is always positive, unless the components of {\\eta} are completely dependent. Moreover, we consider the event that the paths of standard MSP hit some x \\in R twice and we give a sufficient condition for a positive probability of this event.

Decision making with consonant belief functions: Discrepancy resulting with the probability transformation method used

Directory of Open Access Journals (Sweden)

Cinicioglu Esma Nur

2014-01-01

Full Text Available Dempster−Shafer belief function theory can address a wider class of uncertainty than the standard probability theory does, and this fact appeals the researchers in operations research society for potential application areas. However, the lack of a decision theory of belief functions gives rise to the need to use the probability transformation methods for decision making. For representation of statistical evidence, the class of consonant belief functions is used which is not closed under Dempster’s rule of combination but is closed under Walley’s rule of combination. In this research, it is shown that the outcomes obtained using both Dempster’s and Walley’s rules do result in different probability distributions when pignistic transformation is used. However, when plausibility transformation is used, they do result in the same probability distribution. This result shows that the choice of the combination rule and probability transformation method may have a significant effect on decision making since it may change the choice of the decision alternative selected. This result is illustrated via an example of missile type identification.

Continuation of probability density functions using a generalized Lyapunov approach

NARCIS (Netherlands)

Baars, S.; Viebahn, J. P.; Mulder, T. E.; Kuehn, C.; Wubs, F. W.; Dijkstra, H. A.

2017-01-01

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining probability density functions of systems of stochastic partial

Adaptive Neural Control of Nonaffine Nonlinear Systems without Differential Condition for Nonaffine Function

Directory of Open Access Journals (Sweden)

Chaojiao Sun

2016-01-01

Full Text Available An adaptive neural control scheme is proposed for nonaffine nonlinear system without using the implicit function theorem or mean value theorem. The differential conditions on nonaffine nonlinear functions are removed. The control-gain function is modeled with the nonaffine function probably being indifferentiable. Furthermore, only a semibounded condition for nonaffine nonlinear function is required in the proposed method, and the basic idea of invariant set theory is then constructively introduced to cope with the difficulty in the control design for nonaffine nonlinear systems. It is rigorously proved that all the closed-loop signals are bounded and the tracking error converges to a small residual set asymptotically. Finally, simulation examples are provided to demonstrate the effectiveness of the designed method.

Multiregion, multigroup collision probability method with white boundary condition for light water reactor thermalization calculations

International Nuclear Information System (INIS)

Ozgener, B.; Ozgener, H.A.

2005-01-01

A multiregion, multigroup collision probability method with white boundary condition is developed for thermalization calculations of light water moderated reactors. Hydrogen scatterings are treated by Nelkin's kernel while scatterings from other nuclei are assumed to obey the free-gas scattering kernel. The isotropic return (white) boundary condition is applied directly by using the appropriate collision probabilities. Comparisons with alternate numerical methods show the validity of the present formulation. Comparisons with some experimental results indicate that the present formulation is capable of calculating disadvantage factors which are closer to the experimental results than alternative methods

Power probability density function control and performance assessment of a nuclear research reactor

International Nuclear Information System (INIS)

Abharian, Amir Esmaeili; Fadaei, Amir Hosein

2014-01-01

Highlights: • In this paper, the performance assessment of static PDF control system is discussed. • The reactor PDF model is set up based on the B-spline functions. • Acquaints of Nu, and Th-h. equations solve concurrently by reformed Hansen’s method. • A principle of performance assessment is put forward for the PDF of the NR control. - Abstract: One of the main issues in controlling a system is to keep track of the conditions of the system function. The performance condition of the system should be inspected continuously, to keep the system in reliable working condition. In this study, the nuclear reactor is considered as a complicated system and a principle of performance assessment is used for analyzing the performance of the power probability density function (PDF) of the nuclear research reactor control. First, the model of the power PDF is set up, then the controller is designed to make the power PDF for tracing the given shape, that make the reactor to be a closed-loop system. The operating data of the closed-loop reactor are used to assess the control performance with the performance assessment criteria. The modeling, controller design and the performance assessment of the power PDF are all applied to the control of Tehran Research Reactor (TRR) power in a nuclear process. In this paper, the performance assessment of the static PDF control system is discussed, the efficacy and efficiency of the proposed method are investigated, and finally its reliability is proven

The distribution function of a probability measure on a space with a fractal structure

Energy Technology Data Exchange (ETDEWEB)

Sanchez-Granero, M.A.; Galvez-Rodriguez, J.F.

2017-07-01

In this work we show how to define a probability measure with the help of a fractal structure. One of the keys of this approach is to use the completion of the fractal structure. Then we use the theory of a cumulative distribution function on a Polish ultrametric space and describe it in this context. Finally, with the help of fractal structures, we prove that a function satisfying the properties of a cumulative distribution function on a Polish ultrametric space is a cumulative distribution function with respect to some probability measure on the space. (Author)

Multiple-event probability in general-relativistic quantum mechanics

International Nuclear Information System (INIS)

Hellmann, Frank; Mondragon, Mauricio; Perez, Alejandro; Rovelli, Carlo

2007-01-01

We discuss the definition of quantum probability in the context of 'timeless' general-relativistic quantum mechanics. In particular, we study the probability of sequences of events, or multievent probability. In conventional quantum mechanics this can be obtained by means of the 'wave function collapse' algorithm. We first point out certain difficulties of some natural definitions of multievent probability, including the conditional probability widely considered in the literature. We then observe that multievent probability can be reduced to single-event probability, by taking into account the quantum nature of the measuring apparatus. In fact, by exploiting the von-Neumann freedom of moving the quantum/classical boundary, one can always trade a sequence of noncommuting quantum measurements at different times, with an ensemble of simultaneous commuting measurements on the joint system+apparatus system. This observation permits a formulation of quantum theory based only on single-event probability, where the results of the wave function collapse algorithm can nevertheless be recovered. The discussion also bears on the nature of the quantum collapse

Sharp Bounds by Probability-Generating Functions and Variable Drift

DEFF Research Database (Denmark)

Doerr, Benjamin; Fouz, Mahmoud; Witt, Carsten

2011-01-01

We introduce to the runtime analysis of evolutionary algorithms two powerful techniques: probability-generating functions and variable drift analysis. They are shown to provide a clean framework for proving sharp upper and lower bounds. As an application, we improve the results by Doerr et al....... (GECCO 2010) in several respects. First, the upper bound on the expected running time of the most successful quasirandom evolutionary algorithm for the OneMax function is improved from 1.28nln n to 0.982nlnn, which breaks the barrier of nln n posed by coupon-collector processes. Compared to the classical...

Elements of a function analytic approach to probability.

Energy Technology Data Exchange (ETDEWEB)

Ghanem, Roger Georges (University of Southern California, Los Angeles, CA); Red-Horse, John Robert

2008-02-01

We first provide a detailed motivation for using probability theory as a mathematical context in which to analyze engineering and scientific systems that possess uncertainties. We then present introductory notes on the function analytic approach to probabilistic analysis, emphasizing the connections to various classical deterministic mathematical analysis elements. Lastly, we describe how to use the approach as a means to augment deterministic analysis methods in a particular Hilbert space context, and thus enable a rigorous framework for commingling deterministic and probabilistic analysis tools in an application setting.

Heightened fire probability in Indonesia in non-drought conditions: the effect of increasing temperatures

Science.gov (United States)

Fernandes, Kátia; Verchot, Louis; Baethgen, Walter; Gutierrez-Velez, Victor; Pinedo-Vasquez, Miguel; Martius, Christopher

2017-05-01

In Indonesia, drought driven fires occur typically during the warm phase of the El Niño Southern Oscillation. This was the case of the events of 1997 and 2015 that resulted in months-long hazardous atmospheric pollution levels in Equatorial Asia and record greenhouse gas emissions. Nonetheless, anomalously active fire seasons have also been observed in non-drought years. In this work, we investigated the impact of temperature on fires and found that when the July-October (JASO) period is anomalously dry, the sensitivity of fires to temperature is modest. In contrast, under normal-to-wet conditions, fire probability increases sharply when JASO is anomalously warm. This describes a regime in which an active fire season is not limited to drought years. Greater susceptibility to fires in response to a warmer environment finds support in the high evapotranspiration rates observed in normal-to-wet and warm conditions in Indonesia. We also find that fire probability in wet JASOs would be considerably less sensitive to temperature were not for the added effect of recent positive trends. Near-term regional climate projections reveal that, despite negligible changes in precipitation, a continuing warming trend will heighten fire probability over the next few decades especially in non-drought years. Mild fire seasons currently observed in association with wet conditions and cool temperatures will become rare events in Indonesia.

Assumed Probability Density Functions for Shallow and Deep Convection

OpenAIRE

Steven K Krueger; Peter A Bogenschutz; Marat Khairoutdinov

2010-01-01

The assumed joint probability density function (PDF) between vertical velocity and conserved temperature and total water scalars has been suggested to be a relatively computationally inexpensive and unified subgrid-scale (SGS) parameterization for boundary layer clouds and turbulent moments. This paper analyzes the performance of five families of PDFs using large-eddy simulations of deep convection, shallow convection, and a transition from stratocumulus to trade wind cumulus. Three of the PD...

Hawkes-diffusion process and the conditional probability of defaults in the Eurozone

Science.gov (United States)

Kim, Jungmu; Park, Yuen Jung; Ryu, Doojin

2016-05-01

This study examines market information embedded in the European sovereign CDS (credit default swap) market by analyzing the sovereign CDSs of 13 Eurozone countries from January 1, 2008, to February 29, 2012, which includes the recent Eurozone debt crisis period. We design the conditional probability of defaults for the CDS prices based on the Hawkes-diffusion process and obtain the theoretical prices of CDS indexes. To estimate the model parameters, we calibrate the model prices to empirical prices obtained from individual sovereign CDS term structure data. The estimated parameters clearly explain both cross-sectional and time-series data. Our empirical results show that the probability of a huge loss event sharply increased during the Eurozone debt crisis, indicating a contagion effect. Even countries with strong and stable economies, such as Germany and France, suffered from the contagion effect. We also find that the probability of small events is sensitive to the state of the economy, spiking several times due to the global financial crisis and the Greek government debt crisis.

Probability density function modeling of scalar mixing from concentrated sources in turbulent channel flow

Science.gov (United States)

Bakosi, J.; Franzese, P.; Boybeyi, Z.

2007-11-01

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth and Pope [Phys. Fluids 29, 387 (1986)] with Durbin's [J. Fluid Mech. 249, 465 (1993)] method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous transport with a nonlocal representation of the near-wall Reynolds stress anisotropy. The presence of walls is incorporated through the imposition of no-slip and impermeability conditions on particles without the use of damping or wall-functions. Information on the turbulent time scale is supplied by the gamma-distribution model of van Slooten et al. [Phys. Fluids 10, 246 (1998)]. Two different micromixing models are compared that incorporate the effect of small scale mixing on the transported scalar: the widely used interaction by exchange with the mean and the interaction by exchange with the conditional mean model. Single-point velocity and concentration statistics are compared to direct numerical simulation and experimental data at Reτ=1080 based on the friction velocity and the channel half width. The joint model accurately reproduces a wide variety of conditional and unconditional statistics in both physical and composition space.

Exact probability distribution function for the volatility of cumulative production

Science.gov (United States)

Zadourian, Rubina; Klümper, Andreas

2018-04-01

In this paper we study the volatility and its probability distribution function for the cumulative production based on the experience curve hypothesis. This work presents a generalization of the study of volatility in Lafond et al. (2017), which addressed the effects of normally distributed noise in the production process. Due to its wide applicability in industrial and technological activities we present here the mathematical foundation for an arbitrary distribution function of the process, which we expect will pave the future research on forecasting of the production process.

A Hierarchy of Compatibility and Comeasurability Levels in Quantum Logics with Unique Conditional Probabilities

International Nuclear Information System (INIS)

Niestegge, Gerd

2010-01-01

In the quantum mechanical Hilbert space formalism, the probabilistic interpretation is a later ad-hoc add-on, more or less enforced by the experimental evidence, but not motivated by the mathematical model itself. A model involving a clear probabilistic interpretation from the very beginning is provided by the quantum logics with unique conditional probabilities. It includes the projection lattices in von Neumann algebras and here probability conditionalization becomes identical with the state transition of the Lueders-von Neumann measurement process. This motivates the definition of a hierarchy of five compatibility and comeasurability levels in the abstract setting of the quantum logics with unique conditional probabilities. Their meanings are: the absence of quantum interference or influence, the existence of a joint distribution, simultaneous measurability, and the independence of the final state after two successive measurements from the sequential order of these two measurements. A further level means that two elements of the quantum logic (events) belong to the same Boolean subalgebra. In the general case, the five compatibility and comeasurability levels appear to differ, but they all coincide in the common Hilbert space formalism of quantum mechanics, in von Neumann algebras, and in some other cases. (general)

Compact baby universe model in ten dimension and probability function of quantum gravity

International Nuclear Information System (INIS)

Yan Jun; Hu Shike

1991-01-01

The quantum probability functions are calculated for ten-dimensional compact baby universe model. The authors find that the probability for the Yang-Mills baby universe to undergo a spontaneous compactification down to a four-dimensional spacetime is greater than that to remain in the original homogeneous multidimensional state. Some questions about large-wormhole catastrophe are also discussed

Sufficient Condition for Monotonicity in Constructing the Distribution Function With Bernoulli Scheme

Directory of Open Access Journals (Sweden)

Vedenyapin Aleksandr Dmitrievich

2015-11-01

by the function r(x, kmin: Pnk=Сnk[P(r(x, kmin]k[1-P(r(x, kmin]n-k. We defined the probability that the total index change will be in the section [x, nS] as the sum of the probabilities of incompatible events, for which the number of successes satisfies to entered inequality. Then obviously we defined the probability that the total index changing will be in the interval [nI, x. Then the function F(x was introduced, defined on the whole line, which is identical to the amount (probability that the total index changing will be in the interval in the interval (nI, nS], and is identical to zero and one in the additions. Some properties of the distribution function F(x are satisfied automatically. A sufficient condition for the monotonicity is presented in the form of Theorem 2.

Random phenomena fundamentals of probability and statistics for engineers

CERN Document Server

Ogunnaike, Babatunde A

2009-01-01

PreludeApproach PhilosophyFour Basic PrinciplesI FoundationsTwo Motivating ExamplesYield Improvement in a Chemical ProcessQuality Assurance in a Glass Sheet Manufacturing ProcessOutline of a Systematic ApproachRandom Phenomena, Variability, and UncertaintyTwo Extreme Idealizations of Natural PhenomenaRandom Mass PhenomenaIntroducing ProbabilityThe Probabilistic FrameworkII ProbabilityFundamentals of Probability TheoryBuilding BlocksOperationsProbabilityConditional ProbabilityIndependenceRandom Variables and DistributionsDistributionsMathematical ExpectationCharacterizing DistributionsSpecial Derived Probability FunctionsMultidimensional Random VariablesDistributions of Several Random VariablesDistributional Characteristics of Jointly Distributed Random VariablesRandom Variable TransformationsSingle Variable TransformationsBivariate TransformationsGeneral Multivariate TransformationsApplication Case Studies I: ProbabilityMendel and HeredityWorld War II Warship Tactical Response Under AttackIII DistributionsIde...

Probability an introduction

CERN Document Server

Goldberg, Samuel

1960-01-01

Excellent basic text covers set theory, probability theory for finite sample spaces, binomial theorem, probability distributions, means, standard deviations, probability function of binomial distribution, more. Includes 360 problems with answers for half.

Theoretical derivation of wind power probability distribution function and applications

International Nuclear Information System (INIS)

Altunkaynak, Abdüsselam; Erdik, Tarkan; Dabanlı, İsmail; Şen, Zekai

2012-01-01

Highlights: ► Derivation of wind power stochastic characteristics are standard deviation and the dimensionless skewness. ► The perturbation is expressions for the wind power statistics from Weibull probability distribution function (PDF). ► Comparisons with the corresponding characteristics of wind speed PDF abides by the Weibull PDF. ► The wind power abides with the Weibull-PDF. -- Abstract: The instantaneous wind power contained in the air current is directly proportional with the cube of the wind speed. In practice, there is a record of wind speeds in the form of a time series. It is, therefore, necessary to develop a formulation that takes into consideration the statistical parameters of such a time series. The purpose of this paper is to derive the general wind power formulation in terms of the statistical parameters by using the perturbation theory, which leads to a general formulation of the wind power expectation and other statistical parameter expressions such as the standard deviation and the coefficient of variation. The formulation is very general and can be applied specifically for any wind speed probability distribution function. Its application to two-parameter Weibull probability distribution of wind speeds is presented in full detail. It is concluded that provided wind speed is distributed according to a Weibull distribution, the wind power could be derived based on wind speed data. It is possible to determine wind power at any desired risk level, however, in practical studies most often 5% or 10% risk levels are preferred and the necessary simple procedure is presented for this purpose in this paper.

A Derivation of Probabilities of Correct and Wrongful Conviction in a Criminal Trial

DEFF Research Database (Denmark)

Lando, Henrik

2006-01-01

probabilities are the probability of observing (any given) evidence against individual i given that individual j committed the crime (for any j including j equal to i). The variables are derived from the conditional probabilities as a function of the standard of the proof using simple Bayesian updating....

Estimation of functional failure probability of passive systems based on adaptive importance sampling method

International Nuclear Information System (INIS)

Wang Baosheng; Wang Dongqing; Zhang Jianmin; Jiang Jing

2012-01-01

In order to estimate the functional failure probability of passive systems, an innovative adaptive importance sampling methodology is presented. In the proposed methodology, information of variables is extracted with some pre-sampling of points in the failure region. An important sampling density is then constructed from the sample distribution in the failure region. Taking the AP1000 passive residual heat removal system as an example, the uncertainties related to the model of a passive system and the numerical values of its input parameters are considered in this paper. And then the probability of functional failure is estimated with the combination of the response surface method and adaptive importance sampling method. The numerical results demonstrate the high computed efficiency and excellent computed accuracy of the methodology compared with traditional probability analysis methods. (authors)

Explaining regional disparities in traffic mortality by decomposing conditional probabilities.

Science.gov (United States)

Goldstein, Gregory P; Clark, David E; Travis, Lori L; Haskins, Amy E

2011-04-01

In the USA, the mortality rate from traffic injury is higher in rural and in southern regions, for reasons that are not well understood. For 1754 (56%) of the 3142 US counties, we obtained data allowing for separation of the deaths/population rate into deaths/injury, injuries/crash, crashes/exposure and exposure/population, with exposure measured as vehicle miles travelled. A 'decomposition method' proposed by Li and Baker was extended to study how the contributions of these components were affected by three measures of rural location, as well as southern location. The method of Li and Baker extended without difficulty to include non-binary effects and multiple exposures. Deaths/injury was by far the most important determinant in the county-to-county variation in deaths/population, and accounted for the greatest portion of the rural/urban disparity. After controlling for the rural effect, injuries/crash accounted for most of the southern/northern disparity. The increased mortality rate from traffic injury in rural areas can be attributed to the increased probability of death given that a person has been injured, possibly due to challenges faced by emergency medical response systems. In southern areas, there is an increased probability of injury given that a person has crashed, possibly due to differences in vehicle, road, or driving conditions.

Linear positivity and virtual probability

International Nuclear Information System (INIS)

Hartle, James B.

2004-01-01

We investigate the quantum theory of closed systems based on the linear positivity decoherence condition of Goldstein and Page. The objective of any quantum theory of a closed system, most generally the universe, is the prediction of probabilities for the individual members of sets of alternative coarse-grained histories of the system. Quantum interference between members of a set of alternative histories is an obstacle to assigning probabilities that are consistent with the rules of probability theory. A quantum theory of closed systems therefore requires two elements: (1) a condition specifying which sets of histories may be assigned probabilities and (2) a rule for those probabilities. The linear positivity condition of Goldstein and Page is the weakest of the general conditions proposed so far. Its general properties relating to exact probability sum rules, time neutrality, and conservation laws are explored. Its inconsistency with the usual notion of independent subsystems in quantum mechanics is reviewed. Its relation to the stronger condition of medium decoherence necessary for classicality is discussed. The linear positivity of histories in a number of simple model systems is investigated with the aim of exhibiting linearly positive sets of histories that are not decoherent. The utility of extending the notion of probability to include values outside the range of 0-1 is described. Alternatives with such virtual probabilities cannot be measured or recorded, but can be used in the intermediate steps of calculations of real probabilities. Extended probabilities give a simple and general way of formulating quantum theory. The various decoherence conditions are compared in terms of their utility for characterizing classicality and the role they might play in further generalizations of quantum mechanics

Probability density of wave function of excited photoelectron: understanding XANES features

Czech Academy of Sciences Publication Activity Database

Šipr, Ondřej

2001-01-01

Roč. 8, - (2001), s. 232-234 ISSN 0909-0495 R&D Projects: GA ČR GA202/99/0404 Institutional research plan: CEZ:A02/98:Z1-010-914 Keywords : XANES * PED - probability density of wave function Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.519, year: 2001

Bounds for the probability distribution function of the linear ACD process

OpenAIRE

Fernandes, Marcelo

2003-01-01

Rio de Janeiro This paper derives both lower and upper bounds for the probability distribution function of stationary ACD(p, q) processes. For the purpose of illustration, I specialize the results to the main parent distributions in duration analysis. Simulations show that the lower bound is much tighter than the upper bound.

Probability distribution for the Gaussian curvature of the zero level surface of a random function

Science.gov (United States)

Hannay, J. H.

2018-04-01

A rather natural construction for a smooth random surface in space is the level surface of value zero, or ‘nodal’ surface f(x,y,z)  =  0, of a (real) random function f; the interface between positive and negative regions of the function. A physically significant local attribute at a point of a curved surface is its Gaussian curvature (the product of its principal curvatures) because, when integrated over the surface it gives the Euler characteristic. Here the probability distribution for the Gaussian curvature at a random point on the nodal surface f  =  0 is calculated for a statistically homogeneous (‘stationary’) and isotropic zero mean Gaussian random function f. Capitalizing on the isotropy, a ‘fixer’ device for axes supplies the probability distribution directly as a multiple integral. Its evaluation yields an explicit algebraic function with a simple average. Indeed, this average Gaussian curvature has long been known. For a non-zero level surface instead of the nodal one, the probability distribution is not fully tractable, but is supplied as an integral expression.

Quantum Probabilities as Behavioral Probabilities

Directory of Open Access Journals (Sweden)

Vyacheslav I. Yukalov

2017-03-01

Full Text Available We demonstrate that behavioral probabilities of human decision makers share many common features with quantum probabilities. This does not imply that humans are some quantum objects, but just shows that the mathematics of quantum theory is applicable to the description of human decision making. The applicability of quantum rules for describing decision making is connected with the nontrivial process of making decisions in the case of composite prospects under uncertainty. Such a process involves deliberations of a decision maker when making a choice. In addition to the evaluation of the utilities of considered prospects, real decision makers also appreciate their respective attractiveness. Therefore, human choice is not based solely on the utility of prospects, but includes the necessity of resolving the utility-attraction duality. In order to justify that human consciousness really functions similarly to the rules of quantum theory, we develop an approach defining human behavioral probabilities as the probabilities determined by quantum rules. We show that quantum behavioral probabilities of humans do not merely explain qualitatively how human decisions are made, but they predict quantitative values of the behavioral probabilities. Analyzing a large set of empirical data, we find good quantitative agreement between theoretical predictions and observed experimental data.

Dynamic Graphics in Excel for Teaching Statistics: Understanding the Probability Density Function

Science.gov (United States)

Coll-Serrano, Vicente; Blasco-Blasco, Olga; Alvarez-Jareno, Jose A.

2011-01-01

In this article, we show a dynamic graphic in Excel that is used to introduce an important concept in our subject, Statistics I: the probability density function. This interactive graphic seeks to facilitate conceptual understanding of the main aspects analysed by the learners.

Probability for statisticians

CERN Document Server

Shorack, Galen R

2017-01-01

This 2nd edition textbook offers a rigorous introduction to measure theoretic probability with particular attention to topics of interest to mathematical statisticians—a textbook for courses in probability for students in mathematical statistics. It is recommended to anyone interested in the probability underlying modern statistics, providing a solid grounding in the probabilistic tools and techniques necessary to do theoretical research in statistics. For the teaching of probability theory to post graduate statistics students, this is one of the most attractive books available. Of particular interest is a presentation of the major central limit theorems via Stein's method either prior to or alternative to a characteristic function presentation. Additionally, there is considerable emphasis placed on the quantile function as well as the distribution function. The bootstrap and trimming are both presented. Martingale coverage includes coverage of censored data martingales. The text includes measure theoretic...

The non-Gaussian joint probability density function of slope and elevation for a nonlinear gravity wave field. [in ocean surface

Science.gov (United States)

Huang, N. E.; Long, S. R.; Bliven, L. F.; Tung, C.-C.

1984-01-01

On the basis of the mapping method developed by Huang et al. (1983), an analytic expression for the non-Gaussian joint probability density function of slope and elevation for nonlinear gravity waves is derived. Various conditional and marginal density functions are also obtained through the joint density function. The analytic results are compared with a series of carefully controlled laboratory observations, and good agreement is noted. Furthermore, the laboratory wind wave field observations indicate that the capillary or capillary-gravity waves may not be the dominant components in determining the total roughness of the wave field. Thus, the analytic results, though derived specifically for the gravity waves, may have more general applications.

Probability of Failure in Random Vibration

DEFF Research Database (Denmark)

Nielsen, Søren R.K.; Sørensen, John Dalsgaard

1988-01-01

Close approximations to the first-passage probability of failure in random vibration can be obtained by integral equation methods. A simple relation exists between the first-passage probability density function and the distribution function for the time interval spent below a barrier before out......-crossing. An integral equation for the probability density function of the time interval is formulated, and adequate approximations for the kernel are suggested. The kernel approximation results in approximate solutions for the probability density function of the time interval and thus for the first-passage probability...

Interactive design of probability density functions for shape grammars

KAUST Repository

Dang, Minh

2015-11-02

A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density function (pdf) over such a shape space and to sample models according to the designed pdf. First, we propose a user interface that enables a user to quickly provide preference scores for selected shapes and suggest sampling strategies to decide which models to present to the user to evaluate. Second, we propose a novel kernel function to encode the similarity between two procedural models. Third, we propose a framework to interpolate user preference scores by combining multiple techniques: function factorization, Gaussian process regression, autorelevance detection, and l1 regularization. Fourth, we modify the original grammars to generate models with a pdf proportional to the user preference scores. Finally, we provide evaluations of our user interface and framework parameters and a comparison to other exploratory modeling techniques using modeling tasks in five example shape spaces: furniture, low-rise buildings, skyscrapers, airplanes, and vegetation.

On the method of logarithmic cumulants for parametric probability density function estimation.

Science.gov (United States)

Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane

2013-10-01

Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible.

Probabilistic Approach to Conditional Probability of Release of Hazardous Materials from Railroad Tank Cars during Accidents

Science.gov (United States)

2009-10-13

This paper describes a probabilistic approach to estimate the conditional probability of release of hazardous materials from railroad tank cars during train accidents. Monte Carlo methods are used in developing a probabilistic model to simulate head ...

Audio feature extraction using probability distribution function

Science.gov (United States)

Suhaib, A.; Wan, Khairunizam; Aziz, Azri A.; Hazry, D.; Razlan, Zuradzman M.; Shahriman A., B.

2015-05-01

Voice recognition has been one of the popular applications in robotic field. It is also known to be recently used for biometric and multimedia information retrieval system. This technology is attained from successive research on audio feature extraction analysis. Probability Distribution Function (PDF) is a statistical method which is usually used as one of the processes in complex feature extraction methods such as GMM and PCA. In this paper, a new method for audio feature extraction is proposed which is by using only PDF as a feature extraction method itself for speech analysis purpose. Certain pre-processing techniques are performed in prior to the proposed feature extraction method. Subsequently, the PDF result values for each frame of sampled voice signals obtained from certain numbers of individuals are plotted. From the experimental results obtained, it can be seen visually from the plotted data that each individuals' voice has comparable PDF values and shapes.

Conditional probability distribution associated to the E-M image reconstruction algorithm for neutron stimulated emission tomography

International Nuclear Information System (INIS)

Viana, R.S.; Yoriyaz, H.; Santos, A.

2011-01-01

The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)

Conditional probability distribution associated to the E-M image reconstruction algorithm for neutron stimulated emission tomography

Energy Technology Data Exchange (ETDEWEB)

Viana, R.S.; Yoriyaz, H.; Santos, A., E-mail: rodrigossviana@gmail.com, E-mail: hyoriyaz@ipen.br, E-mail: asantos@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)

Thermal and mechanical quantitative sensory testing in Chinese patients with burning mouth syndrome--a probable neuropathic pain condition?

Science.gov (United States)

Mo, Xueyin; Zhang, Jinglu; Fan, Yuan; Svensson, Peter; Wang, Kelun

2015-01-01

To explore the hypothesis that burning mouth syndrome (BMS) probably is a neuropathic pain condition, thermal and mechanical sensory and pain thresholds were tested and compared with age- and gender-matched control participants using a standardized battery of psychophysical techniques. Twenty-five BMS patients (men: 8, women: 17, age: 49.5 ± 11.4 years) and 19 age- and gender-matched healthy control participants were included. The cold detection threshold (CDT), warm detection threshold (WDT), cold pain threshold (CPT), heat pain threshold (HPT), mechanical detection threshold (MDT) and mechanical pain threshold (MPT), in accordance with the German Network of Neuropathic Pain guidelines, were measured at the following four sites: the dorsum of the left hand (hand), the skin at the mental foramen (chin), on the tip of the tongue (tongue), and the mucosa of the lower lip (lip). Statistical analysis was performed using ANOVA with repeated measures to compare the means within and between groups. Furthermore, Z-score profiles were generated, and exploratory correlation analyses between QST and clinical variables were performed. Two-tailed tests with a significance level of 5 % were used throughout. CDTs (P < 0.02) were significantly lower (less sensitivity) and HPTs (P < 0.001) were significantly higher (less sensitivity) at the tongue and lip in BMS patients compared to control participants. WDT (P = 0.007) was also significantly higher at the tongue in BMS patients compared to control subjects . There were no significant differences in MDT and MPT between the BMS patients and healthy subjects at any of the four test sites. Z-scores showed that significant loss of function can be identified for CDT (Z-scores = -0.9±1.1) and HPT (Z-scores = 1.5±0.4). There were no significant correlations between QST and clinical variables (pain intensity, duration, depressions scores). BMS patients had a significant loss of thermal function but not

Boundary conditions of the exact impulse wave function

International Nuclear Information System (INIS)

Gravielle, M.; Miraglia, J.E.

1997-01-01

The behavior of the exact impulse wave function is investigated at intermediate and high impact energies. Numerical details of the wave function and its perturbative potential are reported. We conclude that the impulse wave function does not tend to the proper Coulomb asymptotic limit. For electron capture, however, it is shown that the impulse wave function produces reliable probabilities even for intermediate velocities and symmetric collision systems. copyright 1997 The American Physical Society

Exact calculation of loop formation probability identifies folding motifs in RNA secondary structures

Science.gov (United States)

Sloma, Michael F.; Mathews, David H.

2016-01-01

RNA secondary structure prediction is widely used to analyze RNA sequences. In an RNA partition function calculation, free energy nearest neighbor parameters are used in a dynamic programming algorithm to estimate statistical properties of the secondary structure ensemble. Previously, partition functions have largely been used to estimate the probability that a given pair of nucleotides form a base pair, the conditional stacking probability, the accessibility to binding of a continuous stretch of nucleotides, or a representative sample of RNA structures. Here it is demonstrated that an RNA partition function can also be used to calculate the exact probability of formation of hairpin loops, internal loops, bulge loops, or multibranch loops at a given position. This calculation can also be used to estimate the probability of formation of specific helices. Benchmarking on a set of RNA sequences with known secondary structures indicated that loops that were calculated to be more probable were more likely to be present in the known structure than less probable loops. Furthermore, highly probable loops are more likely to be in the known structure than the set of loops predicted in the lowest free energy structures. PMID:27852924

Noise-level determination for discrete spectra with Gaussian or Lorentzian probability density functions

International Nuclear Information System (INIS)

Moriya, Netzer

2010-01-01

A method, based on binomial filtering, to estimate the noise level of an arbitrary, smoothed pure signal, contaminated with an additive, uncorrelated noise component is presented. If the noise characteristics of the experimental spectrum are known, as for instance the type of the corresponding probability density function (e.g., Gaussian), the noise properties can be extracted. In such cases, both the noise level, as may arbitrarily be defined, and a simulated white noise component can be generated, such that the simulated noise component is statistically indistinguishable from the true noise component present in the original signal. In this paper we present a detailed analysis of the noise level extraction when the additive noise is Gaussian or Lorentzian. We show that the statistical parameters in these cases (mainly the variance and the half width at half maximum, respectively) can directly be obtained from the experimental spectrum even when the pure signal is erratic. Further discussion is given for cases where the noise probability density function is initially unknown.

EDF: Computing electron number probability distribution functions in real space from molecular wave functions

Science.gov (United States)

Francisco, E.; Pendás, A. Martín; Blanco, M. A.

2008-04-01

Given an N-electron molecule and an exhaustive partition of the real space ( R) into m arbitrary regions Ω,Ω,…,Ω ( ⋃i=1mΩ=R), the edf program computes all the probabilities P(n,n,…,n) of having exactly n electrons in Ω, n electrons in Ω,…, and n electrons ( n+n+⋯+n=N) in Ω. Each Ω may correspond to a single basin (atomic domain) or several such basins (functional group). In the later case, each atomic domain must belong to a single Ω. The program can manage both single- and multi-determinant wave functions which are read in from an aimpac-like wave function description ( .wfn) file (T.A. Keith et al., The AIMPAC95 programs, http://www.chemistry.mcmaster.ca/aimpac, 1995). For multi-determinantal wave functions a generalization of the original .wfn file has been introduced. The new format is completely backwards compatible, adding to the previous structure a description of the configuration interaction (CI) coefficients and the determinants of correlated wave functions. Besides the .wfn file, edf only needs the overlap integrals over all the atomic domains between the molecular orbitals (MO). After the P(n,n,…,n) probabilities are computed, edf obtains from them several magnitudes relevant to chemical bonding theory, such as average electronic populations and localization/delocalization indices. Regarding spin, edf may be used in two ways: with or without a splitting of the P(n,n,…,n) probabilities into α and β spin components. Program summaryProgram title: edf Catalogue identifier: AEAJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAJ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 5387 No. of bytes in distributed program, including test data, etc.: 52 381 Distribution format: tar.gz Programming language: Fortran 77 Computer

Introduction to probability with Mathematica

CERN Document Server

Hastings, Kevin J

2009-01-01

Discrete ProbabilityThe Cast of Characters Properties of Probability Simulation Random SamplingConditional ProbabilityIndependenceDiscrete DistributionsDiscrete Random Variables, Distributions, and ExpectationsBernoulli and Binomial Random VariablesGeometric and Negative Binomial Random Variables Poisson DistributionJoint, Marginal, and Conditional Distributions More on ExpectationContinuous ProbabilityFrom the Finite to the (Very) Infinite Continuous Random Variables and DistributionsContinuous ExpectationContinuous DistributionsThe Normal Distribution Bivariate Normal DistributionNew Random Variables from OldOrder Statistics Gamma DistributionsChi-Square, Student's t, and F-DistributionsTransformations of Normal Random VariablesAsymptotic TheoryStrong and Weak Laws of Large Numbers Central Limit TheoremStochastic Processes and ApplicationsMarkov ChainsPoisson Processes QueuesBrownian MotionFinancial MathematicsAppendixIntroduction to Mathematica Glossary of Mathematica Commands for Probability Short Answers...

Evidence reasoning method for constructing conditional probability tables in a Bayesian network of multimorbidity.

Science.gov (United States)

Du, Yuanwei; Guo, Yubin

2015-01-01

The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and diagnosis are difficult to carry out accordingly. Bayesian networks can help to diagnose multimorbidity in health care, but it is difficult to obtain the conditional probability table (CPT) because of the lack of clinically statistical data. Today, expert knowledge and experience are increasingly used in training Bayesian networks in order to help predict or diagnose diseases, but the CPT in Bayesian networks is usually irrational or ineffective for ignoring realistic constraints especially in multimorbidity. In order to solve these problems, an evidence reasoning (ER) approach is employed to extract and fuse inference data from experts using a belief distribution and recursive ER algorithm, based on which evidence reasoning method for constructing conditional probability tables in Bayesian network of multimorbidity is presented step by step. A multimorbidity numerical example is used to demonstrate the method and prove its feasibility and application. Bayesian network can be determined as long as the inference assessment is inferred by each expert according to his/her knowledge or experience. Our method is more effective than existing methods for extracting expert inference data accurately and is fused effectively for constructing CPTs in a Bayesian network of multimorbidity.

Estimating the Probability of Traditional Copying, Conditional on Answer-Copying Statistics.

Science.gov (United States)

Allen, Jeff; Ghattas, Andrew

2016-06-01

Statistics for detecting copying on multiple-choice tests produce p values measuring the probability of a value at least as large as that observed, under the null hypothesis of no copying. The posterior probability of copying is arguably more relevant than the p value, but cannot be derived from Bayes' theorem unless the population probability of copying and probability distribution of the answer-copying statistic under copying are known. In this article, the authors develop an estimator for the posterior probability of copying that is based on estimable quantities and can be used with any answer-copying statistic. The performance of the estimator is evaluated via simulation, and the authors demonstrate how to apply the formula using actual data. Potential uses, generalizability to other types of cheating, and limitations of the approach are discussed.

Probability matching in perceptrons: Effects of conditional dependence and linear nonseparability.

Directory of Open Access Journals (Sweden)

Michael R W Dawson

Full Text Available Probability matching occurs when the behavior of an agent matches the likelihood of occurrence of events in the agent's environment. For instance, when artificial neural networks match probability, the activity in their output unit equals the past probability of reward in the presence of a stimulus. Our previous research demonstrated that simple artificial neural networks (perceptrons, which consist of a set of input units directly connected to a single output unit learn to match probability when presented different cues in isolation. The current paper extends this research by showing that perceptrons can match probabilities when presented simultaneous cues, with each cue signaling different reward likelihoods. In our first simulation, we presented up to four different cues simultaneously; the likelihood of reward signaled by the presence of one cue was independent of the likelihood of reward signaled by other cues. Perceptrons learned to match reward probabilities by treating each cue as an independent source of information about the likelihood of reward. In a second simulation, we violated the independence between cues by making some reward probabilities depend upon cue interactions. We did so by basing reward probabilities on a logical combination (AND or XOR of two of the four possible cues. We also varied the size of the reward associated with the logical combination. We discovered that this latter manipulation was a much better predictor of perceptron performance than was the logical structure of the interaction between cues. This indicates that when perceptrons learn to match probabilities, they do so by assuming that each signal of a reward is independent of any other; the best predictor of perceptron performance is a quantitative measure of the independence of these input signals, and not the logical structure of the problem being learned.

Probability matching in perceptrons: Effects of conditional dependence and linear nonseparability

Science.gov (United States)

2017-01-01

Probability matching occurs when the behavior of an agent matches the likelihood of occurrence of events in the agent’s environment. For instance, when artificial neural networks match probability, the activity in their output unit equals the past probability of reward in the presence of a stimulus. Our previous research demonstrated that simple artificial neural networks (perceptrons, which consist of a set of input units directly connected to a single output unit) learn to match probability when presented different cues in isolation. The current paper extends this research by showing that perceptrons can match probabilities when presented simultaneous cues, with each cue signaling different reward likelihoods. In our first simulation, we presented up to four different cues simultaneously; the likelihood of reward signaled by the presence of one cue was independent of the likelihood of reward signaled by other cues. Perceptrons learned to match reward probabilities by treating each cue as an independent source of information about the likelihood of reward. In a second simulation, we violated the independence between cues by making some reward probabilities depend upon cue interactions. We did so by basing reward probabilities on a logical combination (AND or XOR) of two of the four possible cues. We also varied the size of the reward associated with the logical combination. We discovered that this latter manipulation was a much better predictor of perceptron performance than was the logical structure of the interaction between cues. This indicates that when perceptrons learn to match probabilities, they do so by assuming that each signal of a reward is independent of any other; the best predictor of perceptron performance is a quantitative measure of the independence of these input signals, and not the logical structure of the problem being learned. PMID:28212422

Probability matching in perceptrons: Effects of conditional dependence and linear nonseparability.

Science.gov (United States)

Dawson, Michael R W; Gupta, Maya

2017-01-01

Probability matching occurs when the behavior of an agent matches the likelihood of occurrence of events in the agent's environment. For instance, when artificial neural networks match probability, the activity in their output unit equals the past probability of reward in the presence of a stimulus. Our previous research demonstrated that simple artificial neural networks (perceptrons, which consist of a set of input units directly connected to a single output unit) learn to match probability when presented different cues in isolation. The current paper extends this research by showing that perceptrons can match probabilities when presented simultaneous cues, with each cue signaling different reward likelihoods. In our first simulation, we presented up to four different cues simultaneously; the likelihood of reward signaled by the presence of one cue was independent of the likelihood of reward signaled by other cues. Perceptrons learned to match reward probabilities by treating each cue as an independent source of information about the likelihood of reward. In a second simulation, we violated the independence between cues by making some reward probabilities depend upon cue interactions. We did so by basing reward probabilities on a logical combination (AND or XOR) of two of the four possible cues. We also varied the size of the reward associated with the logical combination. We discovered that this latter manipulation was a much better predictor of perceptron performance than was the logical structure of the interaction between cues. This indicates that when perceptrons learn to match probabilities, they do so by assuming that each signal of a reward is independent of any other; the best predictor of perceptron performance is a quantitative measure of the independence of these input signals, and not the logical structure of the problem being learned.

Continuation of probability density functions using a generalized Lyapunov approach

Energy Technology Data Exchange (ETDEWEB)

Baars, S., E-mail: s.baars@rug.nl [Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, P.O. Box 407, 9700 AK Groningen (Netherlands); Viebahn, J.P., E-mail: viebahn@cwi.nl [Centrum Wiskunde & Informatica (CWI), P.O. Box 94079, 1090 GB, Amsterdam (Netherlands); Mulder, T.E., E-mail: t.e.mulder@uu.nl [Institute for Marine and Atmospheric research Utrecht, Department of Physics and Astronomy, Utrecht University, Princetonplein 5, 3584 CC Utrecht (Netherlands); Kuehn, C., E-mail: ckuehn@ma.tum.de [Technical University of Munich, Faculty of Mathematics, Boltzmannstr. 3, 85748 Garching bei München (Germany); Wubs, F.W., E-mail: f.w.wubs@rug.nl [Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, P.O. Box 407, 9700 AK Groningen (Netherlands); Dijkstra, H.A., E-mail: h.a.dijkstra@uu.nl [Institute for Marine and Atmospheric research Utrecht, Department of Physics and Astronomy, Utrecht University, Princetonplein 5, 3584 CC Utrecht (Netherlands); School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY (United States)

2017-05-01

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining probability density functions of systems of stochastic partial differential equations near fixed points, under a small noise approximation. Key innovation is the efficient solution of a generalized Lyapunov equation using an iterative method involving low-rank approximations. We apply and illustrate the capabilities of the method using a problem in physical oceanography, i.e. the occurrence of multiple steady states of the Atlantic Ocean circulation.

Spatial correlations and probability density function of the phase difference in a developed speckle-field: numerical and natural experiments

International Nuclear Information System (INIS)

Mysina, N Yu; Maksimova, L A; Ryabukho, V P; Gorbatenko, B B

2015-01-01

Investigated are statistical properties of the phase difference of oscillations in speckle-fields at two points in the far-field diffraction region, with different shapes of the scatterer aperture. Statistical and spatial nonuniformity of the probability density function of the field phase difference is established. Numerical experiments show that, for the speckle-fields with an oscillating alternating-sign transverse correlation function, a significant nonuniformity of the probability density function of the phase difference in the correlation region of the field complex amplitude, with the most probable values 0 and p, is observed. A natural statistical interference experiment using Young diagrams has confirmed the results of numerical experiments. (laser applications and other topics in quantum electronics)

Modelling detection probabilities to evaluate management and control tools for an invasive species

Science.gov (United States)

Christy, M.T.; Yackel Adams, A.A.; Rodda, G.H.; Savidge, J.A.; Tyrrell, C.L.

2010-01-01

For most ecologists, detection probability (p) is a nuisance variable that must be modelled to estimate the state variable of interest (i.e. survival, abundance, or occupancy). However, in the realm of invasive species control, the rate of detection and removal is the rate-limiting step for management of this pervasive environmental problem. For strategic planning of an eradication (removal of every individual), one must identify the least likely individual to be removed, and determine the probability of removing it. To evaluate visual searching as a control tool for populations of the invasive brown treesnake Boiga irregularis, we designed a mark-recapture study to evaluate detection probability as a function of time, gender, size, body condition, recent detection history, residency status, searcher team and environmental covariates. We evaluated these factors using 654 captures resulting from visual detections of 117 snakes residing in a 5-ha semi-forested enclosure on Guam, fenced to prevent immigration and emigration of snakes but not their prey. Visual detection probability was low overall (= 0??07 per occasion) but reached 0??18 under optimal circumstances. Our results supported sex-specific differences in detectability that were a quadratic function of size, with both small and large females having lower detection probabilities than males of those sizes. There was strong evidence for individual periodic changes in detectability of a few days duration, roughly doubling detection probability (comparing peak to non-elevated detections). Snakes in poor body condition had estimated mean detection probabilities greater than snakes with high body condition. Search teams with high average detection rates exhibited detection probabilities about twice that of search teams with low average detection rates. Surveys conducted with bright moonlight and strong wind gusts exhibited moderately decreased probabilities of detecting snakes. Synthesis and applications. By

Expected utility with lower probabilities

DEFF Research Database (Denmark)

Hendon, Ebbe; Jacobsen, Hans Jørgen; Sloth, Birgitte

1994-01-01

An uncertain and not just risky situation may be modeled using so-called belief functions assigning lower probabilities to subsets of outcomes. In this article we extend the von Neumann-Morgenstern expected utility theory from probability measures to belief functions. We use this theory...

Cross-Sectional Relationships of Physical Activity and Sedentary Behavior With Cognitive Function in Older Adults With Probable Mild Cognitive Impairment.

Science.gov (United States)

Falck, Ryan S; Landry, Glenn J; Best, John R; Davis, Jennifer C; Chiu, Bryan K; Liu-Ambrose, Teresa

2017-10-01

Mild cognitive impairment (MCI) represents a transition between normal cognitive aging and dementia and may represent a critical time frame for promoting cognitive health through behavioral strategies. Current evidence suggests that physical activity (PA) and sedentary behavior are important for cognition. However, it is unclear whether there are differences in PA and sedentary behavior between people with probable MCI and people without MCI or whether the relationships of PA and sedentary behavior with cognitive function differ by MCI status. The aims of this study were to examine differences in PA and sedentary behavior between people with probable MCI and people without MCI and whether associations of PA and sedentary behavior with cognitive function differed by MCI status. This was a cross-sectional study. Physical activity and sedentary behavior in adults dwelling in the community (N = 151; at least 55 years old) were measured using a wrist-worn actigraphy unit. The Montreal Cognitive Assessment was used to categorize participants with probable MCI (scores of Cognitive function was indexed using the Alzheimer Disease Assessment Scale-Cognitive-Plus (ADAS-Cog Plus). Physical activity and sedentary behavior were compared based on probable MCI status, and relationships of ADAS-Cog Plus with PA and sedentary behavior were examined by probable MCI status. Participants with probable MCI (n = 82) had lower PA and higher sedentary behavior than participants without MCI (n = 69). Higher PA and lower sedentary behavior were associated with better ADAS-Cog Plus performance in participants without MCI (β = -.022 and β = .012, respectively) but not in participants with probable MCI (β cognitive function. The diagnosis of MCI was not confirmed with a physician; therefore, this study could not conclude how many of the participants categorized as having probable MCI would actually have been diagnosed with MCI by a physician. Participants with probable MCI were less active

Ruin probabilities

DEFF Research Database (Denmark)

Asmussen, Søren; Albrecher, Hansjörg

The book gives a comprehensive treatment of the classical and modern ruin probability theory. Some of the topics are Lundberg's inequality, the Cramér-Lundberg approximation, exact solutions, other approximations (e.g., for heavy-tailed claim size distributions), finite horizon ruin probabilities......, extensions of the classical compound Poisson model to allow for reserve-dependent premiums, Markov-modulation, periodicity, change of measure techniques, phase-type distributions as a computational vehicle and the connection to other applied probability areas, like queueing theory. In this substantially...... updated and extended second version, new topics include stochastic control, fluctuation theory for Levy processes, Gerber–Shiu functions and dependence....

Concepts and Bounded Rationality: An Application of Niestegge's Approach to Conditional Quantum Probabilities

Science.gov (United States)

Blutner, Reinhard

2009-03-01

Recently, Gerd Niestegge developed a new approach to quantum mechanics via conditional probabilities developing the well-known proposal to consider the Lüders-von Neumann measurement as a non-classical extension of probability conditionalization. I will apply his powerful and rigorous approach to the treatment of concepts using a geometrical model of meaning. In this model, instances are treated as vectors of a Hilbert space H. In the present approach there are at least two possibilities to form categories. The first possibility sees categories as a mixture of its instances (described by a density matrix). In the simplest case we get the classical probability theory including the Bayesian formula. The second possibility sees categories formed by a distinctive prototype which is the superposition of the (weighted) instances. The construction of prototypes can be seen as transferring a mixed quantum state into a pure quantum state freezing the probabilistic characteristics of the superposed instances into the structure of the formed prototype. Closely related to the idea of forming concepts by prototypes is the existence of interference effects. Such inference effects are typically found in macroscopic quantum systems and I will discuss them in connection with several puzzles of bounded rationality. The present approach nicely generalizes earlier proposals made by authors such as Diederik Aerts, Andrei Khrennikov, Ricardo Franco, and Jerome Busemeyer. Concluding, I will suggest that an active dialogue between cognitive approaches to logic and semantics and the modern approach of quantum information science is mandatory.

New evolution equations for the joint response-excitation probability density function of stochastic solutions to first-order nonlinear PDEs

Science.gov (United States)

Venturi, D.; Karniadakis, G. E.

2012-08-01

By using functional integral methods we determine new evolution equations satisfied by the joint response-excitation probability density function (PDF) associated with the stochastic solution to first-order nonlinear partial differential equations (PDEs). The theory is presented for both fully nonlinear and for quasilinear scalar PDEs subject to random boundary conditions, random initial conditions or random forcing terms. Particular applications are discussed for the classical linear and nonlinear advection equations and for the advection-reaction equation. By using a Fourier-Galerkin spectral method we obtain numerical solutions of the proposed response-excitation PDF equations. These numerical solutions are compared against those obtained by using more conventional statistical approaches such as probabilistic collocation and multi-element probabilistic collocation methods. It is found that the response-excitation approach yields accurate predictions of the statistical properties of the system. In addition, it allows to directly ascertain the tails of probabilistic distributions, thus facilitating the assessment of rare events and associated risks. The computational cost of the response-excitation method is order magnitudes smaller than the one of more conventional statistical approaches if the PDE is subject to high-dimensional random boundary or initial conditions. The question of high-dimensionality for evolution equations involving multidimensional joint response-excitation PDFs is also addressed.

Probability density functions for CP-violating rephasing invariants

Science.gov (United States)

Fortin, Jean-François; Giasson, Nicolas; Marleau, Luc

2018-05-01

The implications of the anarchy principle on CP violation in the lepton sector are investigated. A systematic method is introduced to compute the probability density functions for the CP-violating rephasing invariants of the PMNS matrix from the Haar measure relevant to the anarchy principle. Contrary to the CKM matrix which is hierarchical, it is shown that the Haar measure, and hence the anarchy principle, are very likely to lead to the observed PMNS matrix. Predictions on the CP-violating Dirac rephasing invariant |jD | and Majorana rephasing invariant |j1 | are also obtained. They correspond to 〈 |jD | 〉 Haar = π / 105 ≈ 0.030 and 〈 |j1 | 〉 Haar = 1 / (6 π) ≈ 0.053 respectively, in agreement with the experimental hint from T2K of | jDexp | ≈ 0.032 ± 0.005 (or ≈ 0.033 ± 0.003) for the normal (or inverted) hierarchy.

Dynamic Forecasting Conditional Probability of Bombing Attacks Based on Time-Series and Intervention Analysis.

Science.gov (United States)

Li, Shuying; Zhuang, Jun; Shen, Shifei

2017-07-01

In recent years, various types of terrorist attacks occurred, causing worldwide catastrophes. According to the Global Terrorism Database (GTD), among all attack tactics, bombing attacks happened most frequently, followed by armed assaults. In this article, a model for analyzing and forecasting the conditional probability of bombing attacks (CPBAs) based on time-series methods is developed. In addition, intervention analysis is used to analyze the sudden increase in the time-series process. The results show that the CPBA increased dramatically at the end of 2011. During that time, the CPBA increased by 16.0% in a two-month period to reach the peak value, but still stays 9.0% greater than the predicted level after the temporary effect gradually decays. By contrast, no significant fluctuation can be found in the conditional probability process of armed assault. It can be inferred that some social unrest, such as America's troop withdrawal from Afghanistan and Iraq, could have led to the increase of the CPBA in Afghanistan, Iraq, and Pakistan. The integrated time-series and intervention model is used to forecast the monthly CPBA in 2014 and through 2064. The average relative error compared with the real data in 2014 is 3.5%. The model is also applied to the total number of attacks recorded by the GTD between 2004 and 2014. © 2016 Society for Risk Analysis.

Universal Probability Distribution Function for Bursty Transport in Plasma Turbulence

International Nuclear Information System (INIS)

Sandberg, I.; Benkadda, S.; Garbet, X.; Ropokis, G.; Hizanidis, K.; Castillo-Negrete, D. del

2009-01-01

Bursty transport phenomena associated with convective motion present universal statistical characteristics among different physical systems. In this Letter, a stochastic univariate model and the associated probability distribution function for the description of bursty transport in plasma turbulence is presented. The proposed stochastic process recovers the universal distribution of density fluctuations observed in plasma edge of several magnetic confinement devices and the remarkable scaling between their skewness S and kurtosis K. Similar statistical characteristics of variabilities have been also observed in other physical systems that are characterized by convection such as the x-ray fluctuations emitted by the Cygnus X-1 accretion disc plasmas and the sea surface temperature fluctuations.

Logic, probability, and human reasoning.

Science.gov (United States)

Johnson-Laird, P N; Khemlani, Sangeet S; Goodwin, Geoffrey P

2015-04-01

This review addresses the long-standing puzzle of how logic and probability fit together in human reasoning. Many cognitive scientists argue that conventional logic cannot underlie deductions, because it never requires valid conclusions to be withdrawn - not even if they are false; it treats conditional assertions implausibly; and it yields many vapid, although valid, conclusions. A new paradigm of probability logic allows conclusions to be withdrawn and treats conditionals more plausibly, although it does not address the problem of vapidity. The theory of mental models solves all of these problems. It explains how people reason about probabilities and postulates that the machinery for reasoning is itself probabilistic. Recent investigations accordingly suggest a way to integrate probability and deduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gravity and count probabilities in an expanding universe

Science.gov (United States)

Bouchet, Francois R.; Hernquist, Lars

1992-01-01

The time evolution of nonlinear clustering on large scales in cold dark matter, hot dark matter, and white noise models of the universe is investigated using N-body simulations performed with a tree code. Count probabilities in cubic cells are determined as functions of the cell size and the clustering state (redshift), and comparisons are made with various theoretical models. We isolate the features that appear to be the result of gravitational instability, those that depend on the initial conditions, and those that are likely a consequence of numerical limitations. More specifically, we study the development of skewness, kurtosis, and the fifth moment in relation to variance, the dependence of the void probability on time as well as on sparseness of sampling, and the overall shape of the count probability distribution. Implications of our results for theoretical and observational studies are discussed.

Exact joint density-current probability function for the asymmetric exclusion process.

Science.gov (United States)

Depken, Martin; Stinchcombe, Robin

2004-07-23

We study the asymmetric simple exclusion process with open boundaries and derive the exact form of the joint probability function for the occupation number and the current through the system. We further consider the thermodynamic limit, showing that the resulting distribution is non-Gaussian and that the density fluctuations have a discontinuity at the continuous phase transition, while the current fluctuations are continuous. The derivations are performed by using the standard operator algebraic approach and by the introduction of new operators satisfying a modified version of the original algebra. Copyright 2004 The American Physical Society

Probability-1

CERN Document Server

Shiryaev, Albert N

2016-01-01

This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, the measure-theoretic foundations of probability theory, weak convergence of probability measures, and the central limit theorem. Many examples are discussed in detail, and there are a large number of exercises. The book is accessible to advanced undergraduates and can be used as a text for independent study. To accommodate the greatly expanded material in the third edition of Probability, the book is now divided into two volumes. This first volume contains updated references and substantial revisions of the first three chapters of the second edition. In particular, new material has been added on generating functions, the inclusion-exclusion principle, theorems on monotonic classes (relying on a detailed treatment of “π-λ” systems), and the fundamental theorems of mathematical statistics.

Probability of K atomic shell ionization by heavy particles impact, in functions of the scattering angle

International Nuclear Information System (INIS)

Oliveira, P.M.C. de.

1976-12-01

A method of calculation of the K atomic shell ionization probability by heavy particles impact, in the semi-classical approximation is presented. In this approximation, the projectile has a classical trajectory. The potential energy due to the projectile is taken as perturbation of the Hamiltonian of the neutral atom. We use scaled Thomas-Fermi wave function for the atomic electrons. The method is valid for intermediate atomic number elements and particle energies of some MeV. Probabilities are calculated for the case of Ag (Z = 47) and protons of 1 and 2 MeV. Results are given as function of scattering angle, and agree well known experimental data and also improve older calculations. (Author) [pt

Systematics of the breakup probability function for {sup 6}Li and {sup 7}Li projectiles

Energy Technology Data Exchange (ETDEWEB)

Capurro, O.A., E-mail: capurro@tandar.cnea.gov.ar [Laboratorio TANDAR, Comisión Nacional de Energía Atómica, Av. General Paz 1499, B1650KNA San Martín, Buenos Aires (Argentina); Pacheco, A.J.; Arazi, A. [Laboratorio TANDAR, Comisión Nacional de Energía Atómica, Av. General Paz 1499, B1650KNA San Martín, Buenos Aires (Argentina); CONICET, Av. Rivadavia 1917, C1033AAJ Buenos Aires (Argentina); Carnelli, P.F.F. [CONICET, Av. Rivadavia 1917, C1033AAJ Buenos Aires (Argentina); Instituto de Investigación e Ingeniería Ambiental, Universidad Nacional de San Martín, 25 de Mayo y Francia, B1650BWA San Martín, Buenos Aires (Argentina); Fernández Niello, J.O. [Laboratorio TANDAR, Comisión Nacional de Energía Atómica, Av. General Paz 1499, B1650KNA San Martín, Buenos Aires (Argentina); CONICET, Av. Rivadavia 1917, C1033AAJ Buenos Aires (Argentina); Instituto de Investigación e Ingeniería Ambiental, Universidad Nacional de San Martín, 25 de Mayo y Francia, B1650BWA San Martín, Buenos Aires (Argentina); and others

2016-01-15

Experimental non-capture breakup cross sections can be used to determine the probability of projectile and ejectile fragmentation in nuclear reactions involving weakly bound nuclei. Recently, the probability of both type of dissociations has been analyzed in nuclear reactions involving {sup 9}Be projectiles onto various heavy targets at sub-barrier energies. In the present work we extend this kind of systematic analysis to the case of {sup 6}Li and {sup 7}Li projectiles with the purpose of investigating general features of projectile-like breakup probabilities for reactions induced by stable weakly bound nuclei. For that purpose we have obtained the probabilities of projectile and ejectile breakup for a large number of systems, starting from a compilation of the corresponding reported non-capture breakup cross sections. We parametrize the results in accordance with the previous studies for the case of beryllium projectiles, and we discuss their systematic behavior as a function of the projectile, the target mass and the reaction Q-value.

The limiting conditional probability distribution in a stochastic model of T cell repertoire maintenance.

Science.gov (United States)

Stirk, Emily R; Lythe, Grant; van den Berg, Hugo A; Hurst, Gareth A D; Molina-París, Carmen

2010-04-01

The limiting conditional probability distribution (LCD) has been much studied in the field of mathematical biology, particularly in the context of epidemiology and the persistence of epidemics. However, it has not yet been applied to the immune system. One of the characteristic features of the T cell repertoire is its diversity. This diversity declines in old age, whence the concepts of extinction and persistence are also relevant to the immune system. In this paper we model T cell repertoire maintenance by means of a continuous-time birth and death process on the positive integers, where the origin is an absorbing state. We show that eventual extinction is guaranteed. The late-time behaviour of the process before extinction takes place is modelled by the LCD, which we prove always exists for the process studied here. In most cases, analytic expressions for the LCD cannot be computed but the probability distribution may be approximated by means of the stationary probability distributions of two related processes. We show how these approximations are related to the LCD of the original process and use them to study the LCD in two special cases. We also make use of the large N expansion to derive a further approximation to the LCD. The accuracy of the various approximations is then analysed. (c) 2009 Elsevier Inc. All rights reserved.

Testing the Conditional Mean Function of Autoregressive Conditional Duration Models

DEFF Research Database (Denmark)

Hautsch, Nikolaus

be subject to censoring structures. In an empirical study based on financial transaction data we present an application of the model to estimate conditional asset price change probabilities. Evaluating the forecasting properties of the model, it is shown that the proposed approach is a promising competitor......This paper proposes a dynamic proportional hazard (PH) model with non-specified baseline hazard for the modelling of autoregressive duration processes. A categorization of the durations allows us to reformulate the PH model as an ordered response model based on extreme value distributed errors...

Random function representation of stationary stochastic vector processes for probability density evolution analysis of wind-induced structures

Science.gov (United States)

Liu, Zhangjun; Liu, Zenghui

2018-06-01

This paper develops a hybrid approach of spectral representation and random function for simulating stationary stochastic vector processes. In the proposed approach, the high-dimensional random variables, included in the original spectral representation (OSR) formula, could be effectively reduced to only two elementary random variables by introducing the random functions that serve as random constraints. Based on this, a satisfactory simulation accuracy can be guaranteed by selecting a small representative point set of the elementary random variables. The probability information of the stochastic excitations can be fully emerged through just several hundred of sample functions generated by the proposed approach. Therefore, combined with the probability density evolution method (PDEM), it could be able to implement dynamic response analysis and reliability assessment of engineering structures. For illustrative purposes, a stochastic turbulence wind velocity field acting on a frame-shear-wall structure is simulated by constructing three types of random functions to demonstrate the accuracy and efficiency of the proposed approach. Careful and in-depth studies concerning the probability density evolution analysis of the wind-induced structure have been conducted so as to better illustrate the application prospects of the proposed approach. Numerical examples also show that the proposed approach possesses a good robustness.

High throughput nonparametric probability density estimation.

Science.gov (United States)

Farmer, Jenny; Jacobs, Donald

2018-01-01

In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.

Prediction suppression in monkey inferotemporal cortex depends on the conditional probability between images.

Science.gov (United States)

Ramachandran, Suchitra; Meyer, Travis; Olson, Carl R

2016-01-01

When monkeys view two images in fixed sequence repeatedly over days and weeks, neurons in area TE of the inferotemporal cortex come to exhibit prediction suppression. The trailing image elicits only a weak response when presented following the leading image that preceded it during training. Induction of prediction suppression might depend either on the contiguity of the images, as determined by their co-occurrence and captured in the measure of joint probability P(A,B), or on their contingency, as determined by their correlation and as captured in the measures of conditional probability P(A|B) and P(B|A). To distinguish between these possibilities, we measured prediction suppression after imposing training regimens that held P(A,B) constant but varied P(A|B) and P(B|A). We found that reducing either P(A|B) or P(B|A) during training attenuated prediction suppression as measured during subsequent testing. We conclude that prediction suppression depends on contingency, as embodied in the predictive relations between the images, and not just on contiguity, as embodied in their co-occurrence. Copyright © 2016 the American Physiological Society.

Digital simulation of two-dimensional random fields with arbitrary power spectra and non-Gaussian probability distribution functions.

Science.gov (United States)

Yura, Harold T; Hanson, Steen G

2012-04-01

Methods for simulation of two-dimensional signals with arbitrary power spectral densities and signal amplitude probability density functions are disclosed. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the desired spectral distribution, after which this colored Gaussian probability distribution is transformed via an inverse transform into the desired probability distribution. In most cases the method provides satisfactory results and can thus be considered an engineering approach. Several illustrative examples with relevance for optics are given.

Probability of satellite collision

Science.gov (United States)

Mccarter, J. W.

1972-01-01

A method is presented for computing the probability of a collision between a particular artificial earth satellite and any one of the total population of earth satellites. The collision hazard incurred by the proposed modular Space Station is assessed using the technique presented. The results of a parametric study to determine what type of satellite orbits produce the greatest contribution to the total collision probability are presented. Collision probability for the Space Station is given as a function of Space Station altitude and inclination. Collision probability was also parameterized over miss distance and mission duration.

Electron-trapping probability in natural dosemeters as a function of irradiation temperature

DEFF Research Database (Denmark)

Wallinga, J.; Murray, A.S.; Wintle, A.G.

2002-01-01

The electron-trapping probability in OSL traps as a function of irradiation temperature is investigated for sedimentary quartz and feldspar. A dependency was found for both minerals; this phenomenon could give rise to errors in dose estimation when the irradiation temperature used in laboratory...... procedures is different from that in the natural environment. No evidence was found for the existence of shallow trap saturation effects that Could give rise to a dose-rate dependency of electron trapping....

Dictionary-Based Stochastic Expectation–Maximization for SAR Amplitude Probability Density Function Estimation

OpenAIRE

Moser , Gabriele; Zerubia , Josiane; Serpico , Sebastiano B.

2006-01-01

International audience; In remotely sensed data analysis, a crucial problem is represented by the need to develop accurate models for the statistics of the pixel intensities. This paper deals with the problem of probability density function (pdf) estimation in the context of synthetic aperture radar (SAR) amplitude data analysis. Several theoretical and heuristic models for the pdfs of SAR data have been proposed in the literature, which have been proved to be effective for different land-cov...

Emptiness formation probability of XX-chain in diffusion process

International Nuclear Information System (INIS)

Ogata, Yoshiko

2004-01-01

We study the distribution of emptiness formation probability of XX-model in the diffusion process. There exits a Gaussian decay as well as an exponential decay. The Gaussian decay is caused by the existence of zero point in the Fermi distribution function. The correlation length for each point of scaling factor varies up to the initial condition, monotonically or non-monotonically

[Conditional probability analysis between tinnitus and comorbidities in patients attending the National Rehabilitation Institute-LGII in the period 2012-2013].

Science.gov (United States)

Gómez Toledo, Verónica; Gutiérrez Farfán, Ileana; Verduzco-Mendoza, Antonio; Arch-Tirado, Emilio

Tinnitus is defined as the conscious perception of a sensation of sound that occurs in the absence of an external stimulus. This audiological symptom affects 7% to 19% of the adult population. The aim of this study is to describe the associated comorbidities present in patients with tinnitus usingjoint and conditional probability analysis. Patients of both genders, diagnosed with unilateral or bilateral tinnitus, aged between 20 and 45 years, and had a full computerised medical record, were selected. Study groups were formed on the basis of the following clinical aspects: 1) audiological findings; 2) vestibular findings; 3) comorbidities such as, temporomandibular dysfunction, tubal dysfunction, otosclerosis and, 4) triggering factors of tinnitus noise exposure, respiratory tract infection, use of ototoxic and/or drugs. Of the patients with tinnitus, 27 (65%) reported hearing loss, 11 (26.19%) temporomandibular dysfunction, and 11 (26.19%) with vestibular disorders. When performing the joint probability analysis, it was found that the probability that a patient with tinnitus having hearing loss was 2742 0.65, and 2042 0.47 for bilateral type. The result for P (A ∩ B)=30%. Bayes' theorem P (AiB) = P(Ai∩B)P(B) was used, and various probabilities were calculated. Therefore, in patients with temporomandibulardysfunction and vestibular disorders, a posterior probability of P (Aі/B)=31.44% was calculated. Consideration should be given to the joint and conditional probability approach as tools for the study of different pathologies. Copyright © 2016 Academia Mexicana de Cirugía A.C. Publicado por Masson Doyma México S.A. All rights reserved.

Audio Query by Example Using Similarity Measures between Probability Density Functions of Features

Directory of Open Access Journals (Sweden)

Marko Helén

2010-01-01

Full Text Available This paper proposes a query by example system for generic audio. We estimate the similarity of the example signal and the samples in the queried database by calculating the distance between the probability density functions (pdfs of their frame-wise acoustic features. Since the features are continuous valued, we propose to model them using Gaussian mixture models (GMMs or hidden Markov models (HMMs. The models parametrize each sample efficiently and retain sufficient information for similarity measurement. To measure the distance between the models, we apply a novel Euclidean distance, approximations of Kullback-Leibler divergence, and a cross-likelihood ratio test. The performance of the measures was tested in simulations where audio samples are automatically retrieved from a general audio database, based on the estimated similarity to a user-provided example. The simulations show that the distance between probability density functions is an accurate measure for similarity. Measures based on GMMs or HMMs are shown to produce better results than that of the existing methods based on simpler statistics or histograms of the features. A good performance with low computational cost is obtained with the proposed Euclidean distance.

Estimating the population size and colony boundary of subterranean termites by using the density functions of directionally averaged capture probability.

Science.gov (United States)

Su, Nan-Yao; Lee, Sang-Hee

2008-04-01

Marked termites were released in a linear-connected foraging arena, and the spatial heterogeneity of their capture probabilities was averaged for both directions at distance r from release point to obtain a symmetrical distribution, from which the density function of directionally averaged capture probability P(x) was derived. We hypothesized that as marked termites move into the population and given sufficient time, the directionally averaged capture probability may reach an equilibrium P(e) over the distance r and thus satisfy the equal mixing assumption of the mark-recapture protocol. The equilibrium capture probability P(e) was used to estimate the population size N. The hypothesis was tested in a 50-m extended foraging arena to simulate the distance factor of field colonies of subterranean termites. Over the 42-d test period, the density functions of directionally averaged capture probability P(x) exhibited four phases: exponential decline phase, linear decline phase, equilibrium phase, and postequilibrium phase. The equilibrium capture probability P(e), derived as the intercept of the linear regression during the equilibrium phase, correctly projected N estimates that were not significantly different from the known number of workers in the arena. Because the area beneath the probability density function is a constant (50% in this study), preequilibrium regression parameters and P(e) were used to estimate the population boundary distance 1, which is the distance between the release point and the boundary beyond which the population is absent.

Orthogonal Algorithm of Logic Probability and Syndrome-Testable Analysis

Institute of Scientific and Technical Information of China (English)

无

1990-01-01

A new method,orthogonal algoritm,is presented to compute the logic probabilities(i.e.signal probabilities)accurately,The transfer properties of logic probabilities are studied first,which are useful for the calculation of logic probability of the circuit with random independent inputs.Then the orthogonal algoritm is described to compute the logic probability of Boolean function realized by a combinational circuit.This algorithm can make Boolean function “ORTHOGONAL”so that the logic probabilities can be easily calculated by summing up the logic probabilities of all orthogonal terms of the Booleam function.

Calculation of probability density functions for temperature and precipitation change under global warming

International Nuclear Information System (INIS)

Watterson, Ian G.

2007-01-01

Full text: he IPCC Fourth Assessment Report (Meehl ef al. 2007) presents multi-model means of the CMIP3 simulations as projections of the global climate change over the 21st century under several SRES emission scenarios. To assess the possible range of change for Australia based on the CMIP3 ensemble, we can follow Whetton etal. (2005) and use the 'pattern scaling' approach, which separates the uncertainty in the global mean warming from that in the local change per degree of warming. This study presents several ways of representing these two factors as probability density functions (PDFs). The beta distribution, a smooth, bounded, function allowing skewness, is found to provide a useful representation of the range of CMIP3 results. A weighting of models based on their skill in simulating seasonal means in the present climate over Australia is included. Dessai ef al. (2005) and others have used Monte-Carlo sampling to recombine such global warming and scaled change factors into values of net change. Here, we use a direct integration of the product across the joint probability space defined by the two PDFs. The result is a cumulative distribution function (CDF) for change, for each variable, location, and season. The median of this distribution provides a best estimate of change, while the 10th and 90th percentiles represent a likely range. The probability of exceeding a specified threshold can also be extracted from the CDF. The presentation focuses on changes in Australian temperature and precipitation at 2070 under the A1B scenario. However, the assumption of linearity behind pattern scaling allows results for different scenarios and times to be simply obtained. In the case of precipitation, which must remain non-negative, a simple modification of the calculations (based on decreases being exponential with warming) is used to avoid unrealistic results. These approaches are currently being used for the new CSIRO/ Bureau of Meteorology climate projections

Risk Probabilities

DEFF Research Database (Denmark)

Rojas-Nandayapa, Leonardo

Tail probabilities of sums of heavy-tailed random variables are of a major importance in various branches of Applied Probability, such as Risk Theory, Queueing Theory, Financial Management, and are subject to intense research nowadays. To understand their relevance one just needs to think...... analytic expression for the distribution function of a sum of random variables. The presence of heavy-tailed random variables complicates the problem even more. The objective of this dissertation is to provide better approximations by means of sharp asymptotic expressions and Monte Carlo estimators...

Impaired mismatch negativity (MMN) generation in schizophrenia as a function of stimulus deviance, probability, and interstimulus/interdeviant interval.

Science.gov (United States)

Javitt, D C; Grochowski, S; Shelley, A M; Ritter, W

1998-03-01

Schizophrenia is a severe mental disorder associated with disturbances in perception and cognition. Event-related potentials (ERP) provide a mechanism for evaluating potential mechanisms underlying neurophysiological dysfunction in schizophrenia. Mismatch negativity (MMN) is a short-duration auditory cognitive ERP component that indexes operation of the auditory sensory ('echoic') memory system. Prior studies have demonstrated impaired MMN generation in schizophrenia along with deficits in auditory sensory memory performance. MMN is elicited in an auditory oddball paradigm in which a sequence of repetitive standard tones is interrupted infrequently by a physically deviant ('oddball') stimulus. The present study evaluates MMN generation as a function of deviant stimulus probability, interstimulus interval, interdeviant interval and the degree of pitch separation between the standard and deviant stimuli. The major findings of the present study are first, that MMN amplitude is decreased in schizophrenia across a broad range of stimulus conditions, and second, that the degree of deficit in schizophrenia is largest under conditions when MMN is normally largest. The pattern of deficit observed in schizophrenia differs from the pattern observed in other conditions associated with MMN dysfunction, including Alzheimer's disease, stroke, and alcohol intoxication.

A new formulation of the probability density function in random walk models for atmospheric dispersion

DEFF Research Database (Denmark)

Falk, Anne Katrine Vinther; Gryning, Sven-Erik

1997-01-01

In this model for atmospheric dispersion particles are simulated by the Langevin Equation, which is a stochastic differential equation. It uses the probability density function (PDF) of the vertical velocity fluctuations as input. The PDF is constructed as an expansion after Hermite polynomials...

Probability calculus of fractional order and fractional Taylor's series application to Fokker-Planck equation and information of non-random functions

International Nuclear Information System (INIS)

Jumarie, Guy

2009-01-01

A probability distribution of fractional (or fractal) order is defined by the measure μ{dx} = p(x)(dx) α , 0 α (D x α h α )f(x) provided by the modified Riemann Liouville definition, one can expand a probability calculus parallel to the standard one. A Fourier's transform of fractional order using the Mittag-Leffler function is introduced, together with its inversion formula; and it provides a suitable generalization of the characteristic function of fractal random variables. It appears that the state moments of fractional order are more especially relevant. The main properties of this fractional probability calculus are outlined, it is shown that it provides a sound approach to Fokker-Planck equation which are fractional in both space and time, and it provides new results in the information theory of non-random functions.

A brief introduction to probability.

Science.gov (United States)

Di Paola, Gioacchino; Bertani, Alessandro; De Monte, Lavinia; Tuzzolino, Fabio

2018-02-01

The theory of probability has been debated for centuries: back in 1600, French mathematics used the rules of probability to place and win bets. Subsequently, the knowledge of probability has significantly evolved and is now an essential tool for statistics. In this paper, the basic theoretical principles of probability will be reviewed, with the aim of facilitating the comprehension of statistical inference. After a brief general introduction on probability, we will review the concept of the "probability distribution" that is a function providing the probabilities of occurrence of different possible outcomes of a categorical or continuous variable. Specific attention will be focused on normal distribution that is the most relevant distribution applied to statistical analysis.

Schema bias in source monitoring varies with encoding conditions: support for a probability-matching account.

Science.gov (United States)

Kuhlmann, Beatrice G; Vaterrodt, Bianca; Bayen, Ute J

2012-09-01

Two experiments examined reliance on schematic knowledge in source monitoring. Based on a probability-matching account of source guessing, a schema bias will only emerge if participants do not have a representation of the source-item contingency in the study list, or if the perceived contingency is consistent with schematic expectations. Thus, the account predicts that encoding conditions that affect contingency detection also affect schema bias. In Experiment 1, the schema bias commonly found when schematic information about the sources is not provided before encoding was diminished by an intentional source-memory instruction. In Experiment 2, the depth of processing of schema-consistent and schema-inconsistent source-item pairings was manipulated. Participants consequently overestimated the occurrence of the pairing type they processed in a deep manner, and their source guessing reflected this biased contingency perception. Results support the probability-matching account of source guessing. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Cytoarchitecture, probability maps and functions of the human frontal pole.

Science.gov (United States)

Bludau, S; Eickhoff, S B; Mohlberg, H; Caspers, S; Laird, A R; Fox, P T; Schleicher, A; Zilles, K; Amunts, K

2014-06-01

The frontal pole has more expanded than any other part in the human brain as compared to our ancestors. It plays an important role for specifically human behavior and cognitive abilities, e.g. action selection (Kovach et al., 2012). Evidence about divergent functions of its medial and lateral part has been provided, both in the healthy brain and in psychiatric disorders. The anatomical correlates of such functional segregation, however, are still unknown due to a lack of stereotaxic, microstructural maps obtained in a representative sample of brains. Here we show that the human frontopolar cortex consists of two cytoarchitectonically and functionally distinct areas: lateral frontopolar area 1 (Fp1) and medial frontopolar area 2 (Fp2). Based on observer-independent mapping in serial, cell-body stained sections of 10 brains, three-dimensional, probabilistic maps of areas Fp1 and Fp2 were created. They show, for each position of the reference space, the probability with which each area was found in a particular voxel. Applying these maps as seed regions for a meta-analysis revealed that Fp1 and Fp2 differentially contribute to functional networks: Fp1 was involved in cognition, working memory and perception, whereas Fp2 was part of brain networks underlying affective processing and social cognition. The present study thus disclosed cortical correlates of a functional segregation of the human frontopolar cortex. The probabilistic maps provide a sound anatomical basis for interpreting neuroimaging data in the living human brain, and open new perspectives for analyzing structure-function relationships in the prefrontal cortex. The new data will also serve as a starting point for further comparative studies between human and non-human primate brains. This allows finding similarities and differences in the organizational principles of the frontal lobe during evolution as neurobiological basis for our behavior and cognitive abilities. Copyright © 2013 Elsevier Inc. All

The maximum entropy method of moments and Bayesian probability theory

Science.gov (United States)

Bretthorst, G. Larry

2013-08-01

The problem of density estimation occurs in many disciplines. For example, in MRI it is often necessary to classify the types of tissues in an image. To perform this classification one must first identify the characteristics of the tissues to be classified. These characteristics might be the intensity of a T1 weighted image and in MRI many other types of characteristic weightings (classifiers) may be generated. In a given tissue type there is no single intensity that characterizes the tissue, rather there is a distribution of intensities. Often this distributions can be characterized by a Gaussian, but just as often it is much more complicated. Either way, estimating the distribution of intensities is an inference problem. In the case of a Gaussian distribution, one must estimate the mean and standard deviation. However, in the Non-Gaussian case the shape of the density function itself must be inferred. Three common techniques for estimating density functions are binned histograms [1, 2], kernel density estimation [3, 4], and the maximum entropy method of moments [5, 6]. In the introduction, the maximum entropy method of moments will be reviewed. Some of its problems and conditions under which it fails will be discussed. Then in later sections, the functional form of the maximum entropy method of moments probability distribution will be incorporated into Bayesian probability theory. It will be shown that Bayesian probability theory solves all of the problems with the maximum entropy method of moments. One gets posterior probabilities for the Lagrange multipliers, and, finally, one can put error bars on the resulting estimated density function.

Computation of Probabilities in Causal Models of History of Science

Directory of Open Access Journals (Sweden)

Osvaldo Pessoa Jr.

2006-12-01

Full Text Available : The aim of this paper is to investigate the ascription of probabilities in a causal model of an episode in the history of science. The aim of such a quantitative approach is to allow the implementation of the causal model in a computer, to run simulations. As an example, we look at the beginning of the science of magnetism, “explaining” — in a probabilistic way, in terms of a single causal model — why the field advanced in China but not in Europe (the difference is due to different prior probabilities of certain cultural manifestations. Given the number of years between the occurrences of two causally connected advances X and Y, one proposes a criterion for stipulating the value pY=X of the conditional probability of an advance Y occurring, given X. Next, one must assume a specific form for the cumulative probability function pY=X(t, which we take to be the time integral of an exponential distribution function, as is done in physics of radioactive decay. Rules for calculating the cumulative functions for more than two events are mentioned, involving composition, disjunction and conjunction of causes. We also consider the problems involved in supposing that the appearance of events in time follows an exponential distribution, which are a consequence of the fact that a composition of causes does not follow an exponential distribution, but a “hypoexponential” one. We suggest that a gamma distribution function might more adequately represent the appearance of advances.

Theoretical determination of gamma spectrometry systems efficiency based on probability functions. Application to self-attenuation correction factors

Energy Technology Data Exchange (ETDEWEB)

Barrera, Manuel, E-mail: manuel.barrera@uca.es [Escuela Superior de Ingeniería, University of Cadiz, Avda, Universidad de Cadiz 10, 11519 Puerto Real, Cadiz (Spain); Suarez-Llorens, Alfonso [Facultad de Ciencias, University of Cadiz, Avda, Rep. Saharaui s/n, 11510 Puerto Real, Cadiz (Spain); Casas-Ruiz, Melquiades; Alonso, José J.; Vidal, Juan [CEIMAR, University of Cadiz, Avda, Rep. Saharaui s/n, 11510 Puerto Real, Cádiz (Spain)

2017-05-11

A generic theoretical methodology for the calculation of the efficiency of gamma spectrometry systems is introduced in this work. The procedure is valid for any type of source and detector and can be applied to determine the full energy peak and the total efficiency of any source-detector system. The methodology is based on the idea of underlying probability of detection, which describes the physical model for the detection of the gamma radiation at the particular studied situation. This probability depends explicitly on the direction of the gamma radiation, allowing the use of this dependence the development of more realistic and complex models than the traditional models based on the point source integration. The probability function that has to be employed in practice must reproduce the relevant characteristics of the detection process occurring at the particular studied situation. Once the probability is defined, the efficiency calculations can be performed in general by using numerical methods. Monte Carlo integration procedure is especially useful to perform the calculations when complex probability functions are used. The methodology can be used for the direct determination of the efficiency and also for the calculation of corrections that require this determination of the efficiency, as it is the case of coincidence summing, geometric or self-attenuation corrections. In particular, we have applied the procedure to obtain some of the classical self-attenuation correction factors usually employed to correct for the sample attenuation of cylindrical geometry sources. The methodology clarifies the theoretical basis and approximations associated to each factor, by making explicit the probability which is generally hidden and implicit to each model. It has been shown that most of these self-attenuation correction factors can be derived by using a common underlying probability, having this probability a growing level of complexity as it reproduces more precisely

The Importance of Conditional Probability in Diagnostic Reasoning and Clinical Decision Making: A Primer for the Eye Care Practitioner.

Science.gov (United States)

Sanfilippo, Paul G; Hewitt, Alex W; Mackey, David A

2017-04-01

To outline and detail the importance of conditional probability in clinical decision making and discuss the various diagnostic measures eye care practitioners should be aware of in order to improve the scope of their clinical practice. We conducted a review of the importance of conditional probability in diagnostic testing for the eye care practitioner. Eye care practitioners use diagnostic tests on a daily basis to assist in clinical decision making and optimizing patient care and management. These tests provide probabilistic information that can enable the clinician to increase (or decrease) their level of certainty about the presence of a particular condition. While an understanding of the characteristics of diagnostic tests are essential to facilitate proper interpretation of test results and disease risk, many practitioners either confuse or misinterpret these measures. In the interests of their patients, practitioners should be aware of the basic concepts associated with diagnostic testing and the simple mathematical rule that underpins them. Importantly, the practitioner needs to recognize that the prevalence of a disease in the population greatly determines the clinical value of a diagnostic test.

Conditional non-independence of radiographic image features and the derivation of post-test probabilities – A mammography BI-RADS example

International Nuclear Information System (INIS)

Benndorf, Matthias

2012-01-01

Bayes' theorem has proven to be one of the cornerstones in medical decision making. It allows for the derivation of post-test probabilities, which in case of a positive test result become positive predictive values. If several test results are observed successively Bayes' theorem may be used with assumed conditional independence of test results or with incorporated conditional dependencies. Herein it is examined whether radiographic image features should be considered conditionally independent diagnostic tests when post-test probabilities are to be derived. For this purpose the mammographic mass dataset from the UCI (University of California, Irvine) machine learning repository is analysed. It comprises the description of 961 (516 benign, 445 malignant) mammographic mass lesions according to the BI-RADS (Breast Imaging: Reporting and Data System) lexicon. Firstly, an exhaustive correlation matrix is presented for mammography BI-RADS features among benign and malignant lesions separately; correlation can be regarded as measure for conditional dependence. Secondly, it is shown that the derived positive predictive values for the conjunction of the two features “irregular shape” and “spiculated margin” differ significantly depending on whether conditional dependencies are incorporated into the decision process or not. It is concluded that radiographic image features should not generally be regarded as conditionally independent diagnostic tests.

Probability of detection as a function of multiple influencing parameters

Energy Technology Data Exchange (ETDEWEB)

Pavlovic, Mato

2014-10-15

Non-destructive testing is subject to measurement uncertainties. In safety critical applications the reliability assessment of its capability to detect flaws is therefore necessary. In most applications, the flaw size is the single most important parameter that influences the probability of detection (POD) of the flaw. That is why the POD is typically calculated and expressed as a function of the flaw size. The capability of the inspection system to detect flaws is established by comparing the size of reliably detected flaw with the size of the flaw that is critical for the structural integrity. Applications where several factors have an important influence on the POD are investigated in this dissertation. To devise a reliable estimation of the NDT system capability it is necessary to express the POD as a function of all these factors. A multi-parameter POD model is developed. It enables POD to be calculated and expressed as a function of several influencing parameters. The model was tested on the data from the ultrasonic inspection of copper and cast iron components with artificial flaws. Also, a technique to spatially present POD data called the volume POD is developed. The fusion of the POD data coming from multiple inspections of the same component with different sensors is performed to reach the overall POD of the inspection system.

Probability of detection as a function of multiple influencing parameters

International Nuclear Information System (INIS)

Pavlovic, Mato

2014-01-01

Non-destructive testing is subject to measurement uncertainties. In safety critical applications the reliability assessment of its capability to detect flaws is therefore necessary. In most applications, the flaw size is the single most important parameter that influences the probability of detection (POD) of the flaw. That is why the POD is typically calculated and expressed as a function of the flaw size. The capability of the inspection system to detect flaws is established by comparing the size of reliably detected flaw with the size of the flaw that is critical for the structural integrity. Applications where several factors have an important influence on the POD are investigated in this dissertation. To devise a reliable estimation of the NDT system capability it is necessary to express the POD as a function of all these factors. A multi-parameter POD model is developed. It enables POD to be calculated and expressed as a function of several influencing parameters. The model was tested on the data from the ultrasonic inspection of copper and cast iron components with artificial flaws. Also, a technique to spatially present POD data called the volume POD is developed. The fusion of the POD data coming from multiple inspections of the same component with different sensors is performed to reach the overall POD of the inspection system.

Wave functions and two-electron probability distributions of the Hooke's-law atom and helium

International Nuclear Information System (INIS)

O'Neill, Darragh P.; Gill, Peter M. W.

2003-01-01

The Hooke's-law atom (hookium) provides an exactly soluble model for a two-electron atom in which the nuclear-electron Coulombic attraction has been replaced by a harmonic one. Starting from the known exact position-space wave function for the ground state of hookium, we present the momentum-space wave function. We also look at the intracules, two-electron probability distributions, for hookium in position, momentum, and phase space. These are compared with the Hartree-Fock results and the Coulomb holes (the difference between the exact and Hartree-Fock intracules) in position, momentum, and phase space are examined. We then compare these results with analogous results for the ground state of helium using a simple, explicitly correlated wave function

Using Prediction Markets to Generate Probability Density Functions for Climate Change Risk Assessment

Science.gov (United States)

Boslough, M.

2011-12-01

Climate-related uncertainty is traditionally presented as an error bar, but it is becoming increasingly common to express it in terms of a probability density function (PDF). PDFs are a necessary component of probabilistic risk assessments, for which simple "best estimate" values are insufficient. Many groups have generated PDFs for climate sensitivity using a variety of methods. These PDFs are broadly consistent, but vary significantly in their details. One axiom of the verification and validation community is, "codes don't make predictions, people make predictions." This is a statement of the fact that subject domain experts generate results using assumptions within a range of epistemic uncertainty and interpret them according to their expert opinion. Different experts with different methods will arrive at different PDFs. For effective decision support, a single consensus PDF would be useful. We suggest that market methods can be used to aggregate an ensemble of opinions into a single distribution that expresses the consensus. Prediction markets have been shown to be highly successful at forecasting the outcome of events ranging from elections to box office returns. In prediction markets, traders can take a position on whether some future event will or will not occur. These positions are expressed as contracts that are traded in a double-action market that aggregates price, which can be interpreted as a consensus probability that the event will take place. Since climate sensitivity cannot directly be measured, it cannot be predicted. However, the changes in global mean surface temperature are a direct consequence of climate sensitivity, changes in forcing, and internal variability. Viable prediction markets require an undisputed event outcome on a specific date. Climate-related markets exist on Intrade.com, an online trading exchange. One such contract is titled "Global Temperature Anomaly for Dec 2011 to be greater than 0.65 Degrees C." Settlement is based

Pre-Service Teachers' Conceptions of Probability

Science.gov (United States)

Odafe, Victor U.

2011-01-01

Probability knowledge and skills are needed in science and in making daily decisions that are sometimes made under uncertain conditions. Hence, there is the need to ensure that the pre-service teachers of our children are well prepared to teach probability. Pre-service teachers' conceptions of probability are identified, and ways of helping them…

Economic choices reveal probability distortion in macaque monkeys.

Science.gov (United States)

Stauffer, William R; Lak, Armin; Bossaerts, Peter; Schultz, Wolfram

2015-02-18

Economic choices are largely determined by two principal elements, reward value (utility) and probability. Although nonlinear utility functions have been acknowledged for centuries, nonlinear probability weighting (probability distortion) was only recently recognized as a ubiquitous aspect of real-world choice behavior. Even when outcome probabilities are known and acknowledged, human decision makers often overweight low probability outcomes and underweight high probability outcomes. Whereas recent studies measured utility functions and their corresponding neural correlates in monkeys, it is not known whether monkeys distort probability in a manner similar to humans. Therefore, we investigated economic choices in macaque monkeys for evidence of probability distortion. We trained two monkeys to predict reward from probabilistic gambles with constant outcome values (0.5 ml or nothing). The probability of winning was conveyed using explicit visual cues (sector stimuli). Choices between the gambles revealed that the monkeys used the explicit probability information to make meaningful decisions. Using these cues, we measured probability distortion from choices between the gambles and safe rewards. Parametric modeling of the choices revealed classic probability weighting functions with inverted-S shape. Therefore, the animals overweighted low probability rewards and underweighted high probability rewards. Empirical investigation of the behavior verified that the choices were best explained by a combination of nonlinear value and nonlinear probability distortion. Together, these results suggest that probability distortion may reflect evolutionarily preserved neuronal processing. Copyright © 2015 Stauffer et al.

Rainfall and net infiltration probabilities for future climate conditions at Yucca Mountain

International Nuclear Information System (INIS)

Long, A.; Childs, S.W.

1993-01-01

Performance assessment of repository integrity is a task rendered difficult because it requires predicting the future. This challenge has occupied many scientists who realize that the best assessments are required to maximize the probability of successful repository sitting and design. As part of a performance assessment effort directed by the EPRI, the authors have used probabilistic methods to assess the magnitude and timing of net infiltration at Yucca Mountain. A mathematical model for net infiltration previously published incorporated a probabilistic treatment of climate, surface hydrologic processes and a mathematical model of the infiltration process. In this paper, we present the details of the climatological analysis. The precipitation model is event-based, simulating characteristics of modern rainfall near Yucca Mountain, then extending the model to most likely values for different degrees of pluvial climates. Next the precipitation event model is fed into a process-based infiltration model that considers spatial variability in parameters relevant to net infiltration of Yucca Mountain. The model predicts that average annual net infiltration at Yucca Mountain will range from a mean of about 1 mm under present climatic conditions to a mean of at least 2.4 mm under full glacial (pluvial) conditions. Considerable variations about these means are expected to occur from year-to-year

Probability elements of the mathematical theory

CERN Document Server

Heathcote, C R

2000-01-01

Designed for students studying mathematical statistics and probability after completing a course in calculus and real variables, this text deals with basic notions of probability spaces, random variables, distribution functions and generating functions, as well as joint distributions and the convergence properties of sequences of random variables. Includes worked examples and over 250 exercises with solutions.

Estimation of the probability of success in petroleum exploration

Science.gov (United States)

Davis, J.C.

1977-01-01

A probabilistic model for oil exploration can be developed by assessing the conditional relationship between perceived geologic variables and the subsequent discovery of petroleum. Such a model includes two probabilistic components, the first reflecting the association between a geologic condition (structural closure, for example) and the occurrence of oil, and the second reflecting the uncertainty associated with the estimation of geologic variables in areas of limited control. Estimates of the conditional relationship between geologic variables and subsequent production can be found by analyzing the exploration history of a "training area" judged to be geologically similar to the exploration area. The geologic variables are assessed over the training area using an historical subset of the available data, whose density corresponds to the present control density in the exploration area. The success or failure of wells drilled in the training area subsequent to the time corresponding to the historical subset provides empirical estimates of the probability of success conditional upon geology. Uncertainty in perception of geological conditions may be estimated from the distribution of errors made in geologic assessment using the historical subset of control wells. These errors may be expressed as a linear function of distance from available control. Alternatively, the uncertainty may be found by calculating the semivariogram of the geologic variables used in the analysis: the two procedures will yield approximately equivalent results. The empirical probability functions may then be transferred to the exploration area and used to estimate the likelihood of success of specific exploration plays. These estimates will reflect both the conditional relationship between the geological variables used to guide exploration and the uncertainty resulting from lack of control. The technique is illustrated with case histories from the mid-Continent area of the U.S.A. ?? 1977 Plenum

Risk estimation using probability machines

Science.gov (United States)

2014-01-01

Background Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. Results We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. Conclusions The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from. PMID:24581306

Probability density function evolution of power systems subject to stochastic variation of renewable energy

Science.gov (United States)

Wei, J. Q.; Cong, Y. C.; Xiao, M. Q.

2018-05-01

As renewable energies are increasingly integrated into power systems, there is increasing interest in stochastic analysis of power systems.Better techniques should be developed to account for the uncertainty caused by penetration of renewables and consequently analyse its impacts on stochastic stability of power systems. In this paper, the Stochastic Differential Equations (SDEs) are used to represent the evolutionary behaviour of the power systems. The stationary Probability Density Function (PDF) solution to SDEs modelling power systems excited by Gaussian white noise is analysed. Subjected to such random excitation, the Joint Probability Density Function (JPDF) solution to the phase angle and angular velocity is governed by the generalized Fokker-Planck-Kolmogorov (FPK) equation. To solve this equation, the numerical method is adopted. Special measure is taken such that the generalized FPK equation is satisfied in the average sense of integration with the assumed PDF. Both weak and strong intensities of the stochastic excitations are considered in a single machine infinite bus power system. The numerical analysis has the same result as the one given by the Monte Carlo simulation. Potential studies on stochastic behaviour of multi-machine power systems with random excitations are discussed at the end.

Autoregressive processes with exponentially decaying probability distribution functions: applications to daily variations of a stock market index.

Science.gov (United States)

Porto, Markus; Roman, H Eduardo

2002-04-01

We consider autoregressive conditional heteroskedasticity (ARCH) processes in which the variance sigma(2)(y) depends linearly on the absolute value of the random variable y as sigma(2)(y) = a+b absolute value of y. While for the standard model, where sigma(2)(y) = a + b y(2), the corresponding probability distribution function (PDF) P(y) decays as a power law for absolute value of y-->infinity, in the linear case it decays exponentially as P(y) approximately exp(-alpha absolute value of y), with alpha = 2/b. We extend these results to the more general case sigma(2)(y) = a+b absolute value of y(q), with 0 history of the ARCH process is taken into account, the resulting PDF becomes a stretched exponential even for q = 1, with a stretched exponent beta = 2/3, in a much better agreement with the empirical data.

Determination of probability density functions for parameters in the Munson-Dawson model for creep behavior of salt

International Nuclear Information System (INIS)

Pfeifle, T.W.; Mellegard, K.D.; Munson, D.E.

1992-10-01

The modified Munson-Dawson (M-D) constitutive model that describes the creep behavior of salt will be used in performance assessment calculations to assess compliance of the Waste Isolation Pilot Plant (WIPP) facility with requirements governing the disposal of nuclear waste. One of these standards requires that the uncertainty of future states of the system, material model parameters, and data be addressed in the performance assessment models. This paper presents a method in which measurement uncertainty and the inherent variability of the material are characterized by treating the M-D model parameters as random variables. The random variables can be described by appropriate probability distribution functions which then can be used in Monte Carlo or structural reliability analyses. Estimates of three random variables in the M-D model were obtained by fitting a scalar form of the model to triaxial compression creep data generated from tests of WIPP salt. Candidate probability distribution functions for each of the variables were then fitted to the estimates and their relative goodness-of-fit tested using the Kolmogorov-Smirnov statistic. A sophisticated statistical software package obtained from BMDP Statistical Software, Inc. was used in the M-D model fitting. A separate software package, STATGRAPHICS, was used in fitting the candidate probability distribution functions to estimates of the variables. Skewed distributions, i.e., lognormal and Weibull, were found to be appropriate for the random variables analyzed

Probability theory for 3-layer remote sensing in ideal gas law environment.

Science.gov (United States)

Ben-David, Avishai; Davidson, Charles E

2013-08-26

We extend the probability model for 3-layer radiative transfer [Opt. Express 20, 10004 (2012)] to ideal gas conditions where a correlation exists between transmission and temperature of each of the 3 layers. The effect on the probability density function for the at-sensor radiances is surprisingly small, and thus the added complexity of addressing the correlation can be avoided. The small overall effect is due to (a) small perturbations by the correlation on variance population parameters and (b) cancellation of perturbation terms that appear with opposite signs in the model moment expressions.

Knock probability estimation through an in-cylinder temperature model with exogenous noise

Science.gov (United States)

Bares, P.; Selmanaj, D.; Guardiola, C.; Onder, C.

2018-01-01

This paper presents a new knock model which combines a deterministic knock model based on the in-cylinder temperature and an exogenous noise disturbing this temperature. The autoignition of the end-gas is modelled by an Arrhenius-like function and the knock probability is estimated by propagating a virtual error probability distribution. Results show that the random nature of knock can be explained by uncertainties at the in-cylinder temperature estimation. The model only has one parameter for calibration and thus can be easily adapted online. In order to reduce the measurement uncertainties associated with the air mass flow sensor, the trapped mass is derived from the in-cylinder pressure resonance, which improves the knock probability estimation and reduces the number of sensors needed for the model. A four stroke SI engine was used for model validation. By varying the intake temperature, the engine speed, the injected fuel mass, and the spark advance, specific tests were conducted, which furnished data with various knock intensities and probabilities. The new model is able to predict the knock probability within a sufficient range at various operating conditions. The trapped mass obtained by the acoustical model was compared in steady conditions by using a fuel balance and a lambda sensor and differences below 1 % were found.

An extended car-following model considering random safety distance with different probabilities

Science.gov (United States)

Wang, Jufeng; Sun, Fengxin; Cheng, Rongjun; Ge, Hongxia; Wei, Qi

2018-02-01

Because of the difference in vehicle type or driving skill, the driving strategy is not exactly the same. The driving speeds of the different vehicles may be different for the same headway. Since the optimal velocity function is just determined by the safety distance besides the maximum velocity and headway, an extended car-following model accounting for random safety distance with different probabilities is proposed in this paper. The linear stable condition for this extended traffic model is obtained by using linear stability theory. Numerical simulations are carried out to explore the complex phenomenon resulting from multiple safety distance in the optimal velocity function. The cases of multiple types of safety distances selected with different probabilities are presented. Numerical results show that the traffic flow with multiple safety distances with different probabilities will be more unstable than that with single type of safety distance, and will result in more stop-and-go phenomena.

Transitional Probabilities Are Prioritized over Stimulus/Pattern Probabilities in Auditory Deviance Detection: Memory Basis for Predictive Sound Processing.

Science.gov (United States)

Mittag, Maria; Takegata, Rika; Winkler, István

2016-09-14

Representations encoding the probabilities of auditory events do not directly support predictive processing. In contrast, information about the probability with which a given sound follows another (transitional probability) allows predictions of upcoming sounds. We tested whether behavioral and cortical auditory deviance detection (the latter indexed by the mismatch negativity event-related potential) relies on probabilities of sound patterns or on transitional probabilities. We presented healthy adult volunteers with three types of rare tone-triplets among frequent standard triplets of high-low-high (H-L-H) or L-H-L pitch structure: proximity deviant (H-H-H/L-L-L), reversal deviant (L-H-L/H-L-H), and first-tone deviant (L-L-H/H-H-L). If deviance detection was based on pattern probability, reversal and first-tone deviants should be detected with similar latency because both differ from the standard at the first pattern position. If deviance detection was based on transitional probabilities, then reversal deviants should be the most difficult to detect because, unlike the other two deviants, they contain no low-probability pitch transitions. The data clearly showed that both behavioral and cortical auditory deviance detection uses transitional probabilities. Thus, the memory traces underlying cortical deviance detection may provide a link between stimulus probability-based change/novelty detectors operating at lower levels of the auditory system and higher auditory cognitive functions that involve predictive processing. Our research presents the first definite evidence for the auditory system prioritizing transitional probabilities over probabilities of individual sensory events. Forming representations for transitional probabilities paves the way for predictions of upcoming sounds. Several recent theories suggest that predictive processing provides the general basis of human perception, including important auditory functions, such as auditory scene analysis. Our

Parametric Probability Distribution Functions for Axon Diameters of Corpus Callosum

Directory of Open Access Journals (Sweden)

Farshid eSepehrband

2016-05-01

Full Text Available Axon diameter is an important neuroanatomical characteristic of the nervous system that alters in the course of neurological disorders such as multiple sclerosis. Axon diameters vary, even within a fiber bundle, and are not normally distributed. An accurate distribution function is therefore beneficial, either to describe axon diameters that are obtained from a direct measurement technique (e.g., microscopy, or to infer them indirectly (e.g., using diffusion-weighted MRI. The gamma distribution is a common choice for this purpose (particularly for the inferential approach because it resembles the distribution profile of measured axon diameters which has been consistently shown to be non-negative and right-skewed. In this study we compared a wide range of parametric probability distribution functions against empirical data obtained from electron microscopy images. We observed that the gamma distribution fails to accurately describe the main characteristics of the axon diameter distribution, such as location and scale of the mode and the profile of distribution tails. We also found that the generalized extreme value distribution consistently fitted the measured distribution better than other distribution functions. This suggests that there may be distinct subpopulations of axons in the corpus callosum, each with their own distribution profiles. In addition, we observed that several other distributions outperformed the gamma distribution, yet had the same number of unknown parameters; these were the inverse Gaussian, log normal, log logistic and Birnbaum-Saunders distributions.

Estimation of the four-wave mixing noise probability-density function by the multicanonical Monte Carlo method.

Science.gov (United States)

Neokosmidis, Ioannis; Kamalakis, Thomas; Chipouras, Aristides; Sphicopoulos, Thomas

2005-01-01

The performance of high-powered wavelength-division multiplexed (WDM) optical networks can be severely degraded by four-wave-mixing- (FWM-) induced distortion. The multicanonical Monte Carlo method (MCMC) is used to calculate the probability-density function (PDF) of the decision variable of a receiver, limited by FWM noise. Compared with the conventional Monte Carlo method previously used to estimate this PDF, the MCMC method is much faster and can accurately estimate smaller error probabilities. The method takes into account the correlation between the components of the FWM noise, unlike the Gaussian model, which is shown not to provide accurate results.

Quadratic Functionals with General Boundary Conditions

International Nuclear Information System (INIS)

Dosla, Z.; Dosly, O.

1997-01-01

The purpose of this paper is to give the Reid 'Roundabout Theorem' for quadratic functionals with general boundary conditions. In particular, we describe the so-called coupled point and regularity condition introduced in terms of Riccati equation solutions

Charged-particle thermonuclear reaction rates: II. Tables and graphs of reaction rates and probability density functions

International Nuclear Information System (INIS)

Iliadis, C.; Longland, R.; Champagne, A.E.; Coc, A.; Fitzgerald, R.

2010-01-01

Numerical values of charged-particle thermonuclear reaction rates for nuclei in the A=14 to 40 region are tabulated. The results are obtained using a method, based on Monte Carlo techniques, that has been described in the preceding paper of this issue (Paper I). We present a low rate, median rate and high rate which correspond to the 0.16, 0.50 and 0.84 quantiles, respectively, of the cumulative reaction rate distribution. The meaning of these quantities is in general different from the commonly reported, but statistically meaningless expressions, 'lower limit', 'nominal value' and 'upper limit' of the total reaction rate. In addition, we approximate the Monte Carlo probability density function of the total reaction rate by a lognormal distribution and tabulate the lognormal parameters μ and σ at each temperature. We also provide a quantitative measure (Anderson-Darling test statistic) for the reliability of the lognormal approximation. The user can implement the approximate lognormal reaction rate probability density functions directly in a stellar model code for studies of stellar energy generation and nucleosynthesis. For each reaction, the Monte Carlo reaction rate probability density functions, together with their lognormal approximations, are displayed graphically for selected temperatures in order to provide a visual impression. Our new reaction rates are appropriate for bare nuclei in the laboratory. The nuclear physics input used to derive our reaction rates is presented in the subsequent paper of this issue (Paper III). In the fourth paper of this issue (Paper IV) we compare our new reaction rates to previous results.

Solving probability reasoning based on DNA strand displacement and probability modules.

Science.gov (United States)

Zhang, Qiang; Wang, Xiaobiao; Wang, Xiaojun; Zhou, Changjun

2017-12-01

In computation biology, DNA strand displacement technology is used to simulate the computation process and has shown strong computing ability. Most researchers use it to solve logic problems, but it is only rarely used in probabilistic reasoning. To process probabilistic reasoning, a conditional probability derivation model and total probability model based on DNA strand displacement were established in this paper. The models were assessed through the game "read your mind." It has been shown to enable the application of probabilistic reasoning in genetic diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Probability of inadvertent operation of electrical components in harsh environments

International Nuclear Information System (INIS)

Knoll, A.

1989-01-01

Harsh environment, which means humidity and high temperature, may and will affect unsealed electrical components by causing leakage ground currents in ungrounded direct current systems. The concern in a nuclear power plant is that such harsh environment conditions could cause inadvertent operation of normally deenergized components, which may have a safety-related isolation function. Harsh environment is a common cause failure, and one way to approach the problem is to assume that all the unsealed electrical components will simultaneously and inadvertently energize as a result of the environmental common cause failure. This assumption is unrealistically conservative. Test results indicated that insulating resistences of any terminal block in harsh environments have a random distribution in the range of 1 to 270 kΩ, with a mean value ∼59 kΩ. The objective of this paper is to evaluate a realistic conditional failure probability for inadvertent operation of electrical components in harsh environments. This value will be used thereafter in probabilistic safety evaluations of harsh environment events and will replace both the overconservative common cause probability of 1 and the random failure probability used for mild environments

Upgrading Probability via Fractions of Events

Directory of Open Access Journals (Sweden)

Frič Roman

2016-08-01

Full Text Available The influence of “Grundbegriffe” by A. N. Kolmogorov (published in 1933 on education in the area of probability and its impact on research in stochastics cannot be overestimated. We would like to point out three aspects of the classical probability theory “calling for” an upgrade: (i classical random events are black-and-white (Boolean; (ii classical random variables do not model quantum phenomena; (iii basic maps (probability measures and observables { dual maps to random variables have very different “mathematical nature”. Accordingly, we propose an upgraded probability theory based on Łukasiewicz operations (multivalued logic on events, elementary category theory, and covering the classical probability theory as a special case. The upgrade can be compared to replacing calculations with integers by calculations with rational (and real numbers. Namely, to avoid the three objections, we embed the classical (Boolean random events (represented by the f0; 1g-valued indicator functions of sets into upgraded random events (represented by measurable {0; 1}-valued functions, the minimal domain of probability containing “fractions” of classical random events, and we upgrade the notions of probability measure and random variable.

Probability theory a foundational course

CERN Document Server

Pakshirajan, R P

2013-01-01

This book shares the dictum of J. L. Doob in treating Probability Theory as a branch of Measure Theory and establishes this relation early. Probability measures in product spaces are introduced right at the start by way of laying the ground work to later claim the existence of stochastic processes with prescribed finite dimensional distributions. Other topics analysed in the book include supports of probability measures, zero-one laws in product measure spaces, Erdos-Kac invariance principle, functional central limit theorem and functional law of the iterated logarithm for independent variables, Skorohod embedding, and the use of analytic functions of a complex variable in the study of geometric ergodicity in Markov chains. This book is offered as a text book for students pursuing graduate programs in Mathematics and or Statistics. The book aims to help the teacher present the theory with ease, and to help the student sustain his interest and joy in learning the subject.

Experiencing El Niño conditions during early life reduces recruiting probabilities but not adult survival

Science.gov (United States)

Rodríguez, Cristina; Drummond, Hugh

2018-01-01

In wild long-lived animals, analysis of impacts of stressful natal conditions on adult performance has rarely embraced the entire age span, and the possibility that costs are expressed late in life has seldom been examined. Using 26 years of data from 8541 fledglings and 1310 adults of the blue-footed booby (Sula nebouxii), a marine bird that can live up to 23 years, we tested whether experiencing the warm waters and food scarcity associated with El Niño in the natal year reduces recruitment or survival over the adult lifetime. Warm water in the natal year reduced the probability of recruiting; each additional degree (°C) of water temperature meant a reduction of roughly 50% in fledglings' probability of returning to the natal colony as breeders. Warm water in the current year impacted adult survival, with greater effect at the oldest ages than during early adulthood. However, warm water in the natal year did not affect survival at any age over the adult lifespan. A previous study showed that early recruitment and widely spaced breeding allow boobies that experience warm waters in the natal year to achieve normal fledgling production over the first 10 years; our results now show that this reproductive effort incurs no survival penalty, not even late in life. This pattern is additional evidence of buffering against stressful natal conditions via life-history adjustments. PMID:29410788

Hand-related physical function in rheumatic hand conditions

DEFF Research Database (Denmark)

Klokker, Louise; Terwee, Caroline B; Wæhrens, Eva Ejlersen

2016-01-01

as well as those items from the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) item bank that are relevant to patients with rheumatic hand conditions. Selection will be based on consensus among reviewers. Content validity of selected items will be established......INTRODUCTION: There is no consensus about what constitutes the most appropriate patient-reported outcome measurement (PROM) instrument for measuring physical function in patients with rheumatic hand conditions. Existing instruments lack psychometric testing and vary in feasibility...... and their psychometric qualities. We aim to develop a PROM instrument to assess hand-related physical function in rheumatic hand conditions. METHODS AND ANALYSIS: We will perform a systematic search to identify existing PROMs to rheumatic hand conditions, and select items relevant for hand-related physical function...

Hand-related physical function in rheumatic hand conditions

DEFF Research Database (Denmark)

Klokker, Louise; Terwee, Caroline; Wæhrens, Eva Elisabet Ejlersen

2016-01-01

INTRODUCTION: There is no consensus about what constitutes the most appropriate patient-reported outcome measurement (PROM) instrument for measuring physical function in patients with rheumatic hand conditions. Existing instruments lack psychometric testing and vary in feasibility...... and their psychometric qualities. We aim to develop a PROM instrument to assess hand-related physical function in rheumatic hand conditions. METHODS AND ANALYSIS: We will perform a systematic search to identify existing PROMs to rheumatic hand conditions, and select items relevant for hand-related physical function...... as well as those items from the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) item bank that are relevant to patients with rheumatic hand conditions. Selection will be based on consensus among reviewers. Content validity of selected items will be established...

A research on the importance function used in the calculation of the fracture probability through the optimum method

International Nuclear Information System (INIS)

Zegong, Zhou; Changhong, Liu

1995-01-01

On the basis of the research into original distribution function as the importance function after shifting an appropriate distance, this paper takes the variation of similar ratio of the original function to the importance function as the objective function, the optimum shifting distance obtained by use of an optimization method. The optimum importance function resulting from the optimization method can ensure that the number of Monte Carlo simulations is decreased and at the same time the good estimates of the yearly failure probabilities are obtained

Probability theory and mathematical statistics for engineers

CERN Document Server

Pugachev, V S

1984-01-01

Probability Theory and Mathematical Statistics for Engineers focuses on the concepts of probability theory and mathematical statistics for finite-dimensional random variables.The publication first underscores the probabilities of events, random variables, and numerical characteristics of random variables. Discussions focus on canonical expansions of random vectors, second-order moments of random vectors, generalization of the density concept, entropy of a distribution, direct evaluation of probabilities, and conditional probabilities. The text then examines projections of random vector

A basic course in probability theory

CERN Document Server

Bhattacharya, Rabi

2016-01-01

This text develops the necessary background in probability theory underlying diverse treatments of stochastic processes and their wide-ranging applications. In this second edition, the text has been reorganized for didactic purposes, new exercises have been added and basic theory has been expanded. General Markov dependent sequences and their convergence to equilibrium is the subject of an entirely new chapter. The introduction of conditional expectation and conditional probability very early in the text maintains the pedagogic innovation of the first edition; conditional expectation is illustrated in detail in the context of an expanded treatment of martingales, the Markov property, and the strong Markov property. Weak convergence of probabilities on metric spaces and Brownian motion are two topics to highlight. A selection of large deviation and/or concentration inequalities ranging from those of Chebyshev, Cramer–Chernoff, Bahadur–Rao, to Hoeffding have been added, with illustrative comparisons of thei...

A probability space for quantum models

Science.gov (United States)

Lemmens, L. F.

2017-06-01

A probability space contains a set of outcomes, a collection of events formed by subsets of the set of outcomes and probabilities defined for all events. A reformulation in terms of propositions allows to use the maximum entropy method to assign the probabilities taking some constraints into account. The construction of a probability space for quantum models is determined by the choice of propositions, choosing the constraints and making the probability assignment by the maximum entropy method. This approach shows, how typical quantum distributions such as Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein are partly related with well-known classical distributions. The relation between the conditional probability density, given some averages as constraints and the appropriate ensemble is elucidated.

Probability Issues in without Replacement Sampling

Science.gov (United States)

Joarder, A. H.; Al-Sabah, W. S.

2007-01-01

Sampling without replacement is an important aspect in teaching conditional probabilities in elementary statistics courses. Different methods proposed in different texts for calculating probabilities of events in this context are reviewed and their relative merits and limitations in applications are pinpointed. An alternative representation of…

Probability density function modeling of scalar mixing from concentrated sources in turbulent channel flow

OpenAIRE

Bakosi, J.; Franzese, P.; Boybeyi, Z.

2010-01-01

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth & Pope with Durbin's method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous ...

Introduction to probability theory with contemporary applications

CERN Document Server

Helms, Lester L

2010-01-01

This introduction to probability theory transforms a highly abstract subject into a series of coherent concepts. Its extensive discussions and clear examples, written in plain language, expose students to the rules and methods of probability. Suitable for an introductory probability course, this volume requires abstract and conceptual thinking skills and a background in calculus.Topics include classical probability, set theory, axioms, probability functions, random and independent random variables, expected values, and covariance and correlations. Additional subjects include stochastic process

Collision Probability Analysis

DEFF Research Database (Denmark)

Hansen, Peter Friis; Pedersen, Preben Terndrup

1998-01-01

It is the purpose of this report to apply a rational model for prediction of ship-ship collision probabilities as function of the ship and the crew characteristics and the navigational environment for MS Dextra sailing on a route between Cadiz and the Canary Islands.The most important ship and crew...... characteristics are: ship speed, ship manoeuvrability, the layout of the navigational bridge, the radar system, the number and the training of navigators, the presence of a look out etc. The main parameters affecting the navigational environment are ship traffic density, probability distributions of wind speeds...... probability, i.e. a study of the navigator's role in resolving critical situations, a causation factor is derived as a second step.The report documents the first step in a probabilistic collision damage analysis. Future work will inlcude calculation of energy released for crushing of structures giving...

Optimization of functionalization conditions for protein analysis by AFM

Energy Technology Data Exchange (ETDEWEB)

Arroyo-Hernández, María, E-mail: maria.arroyo@ctb.upm.es [Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid (Spain); Departamento de Ciencia de Materiales, ETSI Caminos, Canales y Puertos, Universidad Politécnica de Madrid, 28040 Madrid (Spain); Daza, Rafael; Pérez-Rigueiro, Jose; Elices, Manuel; Nieto-Márquez, Jorge; Guinea, Gustavo V. [Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid (Spain); Departamento de Ciencia de Materiales, ETSI Caminos, Canales y Puertos, Universidad Politécnica de Madrid, 28040 Madrid (Spain)

2014-10-30

Highlights: • Highest fluorescence is obtained for central conditions. • Largest primary amine contribution is obtained for central conditions. • RMS roughness is smaller than 1 nm for all functional films. • Selected deposition conditions lead to proper RMS and functionality values. • LDH proteins adsorbed on AVS-films were observed by AFM. - Abstract: Activated vapor silanization (AVS) is used to functionalize silicon surfaces through deposition of amine-containing thin films. AVS combines vapor silanization and chemical vapor deposition techniques and allows the properties of the functionalized layers (thickness, amine concentration and topography) to be controlled by tuning the deposition conditions. An accurate characterization is performed to correlate the deposition conditions and functional-film properties. In particular, it is shown that smooth surfaces with a sufficient surface density of amine groups may be obtained with this technique. These surfaces are suitable for the study of proteins with atomic force microscopy.

Recursive recovery of Markov transition probabilities from boundary value data

Energy Technology Data Exchange (ETDEWEB)

Patch, Sarah Kathyrn [Univ. of California, Berkeley, CA (United States)

1994-04-01

In an effort to mathematically describe the anisotropic diffusion of infrared radiation in biological tissue Gruenbaum posed an anisotropic diffusion boundary value problem in 1989. In order to accommodate anisotropy, he discretized the temporal as well as the spatial domain. The probabilistic interpretation of the diffusion equation is retained; radiation is assumed to travel according to a random walk (of sorts). In this random walk the probabilities with which photons change direction depend upon their previous as well as present location. The forward problem gives boundary value data as a function of the Markov transition probabilities. The inverse problem requires finding the transition probabilities from boundary value data. Problems in the plane are studied carefully in this thesis. Consistency conditions amongst the data are derived. These conditions have two effects: they prohibit inversion of the forward map but permit smoothing of noisy data. Next, a recursive algorithm which yields a family of solutions to the inverse problem is detailed. This algorithm takes advantage of all independent data and generates a system of highly nonlinear algebraic equations. Pluecker-Grassmann relations are instrumental in simplifying the equations. The algorithm is used to solve the 4 x 4 problem. Finally, the smallest nontrivial problem in three dimensions, the 2 x 2 x 2 problem, is solved.

Probability Density Function Method for Observing Reconstructed Attractor Structure

Institute of Scientific and Technical Information of China (English)

陆宏伟; 陈亚珠; 卫青

2004-01-01

Probability density function (PDF) method is proposed for analysing the structure of the reconstructed attractor in computing the correlation dimensions of RR intervals of ten normal old men. PDF contains important information about the spatial distribution of the phase points in the reconstructed attractor. To the best of our knowledge, it is the first time that the PDF method is put forward for the analysis of the reconstructed attractor structure. Numerical simulations demonstrate that the cardiac systems of healthy old men are about 6 - 6.5 dimensional complex dynamical systems. It is found that PDF is not symmetrically distributed when time delay is small, while PDF satisfies Gaussian distribution when time delay is big enough. A cluster effect mechanism is presented to explain this phenomenon. By studying the shape of PDFs, that the roles played by time delay are more important than embedding dimension in the reconstruction is clearly indicated. Results have demonstrated that the PDF method represents a promising numerical approach for the observation of the reconstructed attractor structure and may provide more information and new diagnostic potential of the analyzed cardiac system.

Elements of probability and statistics an introduction to probability with De Finetti’s approach and to Bayesian statistics

CERN Document Server

Biagini, Francesca

2016-01-01

This book provides an introduction to elementary probability and to Bayesian statistics using de Finetti's subjectivist approach. One of the features of this approach is that it does not require the introduction of sample space – a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate – but introduces as fundamental the concept of random numbers directly related to their interpretation in applications. Events become a particular case of random numbers and probability a particular case of expectation when it is applied to events. The subjective evaluation of expectation and of conditional expectation is based on an economic choice of an acceptable bet or penalty. The properties of expectation and conditional expectation are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics.

Assumed Probability Density Functions for Shallow and Deep Convection

Directory of Open Access Journals (Sweden)

Steven K Krueger

2010-10-01

Full Text Available The assumed joint probability density function (PDF between vertical velocity and conserved temperature and total water scalars has been suggested to be a relatively computationally inexpensive and unified subgrid-scale (SGS parameterization for boundary layer clouds and turbulent moments. This paper analyzes the performance of five families of PDFs using large-eddy simulations of deep convection, shallow convection, and a transition from stratocumulus to trade wind cumulus. Three of the PDF families are based on the double Gaussian form and the remaining two are the single Gaussian and a Double Delta Function (analogous to a mass flux model. The assumed PDF method is tested for grid sizes as small as 0.4 km to as large as 204.8 km. In addition, studies are performed for PDF sensitivity to errors in the input moments and for how well the PDFs diagnose some higher-order moments. In general, the double Gaussian PDFs more accurately represent SGS cloud structure and turbulence moments in the boundary layer compared to the single Gaussian and Double Delta Function PDFs for the range of grid sizes tested. This is especially true for small SGS cloud fractions. While the most complex PDF, Lewellen-Yoh, better represents shallow convective cloud properties (cloud fraction and liquid water mixing ratio compared to the less complex Analytic Double Gaussian 1 PDF, there appears to be no advantage in implementing Lewellen-Yoh for deep convection. However, the Analytic Double Gaussian 1 PDF better represents the liquid water flux, is less sensitive to errors in the input moments, and diagnoses higher order moments more accurately. Between the Lewellen-Yoh and Analytic Double Gaussian 1 PDFs, it appears that neither family is distinctly better at representing cloudy layers. However, due to the reduced computational cost and fairly robust results, it appears that the Analytic Double Gaussian 1 PDF could be an ideal family for SGS cloud and turbulence

Nuclear data uncertainties: I, Basic concepts of probability

Energy Technology Data Exchange (ETDEWEB)

Smith, D.L.

1988-12-01

Some basic concepts of probability theory are presented from a nuclear-data perspective, in order to provide a foundation for thorough understanding of the role of uncertainties in nuclear data research. Topics included in this report are: events, event spaces, calculus of events, randomness, random variables, random-variable distributions, intuitive and axiomatic probability, calculus of probability, conditional probability and independence, probability distributions, binomial and multinomial probability, Poisson and interval probability, normal probability, the relationships existing between these probability laws, and Bayes' theorem. This treatment emphasizes the practical application of basic mathematical concepts to nuclear data research, and it includes numerous simple examples. 34 refs.

Nuclear data uncertainties: I, Basic concepts of probability

International Nuclear Information System (INIS)

Smith, D.L.

1988-12-01

Some basic concepts of probability theory are presented from a nuclear-data perspective, in order to provide a foundation for thorough understanding of the role of uncertainties in nuclear data research. Topics included in this report are: events, event spaces, calculus of events, randomness, random variables, random-variable distributions, intuitive and axiomatic probability, calculus of probability, conditional probability and independence, probability distributions, binomial and multinomial probability, Poisson and interval probability, normal probability, the relationships existing between these probability laws, and Bayes' theorem. This treatment emphasizes the practical application of basic mathematical concepts to nuclear data research, and it includes numerous simple examples. 34 refs

Internal Medicine residents use heuristics to estimate disease probability.

Science.gov (United States)

Phang, Sen Han; Ravani, Pietro; Schaefer, Jeffrey; Wright, Bruce; McLaughlin, Kevin

2015-01-01

Training in Bayesian reasoning may have limited impact on accuracy of probability estimates. In this study, our goal was to explore whether residents previously exposed to Bayesian reasoning use heuristics rather than Bayesian reasoning to estimate disease probabilities. We predicted that if residents use heuristics then post-test probability estimates would be increased by non-discriminating clinical features or a high anchor for a target condition. We randomized 55 Internal Medicine residents to different versions of four clinical vignettes and asked them to estimate probabilities of target conditions. We manipulated the clinical data for each vignette to be consistent with either 1) using a representative heuristic, by adding non-discriminating prototypical clinical features of the target condition, or 2) using anchoring with adjustment heuristic, by providing a high or low anchor for the target condition. When presented with additional non-discriminating data the odds of diagnosing the target condition were increased (odds ratio (OR) 2.83, 95% confidence interval [1.30, 6.15], p = 0.009). Similarly, the odds of diagnosing the target condition were increased when a high anchor preceded the vignette (OR 2.04, [1.09, 3.81], p = 0.025). Our findings suggest that despite previous exposure to the use of Bayesian reasoning, residents use heuristics, such as the representative heuristic and anchoring with adjustment, to estimate probabilities. Potential reasons for attribute substitution include the relative cognitive ease of heuristics vs. Bayesian reasoning or perhaps residents in their clinical practice use gist traces rather than precise probability estimates when diagnosing.

On the shake-off probability for atomic systems

Energy Technology Data Exchange (ETDEWEB)

Santos, A.C.F., E-mail: toniufrj@gmail.com [Instituto de Física, Universidade Federal do Rio de Janeiro, P.O. Box 68528, 21941-972 Rio de Janeiro, RJ (Brazil); Almeida, D.P. [Departamento de Física, Universidade Federal de Santa Catarina, 88040-900 Florianópolis (Brazil)

2016-07-15

Highlights: • The scope is to find the relationship among SO probabilities, Z and electron density. • A scaling law is suggested, allowing us to find the SO probabilities for atoms. • SO probabilities have been scaled as a function of target Z and polarizability. - Abstract: The main scope in this work has been upon the relationship between shake-off probabilities, target atomic number and electron density. By comparing the saturation values of measured double-to-single photoionization ratios from the literature, a simple scaling law has been found, which allows us to predict the shake-off probabilities for several elements up to Z = 54 within a factor 2. The electron shake-off probabilities accompanying valence shell photoionization have been scaled as a function of the target atomic number, Z, and polarizability, α. This behavior is in qualitative agreement with the experimental results.

Probability densities and Lévy densities

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler

For positive Lévy processes (i.e. subordinators) formulae are derived that express the probability density or the distribution function in terms of power series in time t. The applicability of the results to finance and to turbulence is briefly indicated.......For positive Lévy processes (i.e. subordinators) formulae are derived that express the probability density or the distribution function in terms of power series in time t. The applicability of the results to finance and to turbulence is briefly indicated....

Application of tests of goodness of fit in determining the probability density function for spacing of steel sets in tunnel support system

Directory of Open Access Journals (Sweden)

Farnoosh Basaligheh

2015-12-01

Full Text Available One of the conventional methods for temporary support of tunnels is to use steel sets with shotcrete. The nature of a temporary support system demands a quick installation of its structures. As a result, the spacing between steel sets is not a fixed amount and it can be considered as a random variable. Hence, in the reliability analysis of these types of structures, the selection of an appropriate probability distribution function of spacing of steel sets is essential. In the present paper, the distances between steel sets are collected from an under-construction tunnel and the collected data is used to suggest a proper Probability Distribution Function (PDF for the spacing of steel sets. The tunnel has two different excavation sections. In this regard, different distribution functions were investigated and three common tests of goodness of fit were used for evaluation of each function for each excavation section. Results from all three methods indicate that the Wakeby distribution function can be suggested as the proper PDF for spacing between the steel sets. It is also noted that, although the probability distribution function for two different tunnel sections is the same, the parameters of PDF for the individual sections are different from each other.

Paraconsistent Probabilities: Consistency, Contradictions and Bayes’ Theorem

Directory of Open Access Journals (Sweden)

Juliana Bueno-Soler

2016-09-01

Full Text Available This paper represents the first steps towards constructing a paraconsistent theory of probability based on the Logics of Formal Inconsistency (LFIs. We show that LFIs encode very naturally an extension of the notion of probability able to express sophisticated probabilistic reasoning under contradictions employing appropriate notions of conditional probability and paraconsistent updating, via a version of Bayes’ theorem for conditionalization. We argue that the dissimilarity between the notions of inconsistency and contradiction, one of the pillars of LFIs, plays a central role in our extended notion of probability. Some critical historical and conceptual points about probability theory are also reviewed.

Fusing probability density function into Dempster-Shafer theory of evidence for the evaluation of water treatment plant.

Science.gov (United States)

Chowdhury, Shakhawat

2013-05-01

The evaluation of the status of a municipal drinking water treatment plant (WTP) is important. The evaluation depends on several factors, including, human health risks from disinfection by-products (R), disinfection performance (D), and cost (C) of water production and distribution. The Dempster-Shafer theory (DST) of evidence can combine the individual status with respect to R, D, and C to generate a new indicator, from which the overall status of a WTP can be evaluated. In the DST, the ranges of different factors affecting the overall status are divided into several segments. The basic probability assignments (BPA) for each segment of these factors are provided by multiple experts, which are then combined to obtain the overall status. In assigning the BPA, the experts use their individual judgments, which can impart subjective biases in the overall evaluation. In this research, an approach has been introduced to avoid the assignment of subjective BPA. The factors contributing to the overall status were characterized using the probability density functions (PDF). The cumulative probabilities for different segments of these factors were determined from the cumulative density function, which were then assigned as the BPA for these factors. A case study is presented to demonstrate the application of PDF in DST to evaluate a WTP, leading to the selection of the required level of upgradation for the WTP.

Characterizing the Lyα forest flux probability distribution function using Legendre polynomials

Energy Technology Data Exchange (ETDEWEB)

Cieplak, Agnieszka M.; Slosar, Anže, E-mail: acieplak@bnl.gov, E-mail: anze@bnl.gov [Brookhaven National Laboratory, Bldg 510, Upton, NY, 11973 (United States)

2017-10-01

The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n -th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisation over mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. We find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.

Characterizing the Lyα forest flux probability distribution function using Legendre polynomials

Science.gov (United States)

Cieplak, Agnieszka M.; Slosar, Anže

2017-10-01

The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n-th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisation over mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. We find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.

Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

Science.gov (United States)

Liu, Xian; Engel, Charles C

2012-12-20

Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.

Human Error Probability Assessment During Maintenance Activities of Marine Systems

Directory of Open Access Journals (Sweden)

Rabiul Islam

2018-03-01

Full Text Available Background: Maintenance operations on-board ships are highly demanding. Maintenance operations are intensive activities requiring high man–machine interactions in challenging and evolving conditions. The evolving conditions are weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress. For example, extreme weather condition affects seafarers' performance, increasing the chances of error, and, consequently, can cause injuries or fatalities to personnel. An effective human error probability model is required to better manage maintenance on-board ships. The developed model would assist in developing and maintaining effective risk management protocols. Thus, the objective of this study is to develop a human error probability model considering various internal and external factors affecting seafarers' performance. Methods: The human error probability model is developed using probability theory applied to Bayesian network. The model is tested using the data received through the developed questionnaire survey of >200 experienced seafarers with >5 years of experience. The model developed in this study is used to find out the reliability of human performance on particular maintenance activities. Results: The developed methodology is tested on the maintenance of marine engine's cooling water pump for engine department and anchor windlass for deck department. In the considered case studies, human error probabilities are estimated in various scenarios and the results are compared between the scenarios and the different seafarer categories. The results of the case studies for both departments are also compared. Conclusion: The developed model is effective in assessing human error probabilities. These probabilities would get dynamically updated as and when new information is available on changes in either internal (i.e., training, experience, and fatigue or external (i.e., environmental and operational conditions

The probability of containment failure by direct containment heating in Zion

International Nuclear Information System (INIS)

Pilch, M.M.; Yan, H.; Theofanous, T.G.

1994-12-01

This report is the first step in the resolution of the Direct Containment Heating (DCH) issue for the Zion Nuclear Power Plant using the Risk Oriented Accident Analysis Methodology (ROAAM). This report includes the definition of a probabilistic framework that decomposes the DCH problem into three probability density functions that reflect the most uncertain initial conditions (UO 2 mass, zirconium oxidation fraction, and steel mass). Uncertainties in the initial conditions are significant, but our quantification approach is based on establishing reasonable bounds that are not unnecessarily conservative. To this end, we also make use of the ROAAM ideas of enveloping scenarios and ''splintering.'' Two causal relations (CRs) are used in this framework: CR1 is a model that calculates the peak pressure in the containment as a function of the initial conditions, and CR2 is a model that returns the frequency of containment failure as a function of pressure within the containment. Uncertainty in CR1 is accounted for by the use of two independently developed phenomenological models, the Convection Limited Containment Heating (CLCH) model and the Two-Cell Equilibrium (TCE) model, and by probabilistically distributing the key parameter in both, which is the ratio of the melt entrainment time to the system blowdown time constant. The two phenomenological models have been compared with an extensive database including recent integral simulations at two different physical scales. The containment load distributions do not intersect the containment strength (fragility) curve in any significant way, resulting in containment failure probabilities less than 10 -3 for all scenarios considered. Sensitivity analyses did not show any areas of large sensitivity

Calculation of transition probabilities using the multiconfiguration Dirac-Fock method

International Nuclear Information System (INIS)

Kim, Yong Ki; Desclaux, Jean Paul; Indelicato, Paul

1998-01-01

The performance of the multiconfiguration Dirac-Fock (MCDF) method in calculating transition probabilities of atoms is reviewed. In general, the MCDF wave functions will lead to transition probabilities accurate to ∼ 10% or better for strong, electric-dipole allowed transitions for small atoms. However, it is more difficult to get reliable transition probabilities for weak transitions. Also, some MCDF wave functions for a specific J quantum number may not reduce to the appropriate L and S quantum numbers in the nonrelativistic limit. Transition probabilities calculated from such MCDF wave functions for nonrelativistically forbidden transitions are unreliable. Remedies for such cases are discussed

A prototype method for diagnosing high ice water content probability using satellite imager data

Science.gov (United States)

Yost, Christopher R.; Bedka, Kristopher M.; Minnis, Patrick; Nguyen, Louis; Strapp, J. Walter; Palikonda, Rabindra; Khlopenkov, Konstantin; Spangenberg, Douglas; Smith, William L., Jr.; Protat, Alain; Delanoe, Julien

2018-03-01

Recent studies have found that ingestion of high mass concentrations of ice particles in regions of deep convective storms, with radar reflectivity considered safe for aircraft penetration, can adversely impact aircraft engine performance. Previous aviation industry studies have used the term high ice water content (HIWC) to define such conditions. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO) satellite imager data coupled with in situ total water content (TWC) observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: (1) the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, (2) tropopause-relative infrared brightness temperature, and (3) daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite-aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC ≥ 0.5 g m-3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution of the GEO data.

Collapse susceptibility mapping in karstified gypsum terrain (Sivas basin - Turkey) by conditional probability, logistic regression, artificial neural network models

Science.gov (United States)

Yilmaz, Isik; Keskin, Inan; Marschalko, Marian; Bednarik, Martin

2010-05-01

This study compares the GIS based collapse susceptibility mapping methods such as; conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) applied in gypsum rock masses in Sivas basin (Turkey). Digital Elevation Model (DEM) was first constructed using GIS software. Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index- TWI, stream power index- SPI, Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from CP, LR and ANN models, and they were then compared by means of their validations. Area Under Curve (AUC) values obtained from all three methodologies showed that the map obtained from ANN model looks like more accurate than the other models, and the results also showed that the artificial neural networks is a usefull tool in preparation of collapse susceptibility map and highly compatible with GIS operating features. Key words: Collapse; doline; susceptibility map; gypsum; GIS; conditional probability; logistic regression; artificial neural networks.

Probabilities on Streams and Reflexive Games

Directory of Open Access Journals (Sweden)

Andrew Schumann

2014-01-01

Full Text Available Probability measures on streams (e.g. on hypernumbers and p-adic numbers have been defined. It was shown that these probabilities can be used for simulations of reflexive games. In particular, it can be proved that Aumann's agreement theorem does not hold for these probabilities. Instead of this theorem, there is a statement that is called the reflexion disagreement theorem. Based on this theorem, probabilistic and knowledge conditions can be defined for reflexive games at various reflexion levels up to the infinite level. (original abstract

[Effects of prefrontal ablations on the reaction of the active choice of feeder under different probability and value of the reinforcement on dog].

Science.gov (United States)

Preobrazhenskaia, L A; Ioffe, M E; Mats, V N

2004-01-01

The role of the prefrontal cortex was investigated on the reaction of the active choice of the two feeders under changes value and probability reinforcement. The experiments were performed on 2 dogs with prefrontal ablation (g. proreus). Before the lesions the dogs were taught to receive food in two different feeders to conditioned stimuli with equally probable alimentary reinforcement. After ablation in the inter-trial intervals the dogs were running from the one feeder to another. In the answer to conditioned stimuli for many times the dogs choose the same feeder. The disturbance of the behavior after some times completely restored. In the experiments with competition of probability events and values of reinforcement the dogs chose the feeder with low-probability but better quality of reinforcement. In the experiments with equal value but different probability the intact dogs chose the feeder with higher probability. In our experiments the dogs with prefrontal lesions chose the each feeder equiprobably. Thus in condition of free behavior one of different functions of the prefrontal cortex is the reactions choose with more probability of reinforcement.

Pure state condition for the semi-classical Wigner function

International Nuclear Information System (INIS)

Ozorio de Almeida, A.M.

1982-01-01

The Wigner function W(p,q) is a symmetrized Fourier transform of the density matrix e(q 1 ,q 2 ), representing quantum-mechanical states or their statistical mixture in phase space. Identification of these two alternatives in the case of density matrices depends on the projection identity e 2 = e; its Wigner correspondence is the pure state condition. This criterion is applied to the Wigner functions botained from standard semiclassical wave functions, determining as pure states those whose classical invariant tori satisfy the generalized Bohr-Sommerfeld conditions. Superpositions of eigenstates are then examined and it is found that the Wigner function corresponding to Gaussian random wave functions are smoothed out in the manner of mixedstate Wigner functions. Attention is also given to the pure-state condition in the case where an angular coordinate is used. (orig.)

Uncertainty of Hydrological Drought Characteristics with Copula Functions and Probability Distributions: A Case Study of Weihe River, China

Directory of Open Access Journals (Sweden)

Panpan Zhao

2017-05-01

Full Text Available This study investigates the sensitivity and uncertainty of hydrological droughts frequencies and severity in the Weihe Basin, China during 1960–2012, by using six commonly used univariate probability distributions and three Archimedean copulas to fit the marginal and joint distributions of drought characteristics. The Anderson-Darling method is used for testing the goodness-of-fit of the univariate model, and the Akaike information criterion (AIC is applied to select the best distribution and copula functions. The results demonstrate that there is a very strong correlation between drought duration and drought severity in three stations. The drought return period varies depending on the selected marginal distributions and copula functions and, with an increase of the return period, the differences become larger. In addition, the estimated return periods (both co-occurrence and joint from the best-fitted copulas are the closet to those from empirical distribution. Therefore, it is critical to select the appropriate marginal distribution and copula function to model the hydrological drought frequency and severity. The results of this study can not only help drought investigation to select a suitable probability distribution and copulas function, but are also useful for regional water resource management. However, a few limitations remain in this study, such as the assumption of stationary of runoff series.

On the discretization of probability density functions and the ...

Indian Academy of Sciences (India)

important for most applications or theoretical problems of interest. In statistics ... In probability theory, statistics, statistical mechanics, communication theory, and other .... (1) by taking advantage of SMVT as a general mathematical approach.

An evaluation method for tornado missile strike probability with stochastic correction

Energy Technology Data Exchange (ETDEWEB)

Eguchi, Yuzuru; Murakami, Takahiro; Hirakuchi, Hiromaru; Sugimoto, Soichiro; Hattori, Yasuo [Nuclear Risk Research Center (External Natural Event Research Team), Central Research Institute of Electric Power Industry, Abiko (Japan)

2017-03-15

An efficient evaluation method for the probability of a tornado missile strike without using the Monte Carlo method is proposed in this paper. A major part of the proposed probability evaluation is based on numerical results computed using an in-house code, Tornado-borne missile analysis code, which enables us to evaluate the liftoff and flight behaviors of unconstrained objects on the ground driven by a tornado. Using the Tornado-borne missile analysis code, we can obtain a stochastic correlation between local wind speed and flight distance of each object, and this stochastic correlation is used to evaluate the conditional strike probability, QV(r), of a missile located at position r, where the local wind speed is V. In contrast, the annual exceedance probability of local wind speed, which can be computed using a tornado hazard analysis code, is used to derive the probability density function, p(V). Then, we finally obtain the annual probability of tornado missile strike on a structure with the convolutional integration of product of QV(r) and p(V) over V. The evaluation method is applied to a simple problem to qualitatively confirm the validity, and to quantitatively verify the results for two extreme cases in which an object is located just in the vicinity of or far away from the structure.

An evaluation method for tornado missile strike probability with stochastic correction

International Nuclear Information System (INIS)

Eguchi, Yuzuru; Murakami, Takahiro; Hirakuchi, Hiromaru; Sugimoto, Soichiro; Hattori, Yasuo

2017-01-01

An efficient evaluation method for the probability of a tornado missile strike without using the Monte Carlo method is proposed in this paper. A major part of the proposed probability evaluation is based on numerical results computed using an in-house code, Tornado-borne missile analysis code, which enables us to evaluate the liftoff and flight behaviors of unconstrained objects on the ground driven by a tornado. Using the Tornado-borne missile analysis code, we can obtain a stochastic correlation between local wind speed and flight distance of each object, and this stochastic correlation is used to evaluate the conditional strike probability, QV(r), of a missile located at position r, where the local wind speed is V. In contrast, the annual exceedance probability of local wind speed, which can be computed using a tornado hazard analysis code, is used to derive the probability density function, p(V). Then, we finally obtain the annual probability of tornado missile strike on a structure with the convolutional integration of product of QV(r) and p(V) over V. The evaluation method is applied to a simple problem to qualitatively confirm the validity, and to quantitatively verify the results for two extreme cases in which an object is located just in the vicinity of or far away from the structure

Contributions to quantum probability

International Nuclear Information System (INIS)

Fritz, Tobias

2010-01-01

Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a finite set can occur as the outcome

Thermal disadvantage factor calculation by the multiregion collision probability method

International Nuclear Information System (INIS)

Ozgener, B.; Ozgener, H.A.

2004-01-01

A multi-region collision probability formulation that is capable of applying white boundary condition directly is presented and applied to thermal neutron transport problems. The disadvantage factors computed are compared with their counterparts calculated by S N methods with both direct and indirect application of white boundary condition. The results of the ABH and collision probability method with indirect application of white boundary condition are also considered and comparisons with benchmark Monte Carlo results are carried out. The studies show that the proposed formulation is capable of calculating thermal disadvantage factor with sufficient accuracy without resorting to the fictitious scattering outer shell approximation associated with the indirect application of the white boundary condition in collision probability solutions

A Conditional Fourier-Feynman Transform and Conditional Convolution Product with Change of Scales on a Function Space II

Directory of Open Access Journals (Sweden)

Dong Hyun Cho

2017-01-01

Full Text Available Using a simple formula for conditional expectations over continuous paths, we will evaluate conditional expectations which are types of analytic conditional Fourier-Feynman transforms and conditional convolution products of generalized cylinder functions and the functions in a Banach algebra which is the space of generalized Fourier transforms of the measures on the Borel class of L2[0,T]. We will then investigate their relationships. Particularly, we prove that the conditional transform of the conditional convolution product can be expressed by the product of the conditional transforms of each function. Finally we will establish change of scale formulas for the conditional transforms and the conditional convolution products. In these evaluation formulas and change of scale formulas, we use multivariate normal distributions so that the conditioning function does not contain present positions of the paths.

A new formula for normal tissue complication probability (NTCP) as a function of equivalent uniform dose (EUD).

Science.gov (United States)

Luxton, Gary; Keall, Paul J; King, Christopher R

2008-01-07

To facilitate the use of biological outcome modeling for treatment planning, an exponential function is introduced as a simpler equivalent to the Lyman formula for calculating normal tissue complication probability (NTCP). The single parameter of the exponential function is chosen to reproduce the Lyman calculation to within approximately 0.3%, and thus enable easy conversion of data contained in empirical fits of Lyman parameters for organs at risk (OARs). Organ parameters for the new formula are given in terms of Lyman model m and TD(50), and conversely m and TD(50) are expressed in terms of the parameters of the new equation. The role of the Lyman volume-effect parameter n is unchanged from its role in the Lyman model. For a non-homogeneously irradiated OAR, an equation relates d(ref), n, v(eff) and the Niemierko equivalent uniform dose (EUD), where d(ref) and v(eff) are the reference dose and effective fractional volume of the Kutcher-Burman reduction algorithm (i.e. the LKB model). It follows in the LKB model that uniform EUD irradiation of an OAR results in the same NTCP as the original non-homogeneous distribution. The NTCP equation is therefore represented as a function of EUD. The inverse equation expresses EUD as a function of NTCP and is used to generate a table of EUD versus normal tissue complication probability for the Emami-Burman parameter fits as well as for OAR parameter sets from more recent data.

A new formula for normal tissue complication probability (NTCP) as a function of equivalent uniform dose (EUD)

International Nuclear Information System (INIS)

Luxton, Gary; Keall, Paul J; King, Christopher R

2008-01-01

To facilitate the use of biological outcome modeling for treatment planning, an exponential function is introduced as a simpler equivalent to the Lyman formula for calculating normal tissue complication probability (NTCP). The single parameter of the exponential function is chosen to reproduce the Lyman calculation to within ∼0.3%, and thus enable easy conversion of data contained in empirical fits of Lyman parameters for organs at risk (OARs). Organ parameters for the new formula are given in terms of Lyman model m and TD 50 , and conversely m and TD 50 are expressed in terms of the parameters of the new equation. The role of the Lyman volume-effect parameter n is unchanged from its role in the Lyman model. For a non-homogeneously irradiated OAR, an equation relates d ref , n, v eff and the Niemierko equivalent uniform dose (EUD), where d ref and v eff are the reference dose and effective fractional volume of the Kutcher-Burman reduction algorithm (i.e. the LKB model). It follows in the LKB model that uniform EUD irradiation of an OAR results in the same NTCP as the original non-homogeneous distribution. The NTCP equation is therefore represented as a function of EUD. The inverse equation expresses EUD as a function of NTCP and is used to generate a table of EUD versus normal tissue complication probability for the Emami-Burman parameter fits as well as for OAR parameter sets from more recent data

Alternative probability theories for cognitive psychology.

Science.gov (United States)

Narens, Louis

2014-01-01

Various proposals for generalizing event spaces for probability functions have been put forth in the mathematical, scientific, and philosophic literatures. In cognitive psychology such generalizations are used for explaining puzzling results in decision theory and for modeling the influence of context effects. This commentary discusses proposals for generalizing probability theory to event spaces that are not necessarily boolean algebras. Two prominent examples are quantum probability theory, which is based on the set of closed subspaces of a Hilbert space, and topological probability theory, which is based on the set of open sets of a topology. Both have been applied to a variety of cognitive situations. This commentary focuses on how event space properties can influence probability concepts and impact cognitive modeling. Copyright © 2013 Cognitive Science Society, Inc.

Exploring non-signalling polytopes with negative probability

International Nuclear Information System (INIS)

Oas, G; Barros, J Acacio de; Carvalhaes, C

2014-01-01

Bipartite and tripartite EPR–Bell type systems are examined via joint quasi-probability distributions where probabilities are permitted to be negative. It is shown that such distributions exist only when the no-signalling condition is satisfied. A characteristic measure, the probability mass, is introduced and, via its minimization, limits the number of quasi-distributions describing a given marginal probability distribution. The minimized probability mass is shown to be an alternative way to characterize non-local systems. Non-signalling polytopes for two to eight settings in the bipartite scenario are examined and compared to prior work. Examining perfect cloning of non-local systems within the tripartite scenario suggests defining two categories of signalling. It is seen that many properties of non-local systems can be efficiently described by quasi-probability theory. (paper)

Probability density functions of photochemicals over a coastal area of Northern Italy

International Nuclear Information System (INIS)

Georgiadis, T.; Fortezza, F.; Alberti, L.; Strocchi, V.; Marani, A.; Dal Bo', G.

1998-01-01

The present paper surveys the findings of experimental studies and analyses of statistical probability density functions (PDFs) applied to air pollutant concentrations to provide an interpretation of the ground-level distributions of photochemical oxidants in the coastal area of Ravenna (Italy). The atmospheric-pollution data set was collected from the local environmental monitoring network for the period 1978-1989. Results suggest that the statistical distribution of surface ozone, once normalised over the solar radiation PDF for the whole measurement period, follows a log-normal law as found for other pollutants. Although the Weibull distribution also offers a good fit of the experimental data, the area's meteorological features seem to favour the former distribution once the statistical index estimates have been analysed. Local transport phenomena are discussed to explain the data tail trends

Classical probabilities for Majorana and Weyl spinors

International Nuclear Information System (INIS)

Wetterich, C.

2011-01-01

Highlights: → Map of classical statistical Ising model to fermionic quantum field theory. → Lattice-regularized real Grassmann functional integral for single Weyl spinor. → Emerging complex structure characteristic for quantum physics. → A classical statistical ensemble describes a quantum theory. - Abstract: We construct a map between the quantum field theory of free Weyl or Majorana fermions and the probability distribution of a classical statistical ensemble for Ising spins or discrete bits. More precisely, a Grassmann functional integral based on a real Grassmann algebra specifies the time evolution of the real wave function q τ (t) for the Ising states τ. The time dependent probability distribution of a generalized Ising model obtains as p τ (t)=q τ 2 (t). The functional integral employs a lattice regularization for single Weyl or Majorana spinors. We further introduce the complex structure characteristic for quantum mechanics. Probability distributions of the Ising model which correspond to one or many propagating fermions are discussed explicitly. Expectation values of observables can be computed equivalently in the classical statistical Ising model or in the quantum field theory for fermions.

Free probability and random matrices

CERN Document Server

Mingo, James A

2017-01-01

This volume opens the world of free probability to a wide variety of readers. From its roots in the theory of operator algebras, free probability has intertwined with non-crossing partitions, random matrices, applications in wireless communications, representation theory of large groups, quantum groups, the invariant subspace problem, large deviations, subfactors, and beyond. This book puts a special emphasis on the relation of free probability to random matrices, but also touches upon the operator algebraic, combinatorial, and analytic aspects of the theory. The book serves as a combination textbook/research monograph, with self-contained chapters, exercises scattered throughout the text, and coverage of important ongoing progress of the theory. It will appeal to graduate students and all mathematicians interested in random matrices and free probability from the point of view of operator algebras, combinatorics, analytic functions, or applications in engineering and statistical physics.

Probability distribution functions of turbulence in seepage-affected alluvial channel

Energy Technology Data Exchange (ETDEWEB)

Sharma, Anurag; Kumar, Bimlesh, E-mail: anurag.sharma@iitg.ac.in, E-mail: bimk@iitg.ac.in [Department of Civil Engineering, Indian Institute of Technology Guwahati, 781039 (India)

2017-02-15

The present experimental study is carried out on the probability distribution functions (PDFs) of turbulent flow characteristics within near-bed-surface and away-from-bed surfaces for both no seepage and seepage flow. Laboratory experiments were conducted in the plane sand bed for no seepage (NS), 10% seepage (10%S) and 15% seepage (15%) cases. The experimental calculation of the PDFs of turbulent parameters such as Reynolds shear stress, velocity fluctuations, and bursting events is compared with theoretical expression obtained by Gram–Charlier (GC)-based exponential distribution. Experimental observations follow the computed PDF distributions for both no seepage and seepage cases. Jensen-Shannon divergence (JSD) method is used to measure the similarity between theoretical and experimental PDFs. The value of JSD for PDFs of velocity fluctuation lies between 0.0005 to 0.003 while the JSD value for PDFs of Reynolds shear stress varies between 0.001 to 0.006. Even with the application of seepage, the PDF distribution of bursting events, sweeps and ejections are well characterized by the exponential distribution of the GC series, except that a slight deflection of inward and outward interactions is observed which may be due to weaker events. The value of JSD for outward and inward interactions ranges from 0.0013 to 0.032, while the JSD value for sweep and ejection events varies between 0.0001 to 0.0025. The theoretical expression for the PDF of turbulent intensity is developed in the present study, which agrees well with the experimental observations and JSD lies between 0.007 and 0.015. The work presented is potentially applicable to the probability distribution of mobile-bed sediments in seepage-affected alluvial channels typically characterized by the various turbulent parameters. The purpose of PDF estimation from experimental data is that it provides a complete numerical description in the areas of turbulent flow either at a single or finite number of points

The probability of containment failure by direct containment heating in zion

International Nuclear Information System (INIS)

Pilch, M.M.; Yan, H.; Theofanous, T.G.

1994-01-01

This report is the first step in the resolution of the Direct Containment Heating (DCH) issue for the Zion Nuclear Power Plant using the Risk Oriented Accident Analysis Methodology (ROAAM). This report includes the definition of a probabilistic framework that decomposes the DCH problem into three probability density functions that reflect the most uncertain initial conditions (UO 2 mass, zirconium oxidation fraction, and steel mass). Uncertainties in the initial conditions are significant, but the quantification approach is based on establishing reasonable bounds that are not unnecessarily conservative. To this end, the authors also make use of the ROAAM ideas of enveloping scenarios and open-quotes splinteringclose quotes. Two casual relations (CRs) are used in this framework: CR1 is a model that calculates the peak pressure in the containment as a function of the initial conditions, and CR2 is a model that returns the frequency of containment failure as a function of pressure within the containment. Uncertainty in CR1 is accounted for by the use of two independently developed phenomenological models, the Convection Limited Containment Heating (CLCH) model and the Two-Cell Equilibrium (TCE) model, and by probabilistically distributing the key parameter in both, which is the ratio of the melt entrainment time to the system blowdown time constant. The two phenomenological models have been compared with an extensive data base including recent integral simulations at two different physical scales (1/10th scale in the Surtsey facility at Sandia National Laboratories and 1/40th scale in the COREXIT facility at Argonne National Laboratory). The loads predicted by these models were significantly lower than those from previous parametric calculations. The containment load distributions do not intersect the containment strength curve in any significant way, resulting in containment failure probabilities less than 10 -3 for all scenarios considered

Interactive design of probability density functions for shape grammars

KAUST Repository

Dang, Minh; Lienhard, Stefan; Ceylan, Duygu; Neubert, Boris; Wonka, Peter; Pauly, Mark

2015-01-01

A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density

The Use of Conditional Probability Integral Transformation Method for Testing Accelerated Failure Time Models

Directory of Open Access Journals (Sweden)

Abdalla Ahmed Abdel-Ghaly

2016-06-01

Full Text Available This paper suggests the use of the conditional probability integral transformation (CPIT method as a goodness of fit (GOF technique in the field of accelerated life testing (ALT, specifically for validating the underlying distributional assumption in accelerated failure time (AFT model. The method is based on transforming the data into independent and identically distributed (i.i.d Uniform (0, 1 random variables and then applying the modified Watson statistic to test the uniformity of the transformed random variables. This technique is used to validate each of the exponential, Weibull and lognormal distributions' assumptions in AFT model under constant stress and complete sampling. The performance of the CPIT method is investigated via a simulation study. It is concluded that this method performs well in case of exponential and lognormal distributions. Finally, a real life example is provided to illustrate the application of the proposed procedure.

Approximation methods in probability theory

CERN Document Server

Čekanavičius, Vydas

2016-01-01

This book presents a wide range of well-known and less common methods used for estimating the accuracy of probabilistic approximations, including the Esseen type inversion formulas, the Stein method as well as the methods of convolutions and triangle function. Emphasising the correct usage of the methods presented, each step required for the proofs is examined in detail. As a result, this textbook provides valuable tools for proving approximation theorems. While Approximation Methods in Probability Theory will appeal to everyone interested in limit theorems of probability theory, the book is particularly aimed at graduate students who have completed a standard intermediate course in probability theory. Furthermore, experienced researchers wanting to enlarge their toolkit will also find this book useful.

Large errors and severe conditions

CERN Document Server

Smith, D L; Van Wormer, L A

2002-01-01

Physical parameters that can assume real-number values over a continuous range are generally represented by inherently positive random variables. However, if the uncertainties in these parameters are significant (large errors), conventional means of representing and manipulating the associated variables can lead to erroneous results. Instead, all analyses involving them must be conducted in a probabilistic framework. Several issues must be considered: First, non-linear functional relations between primary and derived variables may lead to significant 'error amplification' (severe conditions). Second, the commonly used normal (Gaussian) probability distribution must be replaced by a more appropriate function that avoids the occurrence of negative sampling results. Third, both primary random variables and those derived through well-defined functions must be dealt with entirely in terms of their probability distributions. Parameter 'values' and 'errors' should be interpreted as specific moments of these probabil...

Stochastic Stability for Time-Delay Markovian Jump Systems with Sector-Bounded Nonlinearities and More General Transition Probabilities

Directory of Open Access Journals (Sweden)

Dan Ye

2013-01-01

Full Text Available This paper is concerned with delay-dependent stochastic stability for time-delay Markovian jump systems (MJSs with sector-bounded nonlinearities and more general transition probabilities. Different from the previous results where the transition probability matrix is completely known, a more general transition probability matrix is considered which includes completely known elements, boundary known elements, and completely unknown ones. In order to get less conservative criterion, the state and transition probability information is used as much as possible to construct the Lyapunov-Krasovskii functional and deal with stability analysis. The delay-dependent sufficient conditions are derived in terms of linear matrix inequalities to guarantee the stability of systems. Finally, numerical examples are exploited to demonstrate the effectiveness of the proposed method.

Generalized Probability-Probability Plots

NARCIS (Netherlands)

Mushkudiani, N.A.; Einmahl, J.H.J.

2004-01-01

We introduce generalized Probability-Probability (P-P) plots in order to study the one-sample goodness-of-fit problem and the two-sample problem, for real valued data.These plots, that are constructed by indexing with the class of closed intervals, globally preserve the properties of classical P-P

Escape probabilities for fluorescent x-rays

International Nuclear Information System (INIS)

Dance, D.R.; Day, G.J.

1985-01-01

Computation of the energy absorption efficiency of an x-ray photon detector involves consideration of the histories of the secondary particles produced in any initial or secondary interaction which may occur within the detector. In particular, the K or higher shell fluorescent x-rays which may be emitted following a photoelectric interaction can carry away a large fraction of the energy of the incident photon, especially if this energy is just above an absorption edge. The effects of such photons cannot be ignored and a correction term, depending upon the probability that the fluorescent x-rays will escape from the detector, must be applied to the energy absorption efficiency. For detectors such as x-ray intensifying screens, it has been usual to calculate this probability by numerical integration. In this note analytic expressions are derived for the escape probability of fluorescent photons from planar detectors in terms of exponential integral functions. Rational approximations for these functions are readily available and these analytic expressions therefore facilitate the computation of photon absorption efficiencies. A table is presented which should obviate the need for calculating the escape probability for most cases of interest. (author)

VISA-2, Reactor Vessel Failure Probability Under Thermal Shock

International Nuclear Information System (INIS)

Simonen, F.; Johnson, K.

1992-01-01

1 - Description of program or function: VISA2 (Vessel Integrity Simulation Analysis) was developed to estimate the failure probability of nuclear reactor pressure vessels under pressurized thermal shock conditions. The deterministic portion of the code performs heat transfer, stress, and fracture mechanics calculations for a vessel subjected to a user-specified temperature and pressure transient. The probabilistic analysis performs a Monte Carlo simulation to estimate the probability of vessel failure. Parameters such as initial crack size and position, copper and nickel content, fluence, and the fracture toughness values for crack initiation and arrest are treated as random variables. Linear elastic fracture mechanics methods are used to model crack initiation and growth. This includes cladding effects in the heat transfer, stress, and fracture mechanics calculations. The simulation procedure treats an entire vessel and recognizes that more than one flaw can exist in a given vessel. The flaw model allows random positioning of the flaw within the vessel wall thickness, and the user can specify either flaw length or length-to-depth aspect ratio for crack initiation and arrest predictions. The flaw size distribution can be adjust on the basis of different inservice inspection techniques and inspection conditions. The toughness simulation model includes a menu of alternative equations for predicting the shift in the reference temperature of the nil-ductility transition. 2 - Method of solution: The solution method uses closed form equations for temperatures, stresses, and stress intensity factors. A polynomial fitting procedure approximates the specified pressure and temperature transient. Failure probabilities are calculated by a Monte Carlo simulation. 3 - Restrictions on the complexity of the problem: Maxima of 30 welds. VISA2 models only the belt-line (cylindrical) region of a reactor vessel. The stresses are a function of the radial (through-wall) coordinate only

Probability Aggregates in Probability Answer Set Programming

OpenAIRE

Saad, Emad

2013-01-01

Probability answer set programming is a declarative programming that has been shown effective for representing and reasoning about a variety of probability reasoning tasks. However, the lack of probability aggregates, e.g. {\\em expected values}, in the language of disjunctive hybrid probability logic programs (DHPP) disallows the natural and concise representation of many interesting problems. In this paper, we extend DHPP to allow arbitrary probability aggregates. We introduce two types of p...

Development and evaluation of probability density functions for a set of human exposure factors

Energy Technology Data Exchange (ETDEWEB)

Maddalena, R.L.; McKone, T.E.; Bodnar, A.; Jacobson, J.

1999-06-01

The purpose of this report is to describe efforts carried out during 1998 and 1999 at the Lawrence Berkeley National Laboratory to assist the U.S. EPA in developing and ranking the robustness of a set of default probability distributions for exposure assessment factors. Among the current needs of the exposure-assessment community is the need to provide data for linking exposure, dose, and health information in ways that improve environmental surveillance, improve predictive models, and enhance risk assessment and risk management (NAS, 1994). The U.S. Environmental Protection Agency (EPA) Office of Emergency and Remedial Response (OERR) plays a lead role in developing national guidance and planning future activities that support the EPA Superfund Program. OERR is in the process of updating its 1989 Risk Assessment Guidance for Superfund (RAGS) as part of the EPA Superfund reform activities. Volume III of RAGS, when completed in 1999 will provide guidance for conducting probabilistic risk assessments. This revised document will contain technical information including probability density functions (PDFs) and methods used to develop and evaluate these PDFs. The PDFs provided in this EPA document are limited to those relating to exposure factors.

Development and evaluation of probability density functions for a set of human exposure factors

International Nuclear Information System (INIS)

Maddalena, R.L.; McKone, T.E.; Bodnar, A.; Jacobson, J.

1999-01-01

The purpose of this report is to describe efforts carried out during 1998 and 1999 at the Lawrence Berkeley National Laboratory to assist the U.S. EPA in developing and ranking the robustness of a set of default probability distributions for exposure assessment factors. Among the current needs of the exposure-assessment community is the need to provide data for linking exposure, dose, and health information in ways that improve environmental surveillance, improve predictive models, and enhance risk assessment and risk management (NAS, 1994). The U.S. Environmental Protection Agency (EPA) Office of Emergency and Remedial Response (OERR) plays a lead role in developing national guidance and planning future activities that support the EPA Superfund Program. OERR is in the process of updating its 1989 Risk Assessment Guidance for Superfund (RAGS) as part of the EPA Superfund reform activities. Volume III of RAGS, when completed in 1999 will provide guidance for conducting probabilistic risk assessments. This revised document will contain technical information including probability density functions (PDFs) and methods used to develop and evaluate these PDFs. The PDFs provided in this EPA document are limited to those relating to exposure factors

Contributions to quantum probability

Energy Technology Data Exchange (ETDEWEB)

Fritz, Tobias

2010-06-25

Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a

The Probability of Neonatal Respiratory Distress Syndrome as a Function of Gestational Age and Lecithin/Sphingomyelin Ratio

Science.gov (United States)

St. Clair, Caryn; Norwitz, Errol R.; Woensdregt, Karlijn; Cackovic, Michael; Shaw, Julia A.; Malkus, Herbert; Ehrenkranz, Richard A.; Illuzzi, Jessica L.

2011-01-01

We sought to define the risk of neonatal respiratory distress syndrome (RDS) as a function of both lecithin/sphingomyelin (L/S) ratio and gestational age. Amniotic fluid L/S ratio data were collected from consecutive women undergoing amniocentesis for fetal lung maturity at Yale-New Haven Hospital from January 1998 to December 2004. Women were included in the study if they delivered a live-born, singleton, nonanomalous infant within 72 hours of amniocentesis. The probability of RDS was modeled using multivariate logistic regression with L/S ratio and gestational age as predictors. A total of 210 mother-neonate pairs (8 RDS, 202 non-RDS) met criteria for analysis. Both gestational age and L/S ratio were independent predictors of RDS. A probability of RDS of 3% or less was noted at an L/S ratio cutoff of ≥3.4 at 34 weeks, ≥2.6 at 36 weeks, ≥1.6 at 38 weeks, and ≥1.2 at term. Under 34 weeks of gestation, the prevalence of RDS was so high that a probability of 3% or less was not observed by this model. These data describe a means of stratifying the probability of neonatal RDS using both gestational age and the L/S ratio and may aid in clinical decision making concerning the timing of delivery. PMID:18773379

Exact probability function for bulk density and current in the asymmetric exclusion process

Science.gov (United States)

Depken, Martin; Stinchcombe, Robin

2005-03-01

We examine the asymmetric simple exclusion process with open boundaries, a paradigm of driven diffusive systems, having a nonequilibrium steady-state transition. We provide a full derivation and expanded discussion and digression on results previously reported briefly in M. Depken and R. Stinchcombe, Phys. Rev. Lett. 93, 040602 (2004). In particular we derive an exact form for the joint probability function for the bulk density and current, both for finite systems, and also in the thermodynamic limit. The resulting distribution is non-Gaussian, and while the fluctuations in the current are continuous at the continuous phase transitions, the density fluctuations are discontinuous. The derivations are done by using the standard operator algebraic techniques and by introducing a modified version of the original operator algebra. As a by-product of these considerations we also arrive at a very simple way of calculating the normalization constant appearing in the standard treatment with the operator algebra. Like the partition function in equilibrium systems, this normalization constant is shown to completely characterize the fluctuations, albeit in a very different manner.

The perception of probability.

Science.gov (United States)

Gallistel, C R; Krishan, Monika; Liu, Ye; Miller, Reilly; Latham, Peter E

2014-01-01

We present a computational model to explain the results from experiments in which subjects estimate the hidden probability parameter of a stepwise nonstationary Bernoulli process outcome by outcome. The model captures the following results qualitatively and quantitatively, with only 2 free parameters: (a) Subjects do not update their estimate after each outcome; they step from one estimate to another at irregular intervals. (b) The joint distribution of step widths and heights cannot be explained on the assumption that a threshold amount of change must be exceeded in order for them to indicate a change in their perception. (c) The mapping of observed probability to the median perceived probability is the identity function over the full range of probabilities. (d) Precision (how close estimates are to the best possible estimate) is good and constant over the full range. (e) Subjects quickly detect substantial changes in the hidden probability parameter. (f) The perceived probability sometimes changes dramatically from one observation to the next. (g) Subjects sometimes have second thoughts about a previous change perception, after observing further outcomes. (h) The frequency with which they perceive changes moves in the direction of the true frequency over sessions. (Explaining this finding requires 2 additional parametric assumptions.) The model treats the perception of the current probability as a by-product of the construction of a compact encoding of the experienced sequence in terms of its change points. It illustrates the why and the how of intermittent Bayesian belief updating and retrospective revision in simple perception. It suggests a reinterpretation of findings in the recent literature on the neurobiology of decision making. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Statistics concerning the Apollo command module water landing, including the probability of occurrence of various impact conditions, sucessful impact, and body X-axis loads

Science.gov (United States)

Whitnah, A. M.; Howes, D. B.

1971-01-01

Statistical information for the Apollo command module water landings is presented. This information includes the probability of occurrence of various impact conditions, a successful impact, and body X-axis loads of various magnitudes.

Hamiltonian theories quantization based on a probability operator

International Nuclear Information System (INIS)

Entral'go, E.E.

1986-01-01

The quantization method with a linear reflection of classical coordinate-momentum-time functions Λ(q,p,t) at quantum operators in a space of quantum states ψ, is considered. The probability operator satisfies a system of equations representing the principles of dynamical and canonical correspondences between the classical and quantum theories. The quantization based on a probability operator leads to a quantum theory with a nonnegative joint coordinate-momentum distribution function for any state ψ. The main consequences of quantum mechanics with a probability operator are discussed in comparison with the generally accepted quantum and classical theories. It is shown that a probability operator leads to an appearance of some new notions called ''subquantum'' ones. Hence the quantum theory with a probability operator does not pretend to any complete description of physical reality in terms of classical variables and by this reason contains no problems like Einstein-Podolsky-Rosen paradox. The results of some concrete problems are given: a free particle, a harmonic oscillator, an electron in the Coulomb field. These results give hope on the possibility of an experimental verification of the quantization based on a probability operator

An introduction to probability and stochastic processes

CERN Document Server

Melsa, James L

2013-01-01

Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

Dependency models and probability of joint events

International Nuclear Information System (INIS)

Oerjasaeter, O.

1982-08-01

Probabilistic dependencies between components/systems are discussed with reference to a broad classification of potential failure mechanisms. Further, a generalized time-dependency model, based on conditional probabilities for estimation of the probability of joint events and event sequences is described. The applicability of this model is clarified/demonstrated by various examples. It is concluded that the described model of dependency is a useful tool for solving a variety of practical problems concerning the probability of joint events and event sequences where common cause and time-dependent failure mechanisms are involved. (Auth.)

Probabilistic Inference: Task Dependency and Individual Differences of Probability Weighting Revealed by Hierarchical Bayesian Modeling.

Science.gov (United States)

Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno

2016-01-01

Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

Probabilistic inference: Task dependency and individual differences of probability weighting revealed by hierarchical Bayesian modelling

Directory of Open Access Journals (Sweden)

Moritz eBoos

2016-05-01

Full Text Available Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities by two (likelihoods design. Five computational models of cognitive processes were compared with the observed behaviour. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model’s success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modelling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modelling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

On the evolution of the density probability density function in strongly self-gravitating systems

International Nuclear Information System (INIS)

Girichidis, Philipp; Konstandin, Lukas; Klessen, Ralf S.; Whitworth, Anthony P.

2014-01-01

The time evolution of the probability density function (PDF) of the mass density is formulated and solved for systems in free-fall using a simple approximate function for the collapse of a sphere. We demonstrate that a pressure-free collapse results in a power-law tail on the high-density side of the PDF. The slope quickly asymptotes to the functional form P V (ρ)∝ρ –1.54 for the (volume-weighted) PDF and P M (ρ)∝ρ –0.54 for the corresponding mass-weighted distribution. From the simple approximation of the PDF we derive analytic descriptions for mass accretion, finding that dynamically quiet systems with narrow density PDFs lead to retarded star formation and low star formation rates (SFRs). Conversely, strong turbulent motions that broaden the PDF accelerate the collapse causing a bursting mode of star formation. Finally, we compare our theoretical work with observations. The measured SFRs are consistent with our model during the early phases of the collapse. Comparison of observed column density PDFs with those derived from our model suggests that observed star-forming cores are roughly in free-fall.

Continuous time random walk model with asymptotical probability density of waiting times via inverse Mittag-Leffler function

Science.gov (United States)

Liang, Yingjie; Chen, Wen

2018-04-01

The mean squared displacement (MSD) of the traditional ultraslow diffusion is a logarithmic function of time. Recently, the continuous time random walk model is employed to characterize this ultraslow diffusion dynamics by connecting the heavy-tailed logarithmic function and its variation as the asymptotical waiting time density. In this study we investigate the limiting waiting time density of a general ultraslow diffusion model via the inverse Mittag-Leffler function, whose special case includes the traditional logarithmic ultraslow diffusion model. The MSD of the general ultraslow diffusion model is analytically derived as an inverse Mittag-Leffler function, and is observed to increase even more slowly than that of the logarithmic function model. The occurrence of very long waiting time in the case of the inverse Mittag-Leffler function has the largest probability compared with the power law model and the logarithmic function model. The Monte Carlo simulations of one dimensional sample path of a single particle are also performed. The results show that the inverse Mittag-Leffler waiting time density is effective in depicting the general ultraslow random motion.

Probability densities and the radon variable transformation theorem

International Nuclear Information System (INIS)

Ramshaw, J.D.

1985-01-01

D. T. Gillespie recently derived a random variable transformation theorem relating to the joint probability densities of functionally dependent sets of random variables. The present author points out that the theorem can be derived as an immediate corollary of a simpler and more fundamental relation. In this relation the probability density is represented as a delta function averaged over an unspecified distribution of unspecified internal random variables. The random variable transformation is derived from this relation

The probability of the false vacuum decay

International Nuclear Information System (INIS)

Kiselev, V.; Selivanov, K.

1983-01-01

The closed expession for the probability of the false vacuum decay in (1+1) dimensions is given. The probability of false vacuum decay is expessed as the product of exponential quasiclassical factor and a functional determinant of the given form. The method for calcutation of this determinant is developed and a complete answer for (1+1) dimensions is given

Negative probability in the framework of combined probability

OpenAIRE

Burgin, Mark

2013-01-01

Negative probability has found diverse applications in theoretical physics. Thus, construction of sound and rigorous mathematical foundations for negative probability is important for physics. There are different axiomatizations of conventional probability. So, it is natural that negative probability also has different axiomatic frameworks. In the previous publications (Burgin, 2009; 2010), negative probability was mathematically formalized and rigorously interpreted in the context of extende...

Bayesian Probability Theory

Science.gov (United States)

von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo

2014-06-01

Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.

Influence of the level of fit of a density probability function to wind-speed data on the WECS mean power output estimation

International Nuclear Information System (INIS)

Carta, Jose A.; Ramirez, Penelope; Velazquez, Sergio

2008-01-01

Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error ε made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R 2 statistic (R a 2 ). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R a 2 statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R a 2 increases

Analyses of moments in pseudorapidity intervals at √s = 546 GeV by means of two probability distributions in pure-birth process

International Nuclear Information System (INIS)

Biyajima, M.; Shirane, K.; Suzuki, N.

1988-01-01

Moments in pseudorapidity intervals at the CERN Sp-barpS collider (√s = 546 GeV) are analyzed by means of two probability distributions in the pure-birth stochastic process. Our results show that a probability distribution obtained from the Poisson distribution as an initial condition is more useful than that obtained from the Kronecker δ function. Analyses of moments by Koba-Nielsen-Olesen scaling functions derived from solutions of the pure-birth stochastic process are also made. Moreover, analyses of preliminary data at √s = 200 and 900 GeV are added

Technical report. The application of probability-generating functions to linear-quadratic radiation survival curves.

Science.gov (United States)

Kendal, W S

2000-04-01

To illustrate how probability-generating functions (PGFs) can be employed to derive a simple probabilistic model for clonogenic survival after exposure to ionizing irradiation. Both repairable and irreparable radiation damage to DNA were assumed to occur by independent (Poisson) processes, at intensities proportional to the irradiation dose. Also, repairable damage was assumed to be either repaired or further (lethally) injured according to a third (Bernoulli) process, with the probability of lethal conversion being directly proportional to dose. Using the algebra of PGFs, these three processes were combined to yield a composite PGF that described the distribution of lethal DNA lesions in irradiated cells. The composite PGF characterized a Poisson distribution with mean, chiD+betaD2, where D was dose and alpha and beta were radiobiological constants. This distribution yielded the conventional linear-quadratic survival equation. To test the composite model, the derived distribution was used to predict the frequencies of multiple chromosomal aberrations in irradiated human lymphocytes. The predictions agreed well with observation. This probabilistic model was consistent with single-hit mechanisms, but it was not consistent with binary misrepair mechanisms. A stochastic model for radiation survival has been constructed from elementary PGFs that exactly yields the linear-quadratic relationship. This approach can be used to investigate other simple probabilistic survival models.

Probability of Survival Decision Aid (PSDA)

National Research Council Canada - National Science Library

Xu, Xiaojiang; Amin, Mitesh; Santee, William R

2008-01-01

A Probability of Survival Decision Aid (PSDA) is developed to predict survival time for hypothermia and dehydration during prolonged exposure at sea in both air and water for a wide range of environmental conditions...

On the probability of the discovery of comets and the reality of the concentration of perihelia

International Nuclear Information System (INIS)

Radzievskij, V.V.

1979-01-01

A high probability of the discovery of comets is discussed from the point of view of Golechek visibility conditions. The Golechek function is calculated for 482 comets with the period P > 1000 years, selected from the Marcden catalogue. A new empiric formula is obtained for the probability of comet discovery depending on the Golechek function and on the bending of orbits. It is shown that the observed concentration of (lambdasub(π)) perihelia longitudes of comet orbits at lambdasub(π)=270 deg can not be a consequence of selection effect. A conclusion is made that the observed concentration of perihelia of comet orbits is real and it may be considered as the most important cosmogonal characteristic. A hypothesis of comet origin can not be perfectly considered without the explanation of this characteristic

Approximations to the Probability of Failure in Random Vibration by Integral Equation Methods

DEFF Research Database (Denmark)

Nielsen, Søren R.K.; Sørensen, John Dalsgaard

Close approximations to the first passage probability of failure in random vibration can be obtained by integral equation methods. A simple relation exists between the first passage probability density function and the distribution function for the time interval spent below a barrier before...... passage probability density. The results of the theory agree well with simulation results for narrow banded processes dominated by a single frequency, as well as for bimodal processes with 2 dominating frequencies in the structural response....... outcrossing. An integral equation for the probability density function of the time interval is formulated, and adequate approximations for the kernel are suggested. The kernel approximation results in approximate solutions for the probability density function of the time interval, and hence for the first...

Quantum probabilities of composite events in quantum measurements with multimode states

International Nuclear Information System (INIS)

Yukalov, V I; Sornette, D

2013-01-01

The problem of defining quantum probabilities of composite events is considered. This problem is of great importance for the theory of quantum measurements and for quantum decision theory, which is a part of measurement theory. We show that the Lüders probability of consecutive measurements is a transition probability between two quantum states and that this probability cannot be treated as a quantum extension of the classical conditional probability. The Wigner distribution is shown to be a weighted transition probability that cannot be accepted as a quantum extension of the classical joint probability. We suggest the definition of quantum joint probabilities by introducing composite events in multichannel measurements. The notion of measurements under uncertainty is defined. We demonstrate that the necessary condition for mode interference is the entanglement of the composite prospect together with the entanglement of the composite statistical state. As an illustration, we consider an example of a quantum game. Special attention is paid to the application of the approach to systems with multimode states, such as atoms, molecules, quantum dots, or trapped Bose-condensed atoms with several coherent modes. (paper)

Probability Estimation in the Framework of Intuitionistic Fuzzy Evidence Theory

Directory of Open Access Journals (Sweden)

Yafei Song

2015-01-01

Full Text Available Intuitionistic fuzzy (IF evidence theory, as an extension of Dempster-Shafer theory of evidence to the intuitionistic fuzzy environment, is exploited to process imprecise and vague information. Since its inception, much interest has been concentrated on IF evidence theory. Many works on the belief functions in IF information systems have appeared. Although belief functions on the IF sets can deal with uncertainty and vagueness well, it is not convenient for decision making. This paper addresses the issue of probability estimation in the framework of IF evidence theory with the hope of making rational decision. Background knowledge about evidence theory, fuzzy set, and IF set is firstly reviewed, followed by introduction of IF evidence theory. Axiomatic properties of probability distribution are then proposed to assist our interpretation. Finally, probability estimations based on fuzzy and IF belief functions together with their proofs are presented. It is verified that the probability estimation method based on IF belief functions is also potentially applicable to classical evidence theory and fuzzy evidence theory. Moreover, IF belief functions can be combined in a convenient way once they are transformed to interval-valued possibilities.

δ'-function perturbations and Neumann boundary-conditions by path integration

International Nuclear Information System (INIS)

Grosche, C.

1994-02-01

δ'-function perturbations and Neumann boundary conditions are incorporated into the path integral formalism. The starting point is the consideration of the path integral representation for the one dimensional Dirac particle together with a relativistic point interaction. The non-relativistic limit yields either a usual δ-function or a δ'-function perturbation; making their strengths infinitely repulsive one obtains Dirichlet, respectively Neumann boundary conditions in the path integral. (orig.)

[Socio-demographics characteristics and health conditions of older homeless persons of Lima, Peru].

Science.gov (United States)

Moquillaza-Risco, Marlene; León, Elsa; Dongo, Mario; Munayco, César V

2015-10-01

Determine the socio-demographics characteristics and health conditions of older homeless persons at the time of enrollment into the National Program "Vida Digna" and the probability of functional dependency by age, and stratified by gender and cognitive impairment. MATERIALS ANDE METHODS: We performed a cross sectional study, reviewing all registration forms of the program in order to identify socio-demographic variables and health conditions of older homeless persons at the time of enrollment in the program. We did a descriptive analysis of the socio-demographic variables and we also determined the frequency of health conditions. Furthermore, we determined the probability of functional dependency by age, and stratified by gender and cognitive impairment through a logistic regression model. The older homeless persons at the time of enrollment in the program were mostly single men, with a primary education or no education. The study subjects had a high frequency of chronic and mental diseases. 50% of them had certain level of functional impairment and roughly 70% had a certain level of cognitive impairment. The probability of functional dependency increased by age, and it was higher in women than in men. This probability increased according to the level of cognitive impairment. This study shows that older homeless persons are a vulnerable population not only because they live outdoors but also because they a have also for the high prevalence of chronic and mental diseases. These diseases prevent the homeless persons from living by themselves special care to overcome their situations.

Evaluation of Presumed Probability-Density-Function Models in Non-Premixed Flames by using Large Eddy Simulation

International Nuclear Information System (INIS)

Cao Hong-Jun; Zhang Hui-Qiang; Lin Wen-Yi

2012-01-01

Four kinds of presumed probability-density-function (PDF) models for non-premixed turbulent combustion are evaluated in flames with various stoichiometric mixture fractions by using large eddy simulation (LES). The LES code is validated by the experimental data of a classical turbulent jet flame (Sandia flame D). The mean and rms temperatures obtained by the presumed PDF models are compared with the LES results. The β-function model achieves a good prediction for different flames. The predicted rms temperature by using the double-δ function model is very small and unphysical in the vicinity of the maximum mean temperature. The clip-Gaussian model and the multi-δ function model make a worse prediction of the extremely fuel-rich or fuel-lean side due to the clip at the boundary of the mixture fraction space. The results also show that the overall prediction performance of presumed PDF models is better at mediate stoichiometric mixture fractions than that at very small or very large ones. (fundamental areas of phenomenology(including applications))

Probability distribution function values in mobile phones;Valores de funciones de distribución de probabilidad en el teléfono móvil

Directory of Open Access Journals (Sweden)

Luis Vicente Chamorro Marcillllo

2013-06-01

Full Text Available Engineering, within its academic and application forms, as well as any formal research work requires the use of statistics and every inferential statistical analysis requires the use of values of probability distribution functions that are generally available in tables. Generally, management of those tables have physical problems (wasteful transport and wasteful consultation and operational (incomplete lists and limited accuracy. The study, “Probability distribution function values in mobile phones”, permitted determining – through a needs survey applied to students involved in statistics studies at Universidad de Nariño – that the best known and most used values correspond to Chi-Square, Binomial, Student’s t, and Standard Normal distributions. Similarly, it showed user’s interest in having the values in question within an alternative means to correct, at least in part, the problems presented by “the famous tables”. To try to contribute to the solution, we built software that allows immediately and dynamically obtaining the values of the probability distribution functions most commonly used by mobile phones.

Discovering context-aware conditional functional dependencies

Institute of Scientific and Technical Information of China (English)

Yuefeng DU; Derong SHEN; Tiezheng NIE; Yue KOU; Ge YU

2017-01-01

Conditional functional dependencies(CFDs) are important techniques for data consistency.However,CFDs are limited to 1) provide the reasonable values for consistency repairing and 2) detect potential errors.This paper presents context-aware conditional functional dependencies(CCFDs) which contribute to provide reasonable values and detect potential errors.Especially,we focus on automatically discovering minimal CCFDs.In this paper,we present context relativity to measure the relationship of CFDs.The overlap of the related CFDs can provide reasonable values which result in more accuracy consistency repairing,and some related CFDs are combined into CCFDs.Moreover,we prove that discovering minimal CCFDs is NP-complete and we design the precise method and the heuristic method.We also present the dominating value to facilitate the process in both the precise method and the heuristic method.Additionally,the context relativity of the CFDs affects the cleaning results.We will give an approximate threshold of context relativity according to data distribution for suggestion.The repairing results are approved more accuracy,even evidenced by our empirical evaluation.

Faster exact Markovian probability functions for motif occurrences: a DFA-only approach.

Science.gov (United States)

Ribeca, Paolo; Raineri, Emanuele

2008-12-15

The computation of the statistical properties of motif occurrences has an obviously relevant application: patterns that are significantly over- or under-represented in genomes or proteins are interesting candidates for biological roles. However, the problem is computationally hard; as a result, virtually all the existing motif finders use fast but approximate scoring functions, in spite of the fact that they have been shown to produce systematically incorrect results. A few interesting exact approaches are known, but they are very slow and hence not practical in the case of realistic sequences. We give an exact solution, solely based on deterministic finite-state automata (DFA), to the problem of finding the whole relevant part of the probability distribution function of a simple-word motif in a homogeneous (biological) sequence. Out of that, the z-value can always be computed, while the P-value can be obtained either when it is not too extreme with respect to the number of floating-point digits available in the implementation, or when the number of pattern occurrences is moderately low. In particular, the time complexity of the algorithms for Markov models of moderate order (0 manage to obtain an algorithm which is both easily interpretable and efficient. This approach can be used for exact statistical studies of very long genomes and protein sequences, as we illustrate with some examples on the scale of the human genome.

Bayesian noninferiority test for 2 binomial probabilities as the extension of Fisher exact test.

Science.gov (United States)

Doi, Masaaki; Takahashi, Fumihiro; Kawasaki, Yohei

2017-12-30

Noninferiority trials have recently gained importance for the clinical trials of drugs and medical devices. In these trials, most statistical methods have been used from a frequentist perspective, and historical data have been used only for the specification of the noninferiority margin Δ>0. In contrast, Bayesian methods, which have been studied recently are advantageous in that they can use historical data to specify prior distributions and are expected to enable more efficient decision making than frequentist methods by borrowing information from historical trials. In the case of noninferiority trials for response probabilities π 1 ,π 2 , Bayesian methods evaluate the posterior probability of H 1 :π 1 >π 2 -Δ being true. To numerically calculate such posterior probability, complicated Appell hypergeometric function or approximation methods are used. Further, the theoretical relationship between Bayesian and frequentist methods is unclear. In this work, we give the exact expression of the posterior probability of the noninferiority under some mild conditions and propose the Bayesian noninferiority test framework which can flexibly incorporate historical data by using the conditional power prior. Further, we show the relationship between Bayesian posterior probability and the P value of the Fisher exact test. From this relationship, our method can be interpreted as the Bayesian noninferior extension of the Fisher exact test, and we can treat superiority and noninferiority in the same framework. Our method is illustrated through Monte Carlo simulations to evaluate the operating characteristics, the application to the real HIV clinical trial data, and the sample size calculation using historical data. Copyright © 2017 John Wiley & Sons, Ltd.

The influence of the electron wave function on the Pt Lsub(I) and Lsub(III) ionization probabilities by 3.6 MeV He impact

International Nuclear Information System (INIS)

Ullrich, J.; Dangendorf, V.; Dexheimer, K.; Do, K.; Kelbch, C.; Kelbch, S.; Schadt, W.; Schmidt-Boecking, H.; Stiebing, K.E.; Roesel, F.; Trautmann, D.

1986-01-01

For 3.6 MeV He impact the Lsub(I) and Lsub(III) subshell ionization probabilities of Pt have been measured. Due to relativistic effects in the electron wave functions, the Lsub(I) subshell ionization probability Isub(LI)(b) is strong enhanced at small impact parameters exceeding even Isub(LIII)(b) in nice agreement with the SCA theory. (orig.)

Nash equilibrium with lower probabilities

DEFF Research Database (Denmark)

Groes, Ebbe; Jacobsen, Hans Jørgen; Sloth, Birgitte

1998-01-01

We generalize the concept of Nash equilibrium in mixed strategies for strategic form games to allow for ambiguity in the players' expectations. In contrast to other contributions, we model ambiguity by means of so-called lower probability measures or belief functions, which makes it possible...

Pade approximant calculations for neutron escape probability

International Nuclear Information System (INIS)

El Wakil, S.A.; Saad, E.A.; Hendi, A.A.

1984-07-01

The neutron escape probability from a non-multiplying slab containing internal source is defined in terms of a functional relation for the scattering function for the diffuse reflection problem. The Pade approximant technique is used to get numerical results which compare with exact results. (author)

The H-Function and Probability Density Functions of Certain Algebraic Combinations of Independent Random Variables with H-Function Probability Distribution

Science.gov (United States)

1981-05-01

Education, 10 (2), A45-A49 (1976). 48. Rain&, R. K., and C. L. Kaul (Koul), "Some inequalities involving the Fox’s H- function," Proceedings of the Indian...1973). 51. Srivastava , A., and K. C. Gupta, "On certain recurrence rela- tions," Mathematische Nachrichten, 46, 13- 23 (1970), 49, 187- 197 (1971). 52...34 Vilnana Parishad Anusandhan Patrika, 10, 205- 217 (1967). 69. Gupta, K. C., and A. Srivastava , "On finite expansions for the H- function," Indian Journal

Using Fuzzy Probability Weights in Cumulative Prospect Theory

Directory of Open Access Journals (Sweden)

Užga-Rebrovs Oļegs

2016-12-01

Full Text Available During the past years, a rapid growth has been seen in the descriptive approaches to decision choice. As opposed to normative expected utility theory, these approaches are based on the subjective perception of probabilities by the individuals, which takes place in real situations of risky choice. The modelling of this kind of perceptions is made on the basis of probability weighting functions. In cumulative prospect theory, which is the focus of this paper, decision prospect outcome weights are calculated using the obtained probability weights. If the value functions are constructed in the sets of positive and negative outcomes, then, based on the outcome value evaluations and outcome decision weights, generalised evaluations of prospect value are calculated, which are the basis for choosing an optimal prospect.

Impact parameter dependence of inner-shell ionization probabilities

International Nuclear Information System (INIS)

Cocke, C.L.

1974-01-01

The probability for ionization of an inner shell of a target atom by a heavy charged projectile is a sensitive function of the impact parameter characterizing the collision. This probability can be measured experimentally by detecting the x-ray resulting from radiative filling of the inner shell in coincidence with the projectile scattered at a determined angle, and by using the scattering angle to deduce the impact parameter. It is conjectured that the functional dependence of the ionization probability may be a more sensitive probe of the ionization mechanism than is a total cross section measurement. Experimental results for the K-shell ionization of both solid and gas targets by oxygen, carbon and fluorine projectiles in the MeV/amu energy range will be presented, and their use in illuminating the inelastic collision process discussed

Fitness Probability Distribution of Bit-Flip Mutation.

Science.gov (United States)

Chicano, Francisco; Sutton, Andrew M; Whitley, L Darrell; Alba, Enrique

2015-01-01

Bit-flip mutation is a common mutation operator for evolutionary algorithms applied to optimize functions over binary strings. In this paper, we develop results from the theory of landscapes and Krawtchouk polynomials to exactly compute the probability distribution of fitness values of a binary string undergoing uniform bit-flip mutation. We prove that this probability distribution can be expressed as a polynomial in p, the probability of flipping each bit. We analyze these polynomials and provide closed-form expressions for an easy linear problem (Onemax), and an NP-hard problem, MAX-SAT. We also discuss a connection of the results with runtime analysis.

Single, Complete, Probability Spaces Consistent With EPR-Bohm-Bell Experimental Data

Science.gov (United States)

Avis, David; Fischer, Paul; Hilbert, Astrid; Khrennikov, Andrei

2009-03-01

We show that paradoxical consequences of violations of Bell's inequality are induced by the use of an unsuitable probabilistic description for the EPR-Bohm-Bell experiment. The conventional description (due to Bell) is based on a combination of statistical data collected for different settings of polarization beam splitters (PBSs). In fact, such data consists of some conditional probabilities which only partially define a probability space. Ignoring this conditioning leads to apparent contradictions in the classical probabilistic model (due to Kolmogorov). We show how to make a completely consistent probabilistic model by taking into account the probabilities of selecting the settings of the PBSs. Our model matches both the experimental data and is consistent with classical probability theory.

Probability

CERN Document Server

Shiryaev, A N

1996-01-01

This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, ergodic theory, weak convergence of probability measures, stationary stochastic processes, and the Kalman-Bucy filter Many examples are discussed in detail, and there are a large number of exercises The book is accessible to advanced undergraduates and can be used as a text for self-study This new edition contains substantial revisions and updated references The reader will find a deeper study of topics such as the distance between probability measures, metrization of weak convergence, and contiguity of probability measures Proofs for a number of some important results which were merely stated in the first edition have been added The author included new material on the probability of large deviations, and on the central limit theorem for sums of dependent random variables

Internal Medicine residents use heuristics to estimate disease probability

OpenAIRE

Phang, Sen Han; Ravani, Pietro; Schaefer, Jeffrey; Wright, Bruce; McLaughlin, Kevin

2015-01-01

Background: Training in Bayesian reasoning may have limited impact on accuracy of probability estimates. In this study, our goal was to explore whether residents previously exposed to Bayesian reasoning use heuristics rather than Bayesian reasoning to estimate disease probabilities. We predicted that if residents use heuristics then post-test probability estimates would be increased by non-discriminating clinical features or a high anchor for a target condition. Method: We randomized 55 In...

Upper Bounds for Ruin Probability with Stochastic Investment Return

Institute of Scientific and Technical Information of China (English)

ZHANG Lihong

2005-01-01

Risk models with stochastic investment return are widely held in practice, as well as in more challenging research fields. Risk theory is mainly concerned with ruin probability, and a tight bound for ruin probability is the best for practical use. This paper presents a discrete time risk model with stochastic investment return. Conditional expectation properties and martingale inequalities are used to obtain both exponential and non-exponential upper bounds for the ruin probability.

The probability of an encounter of two Brownian particles before escape

International Nuclear Information System (INIS)

Holcman, D; Kupka, I

2009-01-01

We study the probability of meeting of two Brownian particles before one of them exits a finite interval. We obtain an explicit expression for the probability as a function of the initial distance between the two particles using the Weierstrass elliptic function. We also find the law of the meeting location. Brownian simulations show the accuracy of our analysis. Finally, we discuss some applications to the probability that a double-strand DNA break repairs in confined environments.

A Novel Adaptive Conditional Probability-Based Predicting Model for User’s Personality Traits

Directory of Open Access Journals (Sweden)

Mengmeng Wang

2015-01-01

Full Text Available With the pervasive increase in social media use, the explosion of users’ generated data provides a potentially very rich source of information, which plays an important role in helping online researchers understand user’s behaviors deeply. Since user’s personality traits are the driving force of user’s behaviors, hence, in this paper, along with social network features, we first extract linguistic features, emotional statistical features, and topic features from user’s Facebook status updates, followed by quantifying importance of features via Kendall correlation coefficient. And then, on the basis of weighted features and dynamic updated thresholds of personality traits, we deploy a novel adaptive conditional probability-based predicting model which considers prior knowledge of correlations between user’s personality traits to predict user’s Big Five personality traits. In the experimental work, we explore the existence of correlations between user’s personality traits which provides a better theoretical support for our proposed method. Moreover, on the same Facebook dataset, compared to other methods, our method can achieve an F1-measure of 80.6% when taking into account correlations between user’s personality traits, and there is an impressive improvement of 5.8% over other approaches.

Left passage probability of Schramm-Loewner Evolution

Science.gov (United States)

Najafi, M. N.

2013-06-01

SLE(κ,ρ⃗) is a variant of Schramm-Loewner Evolution (SLE) which describes the curves which are not conformal invariant, but are self-similar due to the presence of some other preferred points on the boundary. In this paper we study the left passage probability (LPP) of SLE(κ,ρ⃗) through field theoretical framework and find the differential equation governing this probability. This equation is numerically solved for the special case κ=2 and hρ=0 in which hρ is the conformal weight of the boundary changing (bcc) operator. It may be referred to loop erased random walk (LERW) and Abelian sandpile model (ASM) with a sink on its boundary. For the curve which starts from ξ0 and conditioned by a change of boundary conditions at x0, we find that this probability depends significantly on the factor x0-ξ0. We also present the perturbative general solution for large x0. As a prototype, we apply this formalism to SLE(κ,κ-6) which governs the curves that start from and end on the real axis.

Beyond Bayes: On the Need for a Unified and Jaynesian Definition of Probability and Information within Neuroscience

Directory of Open Access Journals (Sweden)

Christopher D. Fiorillo

2012-04-01

Full Text Available It has been proposed that the general function of the brain is inference, which corresponds quantitatively to the minimization of uncertainty (or the maximization of information. However, there has been a lack of clarity about exactly what this means. Efforts to quantify information have been in agreement that it depends on probabilities (through Shannon entropy, but there has long been a dispute about the definition of probabilities themselves. The “frequentist” view is that probabilities are (or can be essentially equivalent to frequencies, and that they are therefore properties of a physical system, independent of any observer of the system. E.T. Jaynes developed the alternate “Bayesian” definition, in which probabilities are always conditional on a state of knowledge through the rules of logic, as expressed in the maximum entropy principle. In doing so, Jaynes and others provided the objective means for deriving probabilities, as well as a unified account of information and logic (knowledge and reason. However, neuroscience literature virtually never specifies any definition of probability, nor does it acknowledge any dispute concerning the definition. Although there has recently been tremendous interest in Bayesian approaches to the brain, even in the Bayesian literature it is common to find probabilities that are purported to come directly and unconditionally from frequencies. As a result, scientists have mistakenly attributed their own information to the neural systems they study. Here I argue that the adoption of a strictly Jaynesian approach will prevent such errors and will provide us with the philosophical and mathematical framework that is needed to understand the general function of the brain. Accordingly, our challenge becomes the identification of the biophysical basis of Jaynesian information and logic. I begin to address this issue by suggesting how we might identify a probability distribution over states of one physical

Fractal supersymmetric QM, Geometric Probability and the Riemann Hypothesis

CERN Document Server

Castro, C

2004-01-01

The Riemann's hypothesis (RH) states that the nontrivial zeros of the Riemann zeta-function are of the form $ s_n =1/2+i\\lambda_n $. Earlier work on the RH based on supersymmetric QM, whose potential was related to the Gauss-Jacobi theta series, allows to provide the proper framework to construct the well defined algorithm to compute the probability to find a zero (an infinity of zeros) in the critical line. Geometric probability theory furnishes the answer to the very difficult question whether the probability that the RH is true is indeed equal to unity or not. To test the validity of this geometric probabilistic framework to compute the probability if the RH is true, we apply it directly to the the hyperbolic sine function $ \\sinh (s) $ case which obeys a trivial analog of the RH (the HSRH). Its zeros are equally spaced in the imaginary axis $ s_n = 0 + i n \\pi $. The geometric probability to find a zero (and an infinity of zeros) in the imaginary axis is exactly unity. We proceed with a fractal supersymme...

Estimation of post-test probabilities by residents: Bayesian reasoning versus heuristics?

Science.gov (United States)

Hall, Stacey; Phang, Sen Han; Schaefer, Jeffrey P; Ghali, William; Wright, Bruce; McLaughlin, Kevin

2014-08-01

Although the process of diagnosing invariably begins with a heuristic, we encourage our learners to support their diagnoses by analytical cognitive processes, such as Bayesian reasoning, in an attempt to mitigate the effects of heuristics on diagnosing. There are, however, limited data on the use ± impact of Bayesian reasoning on the accuracy of disease probability estimates. In this study our objective was to explore whether Internal Medicine residents use a Bayesian process to estimate disease probabilities by comparing their disease probability estimates to literature-derived Bayesian post-test probabilities. We gave 35 Internal Medicine residents four clinical vignettes in the form of a referral letter and asked them to estimate the post-test probability of the target condition in each case. We then compared these to literature-derived probabilities. For each vignette the estimated probability was significantly different from the literature-derived probability. For the two cases with low literature-derived probability our participants significantly overestimated the probability of these target conditions being the correct diagnosis, whereas for the two cases with high literature-derived probability the estimated probability was significantly lower than the calculated value. Our results suggest that residents generate inaccurate post-test probability estimates. Possible explanations for this include ineffective application of Bayesian reasoning, attribute substitution whereby a complex cognitive task is replaced by an easier one (e.g., a heuristic), or systematic rater bias, such as central tendency bias. Further studies are needed to identify the reasons for inaccuracy of disease probability estimates and to explore ways of improving accuracy.

On estimating probability of presence from use-availability or presence-background data.

Science.gov (United States)

Phillips, Steven J; Elith, Jane

2013-06-01

A fundamental ecological modeling task is to estimate the probability that a species is present in (or uses) a site, conditional on environmental variables. For many species, available data consist of "presence" data (locations where the species [or evidence of it] has been observed), together with "background" data, a random sample of available environmental conditions. Recently published papers disagree on whether probability of presence is identifiable from such presence-background data alone. This paper aims to resolve the disagreement, demonstrating that additional information is required. We defined seven simulated species representing various simple shapes of response to environmental variables (constant, linear, convex, unimodal, S-shaped) and ran five logistic model-fitting methods using 1000 presence samples and 10 000 background samples; the simulations were repeated 100 times. The experiment revealed a stark contrast between two groups of methods: those based on a strong assumption that species' true probability of presence exactly matches a given parametric form had highly variable predictions and much larger RMS error than methods that take population prevalence (the fraction of sites in which the species is present) as an additional parameter. For six species, the former group grossly under- or overestimated probability of presence. The cause was not model structure or choice of link function, because all methods were logistic with linear and, where necessary, quadratic terms. Rather, the experiment demonstrates that an estimate of prevalence is not just helpful, but is necessary (except in special cases) for identifying probability of presence. We therefore advise against use of methods that rely on the strong assumption, due to Lele and Keim (recently advocated by Royle et al.) and Lancaster and Imbens. The methods are fragile, and their strong assumption is unlikely to be true in practice. We emphasize, however, that we are not arguing against

Influence of the level of fit of a density probability function to wind-speed data on the WECS mean power output estimation

Energy Technology Data Exchange (ETDEWEB)

Carta, Jose A. [Department of Mechanical Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Ramirez, Penelope; Velazquez, Sergio [Department of Renewable Energies, Technological Institute of the Canary Islands, Pozo Izquierdo Beach s/n, 35119 Santa Lucia, Gran Canaria, Canary Islands (Spain)

2008-10-15

Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error {epsilon} made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R{sup 2} statistic (R{sub a}{sup 2}). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R{sub a}{sup 2} statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R{sub a}{sup 2} increases. (author)

Identifying functional reorganization of spelling networks: an individual peak probability comparison approach

Science.gov (United States)

Purcell, Jeremy J.; Rapp, Brenda

2013-01-01

Previous research has shown that damage to the neural substrates of orthographic processing can lead to functional reorganization during reading (Tsapkini et al., 2011); in this research we ask if the same is true for spelling. To examine the functional reorganization of spelling networks we present a novel three-stage Individual Peak Probability Comparison (IPPC) analysis approach for comparing the activation patterns obtained during fMRI of spelling in a single brain-damaged individual with dysgraphia to those obtained in a set of non-impaired control participants. The first analysis stage characterizes the convergence in activations across non-impaired control participants by applying a technique typically used for characterizing activations across studies: Activation Likelihood Estimate (ALE) (Turkeltaub et al., 2002). This method was used to identify locations that have a high likelihood of yielding activation peaks in the non-impaired participants. The second stage provides a characterization of the degree to which the brain-damaged individual's activations correspond to the group pattern identified in Stage 1. This involves performing a Mahalanobis distance statistics analysis (Tsapkini et al., 2011) that compares each of a control group's peak activation locations to the nearest peak generated by the brain-damaged individual. The third stage evaluates the extent to which the brain-damaged individual's peaks are atypical relative to the range of individual variation among the control participants. This IPPC analysis allows for a quantifiable, statistically sound method for comparing an individual's activation pattern to the patterns observed in a control group and, thus, provides a valuable tool for identifying functional reorganization in a brain-damaged individual with impaired spelling. Furthermore, this approach can be applied more generally to compare any individual's activation pattern with that of a set of other individuals. PMID:24399981

Targeting the probability versus cost of feared outcomes in public speaking anxiety.

Science.gov (United States)

Nelson, Elizabeth A; Deacon, Brett J; Lickel, James J; Sy, Jennifer T

2010-04-01

Cognitive-behavioral theory suggests that social phobia is maintained, in part, by overestimates of the probability and cost of negative social events. Indeed, empirically supported cognitive-behavioral treatments directly target these cognitive biases through the use of in vivo exposure or behavioral experiments. While cognitive-behavioral theories and treatment protocols emphasize the importance of targeting probability and cost biases in the reduction of social anxiety, few studies have examined specific techniques for reducing probability and cost bias, and thus the relative efficacy of exposure to the probability versus cost of negative social events is unknown. In the present study, 37 undergraduates with high public speaking anxiety were randomly assigned to a single-session intervention designed to reduce either the perceived probability or the perceived cost of negative outcomes associated with public speaking. Compared to participants in the probability treatment condition, those in the cost treatment condition demonstrated significantly greater improvement on measures of public speaking anxiety and cost estimates for negative social events. The superior efficacy of the cost treatment condition was mediated by greater treatment-related changes in social cost estimates. The clinical implications of these findings are discussed. Published by Elsevier Ltd.

Joint Probability Distributions for a Class of Non-Markovian Processes

OpenAIRE

Baule, A.; Friedrich, R.

2004-01-01

We consider joint probability distributions for the class of coupled Langevin equations introduced by Fogedby [H.C. Fogedby, Phys. Rev. E 50, 1657 (1994)]. We generalize well-known results for the single time probability distributions to the case of N-time joint probability distributions. It is shown that these probability distribution functions can be obtained by an integral transform from distributions of a Markovian process. The integral kernel obeys a partial differential equation with fr...

The transition probability and the probability for the left-most particle's position of the q-totally asymmetric zero range process

Energy Technology Data Exchange (ETDEWEB)

Korhonen, Marko [Department of Mathematics and Statistics, University of Helsinki, FIN-00014 (Finland); Lee, Eunghyun [Centre de Recherches Mathématiques (CRM), Université de Montréal, Quebec H3C 3J7 (Canada)

2014-01-15

We treat the N-particle zero range process whose jumping rates satisfy a certain condition. This condition is required to use the Bethe ansatz and the resulting model is the q-boson model by Sasamoto and Wadati [“Exact results for one-dimensional totally asymmetric diffusion models,” J. Phys. A 31, 6057–6071 (1998)] or the q-totally asymmetric zero range process (TAZRP) by Borodin and Corwin [“Macdonald processes,” Probab. Theory Relat. Fields (to be published)]. We find the explicit formula of the transition probability of the q-TAZRP via the Bethe ansatz. By using the transition probability we find the probability distribution of the left-most particle's position at time t. To find the probability for the left-most particle's position we find a new identity corresponding to identity for the asymmetric simple exclusion process by Tracy and Widom [“Integral formulas for the asymmetric simple exclusion process,” Commun. Math. Phys. 279, 815–844 (2008)]. For the initial state that all particles occupy a single site, the probability distribution of the left-most particle's position at time t is represented by the contour integral of a determinant.

Failure probability estimate of type 304 stainless steel piping

International Nuclear Information System (INIS)

Daugherty, W.L.; Awadalla, N.G.; Sindelar, R.L.; Mehta, H.S.; Ranganath, S.

1989-01-01

The primary source of in-service degradation of the SRS production reactor process water piping is intergranular stress corrosion cracking (IGSCC). IGSCC has occurred in a limited number of weld heat affected zones, areas known to be susceptible to IGSCC. A model has been developed to combine crack growth rates, crack size distributions, in-service examination reliability estimates and other considerations to estimate the pipe large-break frequency. This frequency estimates the probability that an IGSCC crack will initiate, escape detection by ultrasonic (UT) examination, and grow to instability prior to extending through-wall and being detected by the sensitive leak detection system. These events are combined as the product of four factors: (1) the probability that a given weld heat affected zone contains IGSCC; (2) the conditional probability, given the presence of IGSCC, that the cracking will escape detection during UT examination; (3) the conditional probability, given a crack escapes detection by UT, that it will not grow through-wall and be detected by leakage; (4) the conditional probability, given a crack is not detected by leakage, that it grows to instability prior to the next UT exam. These four factors estimate the occurrence of several conditions that must coexist in order for a crack to lead to a large break of the process water piping. When evaluated for the SRS production reactors, they produce an extremely low break frequency. The objective of this paper is to present the assumptions, methodology, results and conclusions of a probabilistic evaluation for the direct failure of the primary coolant piping resulting from normal operation and seismic loads. This evaluation was performed to support the ongoing PRA effort and to complement deterministic analyses addressing the credibility of a double-ended guillotine break

Pain, functional status, social function and conditions of habitation in elderly unilaterally lower limb amputees

Directory of Open Access Journals (Sweden)

Đurović Aleksandar

2007-01-01

Full Text Available Background/Aim. Few authors are involved in home rehabilitation of amputees or their reintegration into the community. It has been remarked that there is a discontinuity between the phases of the amputee rehabilitation in Serbia. The aim of the study was to establish pain characteristics and functional status of amputees two months after the amputation and to determine their social function and the conditions of their habitation. Methods. This prospective observation study involved 38 elderly amputees with unilateral lower limb amputations. The patients were tested at the hospital on discharge and at their homes two months after the amputation. Pain intensity and functional status were measured by a visual analogue scale (VAS and by Functional Independence Measure (FIM. The patients’ social function was assessed using the Social Dysfunction Rating Scale (SDRS and conditions of their habitation by the self-created Scale of Conditions of Habitation (SCH. In statistic analysis we used the Student t test, χ2 test and Analysis of variance (ANOVA. Results. The majority of patients (63% underwent below knee amputation caused by diabetes (89%. A significant number of patients (84%, χ2 = 17.78; p < 0.01 was not visited by a physiotherapist nor an occupational therapist during two months at home. In this period, the majority of the amputees (68% had phantom pain or residual limb pain (21%. Two months after amputation the pain intensity was significantly lower (VAS = 4.07±2.19; 2.34±1.41; p < 0.001, and the functional status significantly better than on discharge (FIM = 75.13±16.52; 87.87±16.48; p < 0.001. The amputees had the average level of social dysfunction (SDRS = 62.00±11.68 and conditions of habitation (SCH = 7.81±1.97. Conclusion. A total 38 elderly amputees with unilateral lower limb amputations achieved significant functional improvement and reduction of pain, in spite of their social dysfunction, the absence of socio-medical support

Future southcentral US wildfire probability due to climate change

Science.gov (United States)

Stambaugh, Michael C.; Guyette, Richard P.; Stroh, Esther D.; Struckhoff, Matthew A.; Whittier, Joanna B.

2018-01-01

Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. In this paper, we present projections of future fire probability for the southcentral USA using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM). Future fire probability is projected to both increase and decrease across the study region of Oklahoma, New Mexico, and Texas. Among all end-of-century projections, change in fire probabilities (CFPs) range from − 51 to + 240%. Greatest absolute increases in fire probability are shown for areas within the range of approximately 75 to 160 cm mean annual precipitation (MAP), regardless of climate model. Although fire is likely to become more frequent across the southcentral USA, spatial patterns may remain similar unless significant increases in precipitation occur, whereby more extensive areas with increased fire probability are predicted. Perhaps one of the most important results is illumination of climate changes where fire probability response (+, −) may deviate (i.e., tipping points). Fire regimes of southcentral US ecosystems occur in a geographic transition zone from reactant- to reaction-limited conditions, potentially making them uniquely responsive to different scenarios of temperature and precipitation changes. Identification and description of these conditions may help anticipate fire regime changes that will affect human health, agriculture, species conservation, and nutrient and water cycling.

ELIPGRID-PC: A PC program for calculating hot spot probabilities

International Nuclear Information System (INIS)

Davidson, J.R.

1994-10-01

ELIPGRID-PC, a new personal computer program has been developed to provide easy access to Singer's 1972 ELIPGRID algorithm for hot-spot detection probabilities. Three features of the program are the ability to determine: (1) the grid size required for specified conditions, (2) the smallest hot spot that can be sampled with a given probability, and (3) the approximate grid size resulting from specified conditions and sampling cost. ELIPGRID-PC also provides probability of hit versus cost data for graphing with spread-sheets or graphics software. The program has been successfully tested using Singer's published ELIPGRID results. An apparent error in the original ELIPGRID code has been uncovered and an appropriate modification incorporated into the new program

Estimating reliability of degraded system based on the probability density evolution with multi-parameter

Directory of Open Access Journals (Sweden)

Jiang Ge

2017-01-01

Full Text Available System degradation was usually caused by multiple-parameter degradation. The assessment result of system reliability by universal generating function was low accurate when compared with the Monte Carlo simulation. And the probability density function of the system output performance cannot be got. So the reliability assessment method based on the probability density evolution with multi-parameter was presented for complexly degraded system. Firstly, the system output function was founded according to the transitive relation between component parameters and the system output performance. Then, the probability density evolution equation based on the probability conservation principle and the system output function was established. Furthermore, probability distribution characteristics of the system output performance was obtained by solving differential equation. Finally, the reliability of the degraded system was estimated. This method did not need to discrete the performance parameters and can establish continuous probability density function of the system output performance with high calculation efficiency and low cost. Numerical example shows that this method is applicable to evaluate the reliability of multi-parameter degraded system.

Quantum probability and quantum decision-making.

Science.gov (United States)

Yukalov, V I; Sornette, D

2016-01-13

A rigorous general definition of quantum probability is given, which is valid not only for elementary events but also for composite events, for operationally testable measurements as well as for inconclusive measurements, and also for non-commuting observables in addition to commutative observables. Our proposed definition of quantum probability makes it possible to describe quantum measurements and quantum decision-making on the same common mathematical footing. Conditions are formulated for the case when quantum decision theory reduces to its classical counterpart and for the situation where the use of quantum decision theory is necessary. © 2015 The Author(s).

Quantifying seining detection probability for fishes of Great Plains sand‐bed rivers

Science.gov (United States)

Mollenhauer, Robert; Logue, Daniel R.; Brewer, Shannon K.

2018-01-01

Species detection error (i.e., imperfect and variable detection probability) is an essential consideration when investigators map distributions and interpret habitat associations. When fish detection error that is due to highly variable instream environments needs to be addressed, sand‐bed streams of the Great Plains represent a unique challenge. We quantified seining detection probability for diminutive Great Plains fishes across a range of sampling conditions in two sand‐bed rivers in Oklahoma. Imperfect detection resulted in underestimates of species occurrence using naïve estimates, particularly for less common fishes. Seining detection probability also varied among fishes and across sampling conditions. We observed a quadratic relationship between water depth and detection probability, in which the exact nature of the relationship was species‐specific and dependent on water clarity. Similarly, the direction of the relationship between water clarity and detection probability was species‐specific and dependent on differences in water depth. The relationship between water temperature and detection probability was also species dependent, where both the magnitude and direction of the relationship varied among fishes. We showed how ignoring detection error confounded an underlying relationship between species occurrence and water depth. Despite imperfect and heterogeneous detection, our results support that determining species absence can be accomplished with two to six spatially replicated seine hauls per 200‐m reach under average sampling conditions; however, required effort would be higher under certain conditions. Detection probability was low for the Arkansas River Shiner Notropis girardi, which is federally listed as threatened, and more than 10 seine hauls per 200‐m reach would be required to assess presence across sampling conditions. Our model allows scientists to estimate sampling effort to confidently assess species occurrence, which

Most probable degree distribution at fixed structural entropy

Indian Academy of Sciences (India)

Here we derive the most probable degree distribution emerging ... the structural entropy of power-law networks is an increasing function of the expo- .... tition function Z of the network as the sum over all degree distributions, with given energy.

Probabilistic analysis of Millstone Unit 3 ultimate containment failure probability given high pressure: Chapter 14

International Nuclear Information System (INIS)

Bickel, J.H.

1983-01-01

The quantification of the containment event trees in the Millstone Unit 3 Probabilistic Safety Study utilizes a conditional probability of failure given high pressure which is based on a new approach. The generation of this conditional probability was based on a weakest link failure mode model which considered contributions from a number of overlapping failure modes. This overlap effect was due to a number of failure modes whose mean failure pressures were clustered within a 5 psi range and which had uncertainties due to variances in material strengths and analytical uncertainties which were between 9 and 15 psi. Based on a review of possible probability laws to describe the failure probability of individual structural failure modes, it was determined that a Weibull probability law most adequately described the randomness in the physical process of interest. The resultant conditional probability of failure is found to have a median failure pressure of 132.4 psia. The corresponding 5-95 percentile values are 112 psia and 146.7 psia respectively. The skewed nature of the conditional probability of failure vs. pressure results in a lower overall containment failure probability for an appreciable number of the severe accident sequences of interest, but also probabilities which are more rigorously traceable from first principles

Scaling Qualitative Probability

OpenAIRE

Burgin, Mark

2017-01-01

There are different approaches to qualitative probability, which includes subjective probability. We developed a representation of qualitative probability based on relational systems, which allows modeling uncertainty by probability structures and is more coherent than existing approaches. This setting makes it possible proving that any comparative probability is induced by some probability structure (Theorem 2.1), that classical probability is a probability structure (Theorem 2.2) and that i...

The probability distribution of maintenance cost of a system affected by the gamma process of degradation: Finite time solution

International Nuclear Information System (INIS)

Cheng, Tianjin; Pandey, Mahesh D.; Weide, J.A.M. van der

2012-01-01

The stochastic gamma process has been widely used to model uncertain degradation in engineering systems and structures. The optimization of the condition-based maintenance (CBM) policy is typically based on the minimization of the asymptotic cost rate. In the financial planning of a maintenance program, however, a more accurate prediction interval for the cost is needed for prudent decision making. The prediction interval cannot be estimated unless the probability distribution of cost is known. In this context, the asymptotic cost rate has a limited utility. This paper presents the derivation of the probability distribution of maintenance cost, when the system degradation is modelled as a stochastic gamma process. A renewal equation is formulated to derive the characteristic function, then the discrete Fourier transform of the characteristic function leads to the complete probability distribution of cost in a finite time setting. The proposed approach is useful for a precise estimation of prediction limits and optimization of the maintenance cost.

Thermal conditions and functional requirements for molten fuel containment

International Nuclear Information System (INIS)

Kang, C.S.; Torri, A.

1980-05-01

This paper discusses the configuration and functional requirements for the molten fuel containment system (MFCS) in the GCFR demonstration plant design. Meltdown conditions following a loss of shutdown cooling (LOSC) accident were studied to define the core debris volume for a realistic meltdown case. Materials and thicknesses of the molten fuel container were defined. Stainless steel was chosen as the sacrificial material and magnesium oxide was chosen as the crucible material. Thermal conditions for an expected quasi-steady state were analyzed. Highlights of the functional requirements which directly affect the MFCS design are discussed

Finite-size scaling of survival probability in branching processes

OpenAIRE

Garcia-Millan, Rosalba; Font-Clos, Francesc; Corral, Alvaro

2014-01-01

Branching processes pervade many models in statistical physics. We investigate the survival probability of a Galton-Watson branching process after a finite number of generations. We reveal the finite-size scaling law of the survival probability for a given branching process ruled by a probability distribution of the number of offspring per element whose standard deviation is finite, obtaining the exact scaling function as well as the critical exponents. Our findings prove the universal behavi...

Harmonic Function of Poincare Cone Condition In Solving Dirichlet ...

African Journals Online (AJOL)

Harmonic Function of Poincare Cone Condition In Solving Dirichlet Problem. ... Journal of the Nigerian Association of Mathematical Physics ... theorem, the dirichlet problem and maximum principle where we conclude that the application of sums , differences and scalar multiples of harmonic functions are again harmonic.

Estimation of probability density functions of damage parameter for valve leakage detection in reciprocating pump used in nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Kyeom; Kim, Tae Yun; Kim, Hyun Su; Chai, Jang Bom; Lee, Jin Woo [Div. of Mechanical Engineering, Ajou University, Suwon (Korea, Republic of)

2016-10-15

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

Estimation of probability density functions of damage parameter for valve leakage detection in reciprocating pump used in nuclear power plants

International Nuclear Information System (INIS)

Lee, Jong Kyeom; Kim, Tae Yun; Kim, Hyun Su; Chai, Jang Bom; Lee, Jin Woo

2016-01-01

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage

Estimation of Probability Density Functions of Damage Parameter for Valve Leakage Detection in Reciprocating Pump Used in Nuclear Power Plants

Directory of Open Access Journals (Sweden)

Jong Kyeom Lee

2016-10-01

Full Text Available This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

Sensitivity analysis of limit state functions for probability-based plastic design

Science.gov (United States)

Frangopol, D. M.

1984-01-01

The evaluation of the total probability of a plastic collapse failure P sub f for a highly redundant structure of random interdependent plastic moments acted on by random interdepedent loads is a difficult and computationally very costly process. The evaluation of reasonable bounds to this probability requires the use of second moment algebra which involves man statistical parameters. A computer program which selects the best strategy for minimizing the interval between upper and lower bounds of P sub f is now in its final stage of development. The relative importance of various uncertainties involved in the computational process on the resulting bounds of P sub f, sensitivity is analyzed. Response sensitivities for both mode and system reliability of an ideal plastic portal frame are shown.

Measurement uncertainty and probability

CERN Document Server

Willink, Robin

2013-01-01

A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science.

What Are Probability Surveys used by the National Aquatic Resource Surveys?

Science.gov (United States)

The National Aquatic Resource Surveys (NARS) use probability-survey designs to assess the condition of the nation’s waters. In probability surveys (also known as sample-surveys or statistical surveys), sampling sites are selected randomly.

A quantum probability model of causal reasoning

Directory of Open Access Journals (Sweden)

Jennifer S Trueblood

2012-05-01

Full Text Available People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause with diagnostic judgments (i.e., the conditional probability of a cause given an effect. The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment.

Computing rates of Markov models of voltage-gated ion channels by inverting partial differential equations governing the probability density functions of the conducting and non-conducting states.

Science.gov (United States)

Tveito, Aslak; Lines, Glenn T; Edwards, Andrew G; McCulloch, Andrew

2016-07-01

Markov models are ubiquitously used to represent the function of single ion channels. However, solving the inverse problem to construct a Markov model of single channel dynamics from bilayer or patch-clamp recordings remains challenging, particularly for channels involving complex gating processes. Methods for solving the inverse problem are generally based on data from voltage clamp measurements. Here, we describe an alternative approach to this problem based on measurements of voltage traces. The voltage traces define probability density functions of the functional states of an ion channel. These probability density functions can also be computed by solving a deterministic system of partial differential equations. The inversion is based on tuning the rates of the Markov models used in the deterministic system of partial differential equations such that the solution mimics the properties of the probability density function gathered from (pseudo) experimental data as well as possible. The optimization is done by defining a cost function to measure the difference between the deterministic solution and the solution based on experimental data. By evoking the properties of this function, it is possible to infer whether the rates of the Markov model are identifiable by our method. We present applications to Markov model well-known from the literature. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Boundary conditions for quasiclassical Green's function for superfluid Fermi systems

International Nuclear Information System (INIS)

Nagai, K.; Hara, J.

1988-01-01

The authors show that the quasiclassical Green's Function for Fermi liquids can be constructed from the solutions of the Bogoliubov-de Gennes equation within the Andreev approximation and derive self-consistent relations to be satisfied by the quasiclassical Green's function at the surfaces. The so-called normalization condition for the quasiclassical Green's function is obtained from this self-consistent relation. They consider a specularly reflecting wall, a randomly rippled wall, and a proximity boundary as model surfaces. Their boundary condition for the randomly rippled wall is different from that derived by Buchholtz and Rainer and Buchholtz

Smoothed Conditional Scale Function Estimation in AR(1-ARCH(1 Processes

Directory of Open Access Journals (Sweden)

Lema Logamou Seknewna

2018-01-01

Full Text Available The estimation of the Smoothed Conditional Scale Function for time series was taken out under the conditional heteroscedastic innovations by imitating the kernel smoothing in nonparametric QAR-QARCH scheme. The estimation was taken out based on the quantile regression methodology proposed by Koenker and Bassett. And the proof of the asymptotic properties of the Conditional Scale Function estimator for this type of process was given and its consistency was shown.

Probability shapes perceptual precision: A study in orientation estimation.

Science.gov (United States)

Jabar, Syaheed B; Anderson, Britt

2015-12-01

Probability is known to affect perceptual estimations, but an understanding of mechanisms is lacking. Moving beyond binary classification tasks, we had naive participants report the orientation of briefly viewed gratings where we systematically manipulated contingent probability. Participants rapidly developed faster and more precise estimations for high-probability tilts. The shapes of their error distributions, as indexed by a kurtosis measure, also showed a distortion from Gaussian. This kurtosis metric was robust, capturing probability effects that were graded, contextual, and varying as a function of stimulus orientation. Our data can be understood as a probability-induced reduction in the variability or "shape" of estimation errors, as would be expected if probability affects the perceptual representations. As probability manipulations are an implicit component of many endogenous cuing paradigms, changes at the perceptual level could account for changes in performance that might have traditionally been ascribed to "attention." (c) 2015 APA, all rights reserved).

Dynamic SEP event probability forecasts

Science.gov (United States)

Kahler, S. W.; Ling, A.

2015-10-01

The forecasting of solar energetic particle (SEP) event probabilities at Earth has been based primarily on the estimates of magnetic free energy in active regions and on the observations of peak fluxes and fluences of large (≥ M2) solar X-ray flares. These forecasts are typically issued for the next 24 h or with no definite expiration time, which can be deficient for time-critical operations when no SEP event appears following a large X-ray flare. It is therefore important to decrease the event probability forecast with time as a SEP event fails to appear. We use the NOAA listing of major (≥10 pfu) SEP events from 1976 to 2014 to plot the delay times from X-ray peaks to SEP threshold onsets as a function of solar source longitude. An algorithm is derived to decrease the SEP event probabilities with time when no event is observed to reach the 10 pfu threshold. In addition, we use known SEP event size distributions to modify probability forecasts when SEP intensity increases occur below the 10 pfu event threshold. An algorithm to provide a dynamic SEP event forecast, Pd, for both situations of SEP intensities following a large flare is derived.

Psychosocial functioning in adults with congenital craniofacial conditions.

Science.gov (United States)

Roberts, R M; Mathias, J L

2012-05-01

To examine the psychosocial functioning of adults with congenital craniofacial conditions relative to normative data. Single sample cross-sectional design. The Australian Craniofacial Unit, Women's and Children's Hospital, Adelaide, which is one of the main craniofacial treatment centers in Australia. Adults (N  =  93) with congenital craniofacial conditions (excluding cleft lip/palate) who were treated in the Australian Craniofacial Unit. All participants completed self-report scales assessing health-related quality of life (SF-36); life satisfaction, anxiety, and depression (HADS); self-esteem (Rosenberg); appearance-related concerns; perceived social support; and social anxiety. Overall, participants were very similar in psychosocial function to the general population. However, adults with craniofacial conditions were less likely to be married and have children (females), were more likely to be receiving a disability pension, and reported more appearance-related concerns and less social support from friends. They also reported more limitations in both their social activities, due to physical or emotional problems, and usual role activities, because of emotional problems, as well as poorer mental health. These results give cause to be very positive about the long-term outcomes of children who are undergoing treatment for craniofacial conditions, while also identifying specific areas that interventions could target.

A probable new type of osteopenic bone disease

Energy Technology Data Exchange (ETDEWEB)

Widhe, Torulf L. [Department of Orthopaedics, Huddinge University Hospital (Sweden)

2002-06-01

A probable new type of osteopenic bone disease in two sisters and one female cousin is described. In infancy, the radiological findings were osteopenia, coxa vara, periosteal cloaking, bowing of the long bones, and flaring of the metaphyses. During growth, spinal pathology developed with compression of the vertebral bodies and scoliosis in one girl and kyphosis in another. All three children had genu valgum and two developed severe S-shaped bowing of the tibiae. Growth was stunted. Inheritance of this disorder is probably recessive. Type I and III collagen biosynthesis was normal. This condition is probably a hitherto undescribed form of osteogenesis imperfecta type III or a new bone disease. (orig.)

A probable new type of osteopenic bone disease

International Nuclear Information System (INIS)

Widhe, Torulf L.

2002-01-01

A probable new type of osteopenic bone disease in two sisters and one female cousin is described. In infancy, the radiological findings were osteopenia, coxa vara, periosteal cloaking, bowing of the long bones, and flaring of the metaphyses. During growth, spinal pathology developed with compression of the vertebral bodies and scoliosis in one girl and kyphosis in another. All three children had genu valgum and two developed severe S-shaped bowing of the tibiae. Growth was stunted. Inheritance of this disorder is probably recessive. Type I and III collagen biosynthesis was normal. This condition is probably a hitherto undescribed form of osteogenesis imperfecta type III or a new bone disease. (orig.)

Time dependent and asymptotic neutron number probability distribution calculation using discrete Fourier transform

International Nuclear Information System (INIS)

Humbert, Ph.

2005-01-01

In this paper we consider the probability distribution of neutrons in a multiplying assembly. The problem is studied using a space independent one group neutron point reactor model without delayed neutrons. We recall the generating function methodology and analytical results obtained by G.I. Bell when the c 2 approximation is used and we present numerical solutions in the general case, without this approximation. The neutron source induced distribution is calculated using the single initial neutron distribution which satisfies a master (Kolmogorov backward) equation. This equation is solved using the generating function method. The generating function satisfies a differential equation and the probability distribution is derived by inversion of the generating function. Numerical results are obtained using the same methodology where the generating function is the Fourier transform of the probability distribution. Discrete Fourier transforms are used to calculate the discrete time dependent distributions and continuous Fourier transforms are used to calculate the asymptotic continuous probability distributions. Numerical applications are presented to illustrate the method. (author)

Fasting: Benefits and probable health harmfulness from the Islamic perspective

Directory of Open Access Journals (Sweden)

Mahdi Ebrahimi

2015-06-01

Medical science can determine the effects and consequences of thirst and hunger during the month of Ramadan. In the religious perspective, it has been emphasized that fasting is for achieving the divine virtue, and this shouldn’t be in conflict with maintaining man’s health. Therefore, the conditions in which there is the probability of harmfulness to man’s health due to fasting, man shouldn’t fast. As a result, medical science could recognize the conditions in which there is probable harmfulness to man’s health.

A note on the transition probability over Csup(*)-algebras

International Nuclear Information System (INIS)

Alberti, P.M.; Karl-Marx-Universitaet, Leipzig

1983-01-01

The algebraic structure of Uhlmann's transition probability between mixed states on unital Csup(*)-algebras is analyzed. Several improvements of methods to calculate the transition probability are fixed, examples are given (e.g., the case of quasi-local Csup(*)-algebras is dealt with) and two more functional characterizations are proved in general. (orig.)

Joint probability distributions for a class of non-Markovian processes.

Science.gov (United States)

Baule, A; Friedrich, R

2005-02-01

We consider joint probability distributions for the class of coupled Langevin equations introduced by Fogedby [H. C. Fogedby, Phys. Rev. E 50, 1657 (1994)]. We generalize well-known results for the single-time probability distributions to the case of N -time joint probability distributions. It is shown that these probability distribution functions can be obtained by an integral transform from distributions of a Markovian process. The integral kernel obeys a partial differential equation with fractional time derivatives reflecting the non-Markovian character of the process.

The Efficacy of Using Diagrams When Solving Probability Word Problems in College

Science.gov (United States)

Beitzel, Brian D.; Staley, Richard K.

2015-01-01

Previous experiments have shown a deleterious effect of visual representations on college students' ability to solve total- and joint-probability word problems. The present experiments used conditional-probability problems, known to be more difficult than total- and joint-probability problems. The diagram group was instructed in how to use tree…

Communication: Two types of flat-planes conditions in density functional theory.

Science.gov (United States)

Yang, Xiaotian Derrick; Patel, Anand H G; Miranda-Quintana, Ramón Alain; Heidar-Zadeh, Farnaz; González-Espinoza, Cristina E; Ayers, Paul W

2016-07-21

Using results from atomic spectroscopy, we show that there are two types of flat-planes conditions. The first type of flat-planes condition occurs when the energy as a function of the number of electrons of each spin, Nα and Nβ, has a derivative discontinuity on a line segment where the number of electrons, Nα + Nβ, is an integer. The second type of flat-planes condition occurs when the energy has a derivative discontinuity on a line segment where the spin polarization, Nα - Nβ, is an integer, but does not have a discontinuity associated with an integer number of electrons. Type 2 flat planes are rare-we observed just 15 type 2 flat-planes conditions out of the 4884 cases we tested-but their mere existence has implications for the design of exchange-correlation energy density functionals. To facilitate the development of functionals that have the correct behavior with respect to both fractional number of electrons and fractional spin polarization, we present a dataset for the chromium atom and its ions that can be used to test new functionals.

Introduction to probability and statistics for science, engineering, and finance

CERN Document Server

Rosenkrantz, Walter A

2008-01-01

Data Analysis Orientation The Role and Scope of Statistics in Science and Engineering Types of Data: Examples from Engineering, Public Health, and Finance The Frequency Distribution of a Variable Defined on a Population Quantiles of a Distribution Measures of Location (Central Value) and Variability Covariance, Correlation, and Regression: Computing a Stock's Beta Mathematical Details and Derivations Large Data Sets Probability Theory Orientation Sample Space, Events, Axioms of Probability Theory Mathematical Models of Random Sampling Conditional Probability and Baye

Realizing ecosystem services: wetland hydrologic function along a gradient of ecosystem condition.

Science.gov (United States)

McLaughlin, Daniel L; Cohen, Matthew J

2013-10-01

Wetlands provide numerous ecosystem services, from habitat provision to pollutant removal, floodwater storage, and microclimate regulation. Delivery of particular services relies on specific ecological functions, and thus to varying degree on wetland ecological condition, commonly quantified as departure from minimally impacted reference sites. Condition assessments are widely adopted as regulatory indicators of ecosystem function, and for some services (e.g., habitat) links between condition and function are often direct. For others, however, links are more tenuous, and using condition alone to enumerate ecosystem value (e.g., for compensatory mitigation) may underestimate important services. Hydrologic function affects many services cited in support of wetland protection both directly (floodwater retention, microclimate regulation) and indirectly (biogeochemical cycling, pollutant removal). We investigated links between condition and hydrologic function to test the hypothesis, embedded in regulatory assessment of wetland value, that condition predicts function. Condition was assessed using rapid and intensive approaches, including Florida's official wetland assessment tool, in 11 isolated forested wetlands in north Florida (USA) spanning a land use intensity gradient. Hydrologic function was assessed using hydrologic regime (mean, variance, and rates of change of water depth), and measurements of groundwater exchange and evapotranspiration (ET). Despite a wide range in condition, no systematic variation in hydrologic regime was observed; indeed reference sites spanned the full range of variation. In contrast, ET was affected by land use, with higher rates in intensive (agriculture and urban) landscapes in response to higher leaf area. ET determines latent heat exchange, which regulates microclimate, a valuable service in urban heat islands. Higher ET also indicates higher productivity and thus carbon cycling. Groundwater exchange regularly reversed flow direction

Estimating the Probability of Wind Ramping Events: A Data-driven Approach

OpenAIRE

Wang, Cheng; Wei, Wei; Wang, Jianhui; Qiu, Feng

2016-01-01

This letter proposes a data-driven method for estimating the probability of wind ramping events without exploiting the exact probability distribution function (PDF) of wind power. Actual wind data validates the proposed method.

The probability of a tornado missile hitting a target

International Nuclear Information System (INIS)

Goodman, J.; Koch, J.E.

1983-01-01

It is shown that tornado missile transportation is a diffusion Markovian process. Therefore, the Green's function method is applied for the estimation of the probability of hitting a unit target area. This propability is expressed through a joint density of tornado intensity and path area, a probability of tornado missile injection and a tornado missile height distribution. (orig.)

Geometric modeling in probability and statistics

CERN Document Server

Calin, Ovidiu

2014-01-01

This book covers topics of Informational Geometry, a field which deals with the differential geometric study of the manifold probability density functions. This is a field that is increasingly attracting the interest of researchers from many different areas of science, including mathematics, statistics, geometry, computer science, signal processing, physics and neuroscience. It is the authors’ hope that the present book will be a valuable reference for researchers and graduate students in one of the aforementioned fields. This textbook is a unified presentation of differential geometry and probability theory, and constitutes a text for a course directed at graduate or advanced undergraduate students interested in applications of differential geometry in probability and statistics. The book contains over 100 proposed exercises meant to help students deepen their understanding, and it is accompanied by software that is able to provide numerical computations of several information geometric objects. The reader...

Bayesian optimization for computationally extensive probability distributions.

Science.gov (United States)

Tamura, Ryo; Hukushima, Koji

2018-01-01

An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique. A key idea of the proposed method is to use extreme values of acquisition functions by Gaussian processes for the next training phase, which should be located near a local maximum or a global maximum of the probability distribution. Our Bayesian optimization technique is applied to the posterior distribution in the effective physical model estimation, which is a computationally extensive probability distribution. Even when the number of sampling points on the posterior distributions is fixed to be small, the Bayesian optimization provides a better maximizer of the posterior distributions in comparison to those by the random search method, the steepest descent method, or the Monte Carlo method. Furthermore, the Bayesian optimization improves the results efficiently by combining the steepest descent method and thus it is a powerful tool to search for a better maximizer of computationally extensive probability distributions.

Characteristic length of the knotting probability revisited

International Nuclear Information System (INIS)

Uehara, Erica; Deguchi, Tetsuo

2015-01-01

We present a self-avoiding polygon (SAP) model for circular DNA in which the radius of impermeable cylindrical segments corresponds to the screening length of double-stranded DNA surrounded by counter ions. For the model we evaluate the probability for a generated SAP with N segments having a given knot K through simulation. We call it the knotting probability of a knot K with N segments for the SAP model. We show that when N is large the most significant factor in the knotting probability is given by the exponentially decaying part exp(−N/N K ), where the estimates of parameter N K are consistent with the same value for all the different knots we investigated. We thus call it the characteristic length of the knotting probability. We give formulae expressing the characteristic length as a function of the cylindrical radius r ex , i.e. the screening length of double-stranded DNA. (paper)

Crash probability estimation via quantifying driver hazard perception.

Science.gov (United States)

Li, Yang; Zheng, Yang; Wang, Jianqiang; Kodaka, Kenji; Li, Keqiang

2018-07-01

Crash probability estimation is an important method to predict the potential reduction of crash probability contributed by forward collision avoidance technologies (FCATs). In this study, we propose a practical approach to estimate crash probability, which combines a field operational test and numerical simulations of a typical rear-end crash model. To consider driver hazard perception characteristics, we define a novel hazard perception measure, called as driver risk response time, by considering both time-to-collision (TTC) and driver braking response to impending collision risk in a near-crash scenario. Also, we establish a driving database under mixed Chinese traffic conditions based on a CMBS (Collision Mitigation Braking Systems)-equipped vehicle. Applying the crash probability estimation in this database, we estimate the potential decrease in crash probability owing to use of CMBS. A comparison of the results with CMBS on and off shows a 13.7% reduction of crash probability in a typical rear-end near-crash scenario with a one-second delay of driver's braking response. These results indicate that CMBS is positive in collision prevention, especially in the case of inattentive drivers or ole drivers. The proposed crash probability estimation offers a practical way for evaluating the safety benefits in the design and testing of FCATs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Probability Weighting as Evolutionary Second-best

OpenAIRE

Herold, Florian; Netzer, Nick

2011-01-01

The economic concept of the second-best involves the idea that multiple simultaneous deviations from a hypothetical first-best optimum may be optimal once the first-best itself can no longer be achieved, since one distortion may partially compensate for another. Within an evolutionary framework, we translate this concept to behavior under uncertainty. We argue that the two main components of prospect theory, the value function and the probability weighting function, are complements in the sec...

Correlation functions for Hermitian many-body systems: Necessary conditions

International Nuclear Information System (INIS)

Brown, E.B.

1994-01-01

Lee [Phys. Rev. B 47, 8293 (1993)] has shown that the odd-numbered derivatives of the Kubo autocorrelation function vanish at t=0. We show that this condition is based on a more general property of nondiagonal Kubo correlation functions. This general property provides that certain functional forms (e.g., simple exponential decay) are not admissible for any symmetric or antisymmetric Kubo correlation function in a Hermitian many-body system. Lee's result emerges as a special case of this result. Applications to translationally invariant systems and systems with rotational symmetries are also demonstrated

Examining the association between male circumcision and sexual function: evidence from a British probability survey.

Science.gov (United States)

Homfray, Virginia; Tanton, Clare; Mitchell, Kirstin R; Miller, Robert F; Field, Nigel; Macdowall, Wendy; Wellings, Kaye; Sonnenberg, Pam; Johnson, Anne M; Mercer, Catherine H

2015-07-17

Despite biological advantages of male circumcision in reducing HIV/sexually transmitted infection acquisition, concern is often expressed that it may reduce sexual enjoyment and function. We examine the association between circumcision and sexual function among sexually active men in Britain using data from Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3). Natsal-3 asked about circumcision and included a validated measure of sexual function, the Natsal-SF, which takes into account not only sexual difficulties but also the relationship context and overall level of satisfaction. A stratified probability survey of 6293 men and 8869 women aged 16-74 years, resident in Britain, undertaken 2010-2012, using computer-assisted face-to-face interviewing with computer-assisted self-interview for the more sensitive questions. Logistic regression was used to calculate odds ratios (ORs) to examine the association between reporting male circumcision and aspects of sexual function among sexually active men (n = 4816). The prevalence of male circumcision in Britain was 20.7% [95% confidence interval (CI): 19.3-21.8]. There was no association between male circumcision and, being in the lowest quintile of scores for the Natsal-SF, an indicator of poorer sexual function (adjusted OR: 0.95, 95% CI: 0.76-1.18). Circumcised men were as likely as uncircumcised men to report the specific sexual difficulties asked about in Natsal-3, except that a larger proportion of circumcised men reported erectile difficulties. This association was of borderline statistical significance after adjusting for age and relationship status (adjusted OR: 1.27, 95% CI: 0.99-1.63). Data from a large, nationally representative British survey suggest that circumcision is not associated with men's overall sexual function at a population level.

Covariate-adjusted Spearman's rank correlation with probability-scale residuals.

Science.gov (United States)

Liu, Qi; Li, Chun; Wanga, Valentine; Shepherd, Bryan E

2018-06-01

It is desirable to adjust Spearman's rank correlation for covariates, yet existing approaches have limitations. For example, the traditionally defined partial Spearman's correlation does not have a sensible population parameter, and the conditional Spearman's correlation defined with copulas cannot be easily generalized to discrete variables. We define population parameters for both partial and conditional Spearman's correlation through concordance-discordance probabilities. The definitions are natural extensions of Spearman's rank correlation in the presence of covariates and are general for any orderable random variables. We show that they can be neatly expressed using probability-scale residuals (PSRs). This connection allows us to derive simple estimators. Our partial estimator for Spearman's correlation between X and Y adjusted for Z is the correlation of PSRs from models of X on Z and of Y on Z, which is analogous to the partial Pearson's correlation derived as the correlation of observed-minus-expected residuals. Our conditional estimator is the conditional correlation of PSRs. We describe estimation and inference, and highlight the use of semiparametric cumulative probability models, which allow preservation of the rank-based nature of Spearman's correlation. We conduct simulations to evaluate the performance of our estimators and compare them with other popular measures of association, demonstrating their robustness and efficiency. We illustrate our method in two applications, a biomarker study and a large survey. © 2017, The International Biometric Society.

Time-averaged probability density functions of soot nanoparticles along the centerline of a piloted turbulent diffusion flame using a scanning mobility particle sizer

KAUST Repository

Chowdhury, Snehaunshu; Boyette, Wesley; Roberts, William L.

2017-01-01

In this study, we demonstrate the use of a scanning mobility particle sizer (SMPS) as an effective tool to measure the probability density functions (PDFs) of soot nanoparticles in turbulent flames. Time-averaged soot PDFs necessary for validating

STADIC: a computer code for combining probability distributions

International Nuclear Information System (INIS)

Cairns, J.J.; Fleming, K.N.

1977-03-01

The STADIC computer code uses a Monte Carlo simulation technique for combining probability distributions. The specific function for combination of the input distribution is defined by the user by introducing the appropriate FORTRAN statements to the appropriate subroutine. The code generates a Monte Carlo sampling from each of the input distributions and combines these according to the user-supplied function to provide, in essence, a random sampling of the combined distribution. When the desired number of samples is obtained, the output routine calculates the mean, standard deviation, and confidence limits for the resultant distribution. This method of combining probability distributions is particularly useful in cases where analytical approaches are either too difficult or undefined

Use of probability tables for propagating uncertainties in neutronics

International Nuclear Information System (INIS)

Coste-Delclaux, M.; Diop, C.M.; Lahaye, S.

2017-01-01

Highlights: • Moment-based probability table formalism is described. • Representation by probability tables of any uncertainty distribution is established. • Multiband equations for two kinds of uncertainty propagation problems are solved. • Numerical examples are provided and validated against Monte Carlo simulations. - Abstract: Probability tables are a generic tool that allows representing any random variable whose probability density function is known. In the field of nuclear reactor physics, this tool is currently used to represent the variation of cross-sections versus energy (neutron transport codes TRIPOLI4®, MCNP, APOLLO2, APOLLO3®, ECCO/ERANOS…). In the present article we show how we can propagate uncertainties, thanks to a probability table representation, through two simple physical problems: an eigenvalue problem (neutron multiplication factor) and a depletion problem.

On the regularity of the extinction probability of a branching process in varying and random environments

International Nuclear Information System (INIS)

Alili, Smail; Rugh, Hans Henrik

2008-01-01

We consider a supercritical branching process in time-dependent environment ξ. We assume that the offspring distributions depend regularly (C k or real-analytically) on real parameters λ. We show that the extinction probability q λ (ξ), given the environment ξ 'inherits' this regularity whenever the offspring distributions satisfy a condition of contraction-type. Our proof makes use of the Poincaré metric on the complex unit disc and a real-analytic implicit function theorem

On Probability Leakage

OpenAIRE

Briggs, William M.

2012-01-01

The probability leakage of model M with respect to evidence E is defined. Probability leakage is a kind of model error. It occurs when M implies that events $y$, which are impossible given E, have positive probability. Leakage does not imply model falsification. Models with probability leakage cannot be calibrated empirically. Regression models, which are ubiquitous in statistical practice, often evince probability leakage.

Evaluation of the divided attention condition during functional analyses.

Science.gov (United States)

Fahmie, Tara A; Iwata, Brian A; Harper, Jill M; Querim, Angie C

2013-01-01

A common condition included in most functional analyses (FAs) is the attention condition, in which the therapist ignores the client by engaging in a solitary activity (antecedent event) but delivers attention to the client contingent on problem behavior (consequent event). The divided attention condition is similar, except that the antecedent event consists of the therapist conversing with an adult confederate. We compared the typical and divided attention conditions to determine whether behavior in general (Study 1) and problem behavior in particular (Study 2) were more sensitive to one of the test conditions. Results showed that the divided attention condition resulted in faster acquisition or more efficient FA results for 2 of 9 subjects, suggesting that the divided attention condition could be considered a preferred condition when resources are available. © Society for the Experimental Analysis of Behavior.

Comparison of density estimators. [Estimation of probability density functions

Energy Technology Data Exchange (ETDEWEB)

Kao, S.; Monahan, J.F.

1977-09-01

Recent work in the field of probability density estimation has included the introduction of some new methods, such as the polynomial and spline methods and the nearest neighbor method, and the study of asymptotic properties in depth. This earlier work is summarized here. In addition, the computational complexity of the various algorithms is analyzed, as are some simulations. The object is to compare the performance of the various methods in small samples and their sensitivity to change in their parameters, and to attempt to discover at what point a sample is so small that density estimation can no longer be worthwhile. (RWR)

Non-equilibrium random matrix theory. Transition probabilities

International Nuclear Information System (INIS)

Pedro, Francisco Gil; Westphal, Alexander

2016-06-01

In this letter we present an analytic method for calculating the transition probability between two random Gaussian matrices with given eigenvalue spectra in the context of Dyson Brownian motion. We show that in the Coulomb gas language, in large N limit, memory of the initial state is preserved in the form of a universal linear potential acting on the eigenvalues. We compute the likelihood of any given transition as a function of time, showing that as memory of the initial state is lost, transition probabilities converge to those of the static ensemble.

Non-equilibrium random matrix theory. Transition probabilities

Energy Technology Data Exchange (ETDEWEB)

Pedro, Francisco Gil [Univ. Autonoma de Madrid (Spain). Dept. de Fisica Teorica; Westphal, Alexander [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Gruppe Theorie

2016-06-15

In this letter we present an analytic method for calculating the transition probability between two random Gaussian matrices with given eigenvalue spectra in the context of Dyson Brownian motion. We show that in the Coulomb gas language, in large N limit, memory of the initial state is preserved in the form of a universal linear potential acting on the eigenvalues. We compute the likelihood of any given transition as a function of time, showing that as memory of the initial state is lost, transition probabilities converge to those of the static ensemble.

Communication: Two types of flat-planes conditions in density functional theory

Energy Technology Data Exchange (ETDEWEB)

Yang, Xiaotian Derrick; Patel, Anand H. G.; González-Espinoza, Cristina E.; Ayers, Paul W. [Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario LBS 4M1 (Canada); Miranda-Quintana, Ramón Alain [Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario LBS 4M1 (Canada); Laboratory of Computational and Theoretical Chemistry, Faculty of Chemistry, University of Havana, Havana (Cuba); Heidar-Zadeh, Farnaz [Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario LBS 4M1 (Canada); Department of Inorganic and Physical Chemistry, Ghent University, Krijgslaan 281 (S3), 9000 Gent (Belgium); Center for Molecular Modeling, Ghent University, Technologiepark 903, 9052 Zwijnaarde (Belgium)

2016-07-21

Using results from atomic spectroscopy, we show that there are two types of flat-planes conditions. The first type of flat-planes condition occurs when the energy as a function of the number of electrons of each spin, N{sub α} and N{sub β}, has a derivative discontinuity on a line segment where the number of electrons, N{sub α} + N{sub β}, is an integer. The second type of flat-planes condition occurs when the energy has a derivative discontinuity on a line segment where the spin polarization, N{sub α} – N{sub β}, is an integer, but does not have a discontinuity associated with an integer number of electrons. Type 2 flat planes are rare—we observed just 15 type 2 flat-planes conditions out of the 4884 cases we tested—but their mere existence has implications for the design of exchange-correlation energy density functionals. To facilitate the development of functionals that have the correct behavior with respect to both fractional number of electrons and fractional spin polarization, we present a dataset for the chromium atom and its ions that can be used to test new functionals.

Height probabilities in the Abelian sandpile model on the generalized finite Bethe lattice

Science.gov (United States)

Chen, Haiyan; Zhang, Fuji

2013-08-01

In this paper, we study the sandpile model on the generalized finite Bethe lattice with a particular boundary condition. Using a combinatorial method, we give the exact expressions for all single-site probabilities and some two-site joint probabilities. As a by-product, we prove that the height probabilities of bulk vertices are all the same for the Bethe lattice with certain given boundary condition, which was found from numerical evidence by Grassberger and Manna ["Some more sandpiles," J. Phys. (France) 51, 1077-1098 (1990)], 10.1051/jphys:0199000510110107700 but without a proof.

NESTEM-QRAS: A Tool for Estimating Probability of Failure

Science.gov (United States)

Patel, Bhogilal M.; Nagpal, Vinod K.; Lalli, Vincent A.; Pai, Shantaram; Rusick, Jeffrey J.

2002-10-01

An interface between two NASA GRC specialty codes, NESTEM and QRAS has been developed. This interface enables users to estimate, in advance, the risk of failure of a component, a subsystem, and/or a system under given operating conditions. This capability would be able to provide a needed input for estimating the success rate for any mission. NESTEM code, under development for the last 15 years at NASA Glenn Research Center, has the capability of estimating probability of failure of components under varying loading and environmental conditions. This code performs sensitivity analysis of all the input variables and provides their influence on the response variables in the form of cumulative distribution functions. QRAS, also developed by NASA, assesses risk of failure of a system or a mission based on the quantitative information provided by NESTEM or other similar codes, and user provided fault tree and modes of failure. This paper will describe briefly, the capabilities of the NESTEM, QRAS and the interface. Also, in this presentation we will describe stepwise process the interface uses using an example.

NESTEM-QRAS: A Tool for Estimating Probability of Failure

Science.gov (United States)

Patel, Bhogilal M.; Nagpal, Vinod K.; Lalli, Vincent A.; Pai, Shantaram; Rusick, Jeffrey J.

2002-01-01

An interface between two NASA GRC specialty codes, NESTEM and QRAS has been developed. This interface enables users to estimate, in advance, the risk of failure of a component, a subsystem, and/or a system under given operating conditions. This capability would be able to provide a needed input for estimating the success rate for any mission. NESTEM code, under development for the last 15 years at NASA Glenn Research Center, has the capability of estimating probability of failure of components under varying loading and environmental conditions. This code performs sensitivity analysis of all the input variables and provides their influence on the response variables in the form of cumulative distribution functions. QRAS, also developed by NASA, assesses risk of failure of a system or a mission based on the quantitative information provided by NESTEM or other similar codes, and user provided fault tree and modes of failure. This paper will describe briefly, the capabilities of the NESTEM, QRAS and the interface. Also, in this presentation we will describe stepwise process the interface uses using an example.

Conserving relativistic many-body approach: Equation of state, spectral function, and occupation probabilities of nuclear matter

International Nuclear Information System (INIS)

de Jong, F.; Malfliet, R.

1991-01-01

Starting from a relativistic Lagrangian we derive a ''conserving'' approximation for the description of nuclear matter. We show this to be a nontrivial extension over the relativistic Dirac-Brueckner scheme. The saturation point of the equation of state calculated agrees very well with the empirical saturation point. The conserving character of the approach is tested by means of the Hugenholtz--van Hove theorem. We find the theorem fulfilled very well around saturation. A new value for compression modulus is derived, K=310 MeV. Also we calculate the occupation probabilities at normal nuclear matter densities by means of the spectral function. The average depletion κ of the Fermi sea is found to be κ∼0.11

The probability of object-scene co-occurrence influences object identification processes.

Science.gov (United States)

Sauvé, Geneviève; Harmand, Mariane; Vanni, Léa; Brodeur, Mathieu B

2017-07-01

Contextual information allows the human brain to make predictions about the identity of objects that might be seen and irregularities between an object and its background slow down perception and identification processes. Bar and colleagues modeled the mechanisms underlying this beneficial effect suggesting that the brain stocks information about the statistical regularities of object and scene co-occurrence. Their model suggests that these recurring regularities could be conceptualized along a continuum in which the probability of seeing an object within a given scene can be high (probable condition), moderate (improbable condition) or null (impossible condition). In the present experiment, we propose to disentangle the electrophysiological correlates of these context effects by directly comparing object-scene pairs found along this continuum. We recorded the event-related potentials of 30 healthy participants (18-34 years old) and analyzed their brain activity in three time windows associated with context effects. We observed anterior negativities between 250 and 500 ms after object onset for the improbable and impossible conditions (improbable more negative than impossible) compared to the probable condition as well as a parieto-occipital positivity (improbable more positive than impossible). The brain may use different processing pathways to identify objects depending on whether the probability of co-occurrence with the scene is moderate (rely more on top-down effects) or null (rely more on bottom-up influences). The posterior positivity could index error monitoring aimed to ensure that no false information is integrated into mental representations of the world.

Conditionally exponential convex functions on locally compact groups

International Nuclear Information System (INIS)

Okb El-Bab, A.S.

1992-09-01

The main results of the thesis are: 1) The construction of a compact base for the convex cone of all conditionally exponential convex functions. 2) The determination of the extreme parts of this cone. Some supplementary lemmas are proved for this purpose. (author). 8 refs

The influence of initial beliefs on judgments of probability.

Science.gov (United States)

Yu, Erica C; Lagnado, David A

2012-01-01

This study aims to investigate whether experimentally induced prior beliefs affect processing of evidence including the updating of beliefs under uncertainty about the unknown probabilities of outcomes and the structural, outcome-generating nature of the environment. Participants played a gambling task in the form of computer-simulated slot machines and were given information about the slot machines' possible outcomes without their associated probabilities. One group was induced with a prior belief about the outcome space that matched the space of actual outcomes to be sampled; the other group was induced with a skewed prior belief that included the actual outcomes and also fictional higher outcomes. In reality, however, all participants sampled evidence from the same underlying outcome distribution, regardless of priors given. Before and during sampling, participants expressed their beliefs about the outcome distribution (values and probabilities). Evaluation of those subjective probability distributions suggests that all participants' judgments converged toward the observed outcome distribution. However, despite observing no supporting evidence for fictional outcomes, a significant proportion of participants in the skewed priors condition expected them in the future. A probe of the participants' understanding of the underlying outcome-generating processes indicated that participants' judgments were based on the information given in the induced priors and consequently, a significant proportion of participants in the skewed condition believed the slot machines were not games of chance while participants in the control condition believed the machines generated outcomes at random. Beyond Bayesian or heuristic belief updating, priors not only contribute to belief revision but also affect one's deeper understanding of the environment.

Quantum probabilities as Dempster-Shafer probabilities in the lattice of subspaces

International Nuclear Information System (INIS)

Vourdas, A.

2014-01-01

The orthocomplemented modular lattice of subspaces L[H(d)], of a quantum system with d-dimensional Hilbert space H(d), is considered. A generalized additivity relation which holds for Kolmogorov probabilities is violated by quantum probabilities in the full lattice L[H(d)] (it is only valid within the Boolean subalgebras of L[H(d)]). This suggests the use of more general (than Kolmogorov) probability theories, and here the Dempster-Shafer probability theory is adopted. An operator D(H 1 ,H 2 ), which quantifies deviations from Kolmogorov probability theory is introduced, and it is shown to be intimately related to the commutator of the projectors P(H 1 ),P(H 2 ), to the subspaces H 1 , H 2 . As an application, it is shown that the proof of the inequalities of Clauser, Horne, Shimony, and Holt for a system of two spin 1/2 particles is valid for Kolmogorov probabilities, but it is not valid for Dempster-Shafer probabilities. The violation of these inequalities in experiments supports the interpretation of quantum probabilities as Dempster-Shafer probabilities

Domestic wells have high probability of pumping septic tank leachate

Science.gov (United States)

Bremer, J. E.; Harter, T.

2012-08-01

Onsite wastewater treatment systems are common in rural and semi-rural areas around the world; in the US, about 25-30% of households are served by a septic (onsite) wastewater treatment system, and many property owners also operate their own domestic well nearby. Site-specific conditions and local groundwater flow are often ignored when installing septic systems and wells. In areas with small lots (thus high spatial septic system densities), shallow domestic wells are prone to contamination by septic system leachate. Mass balance approaches have been used to determine a maximum septic system density that would prevent contamination of groundwater resources. In this study, a source area model based on detailed groundwater flow and transport modeling is applied for a stochastic analysis of domestic well contamination by septic leachate. Specifically, we determine the probability that a source area overlaps with a septic system drainfield as a function of aquifer properties, septic system density and drainfield size. We show that high spatial septic system density poses a high probability of pumping septic system leachate. The hydraulic conductivity of the aquifer has a strong influence on the intersection probability. We find that mass balance calculations applied on a regional scale underestimate the contamination risk of individual drinking water wells by septic systems. This is particularly relevant for contaminants released at high concentrations, for substances that experience limited attenuation, and those that are harmful even at low concentrations (e.g., pathogens).

Domestic wells have high probability of pumping septic tank leachate

Directory of Open Access Journals (Sweden)

J. E. Bremer

2012-08-01

Full Text Available Onsite wastewater treatment systems are common in rural and semi-rural areas around the world; in the US, about 25–30% of households are served by a septic (onsite wastewater treatment system, and many property owners also operate their own domestic well nearby. Site-specific conditions and local groundwater flow are often ignored when installing septic systems and wells. In areas with small lots (thus high spatial septic system densities, shallow domestic wells are prone to contamination by septic system leachate. Mass balance approaches have been used to determine a maximum septic system density that would prevent contamination of groundwater resources. In this study, a source area model based on detailed groundwater flow and transport modeling is applied for a stochastic analysis of domestic well contamination by septic leachate. Specifically, we determine the probability that a source area overlaps with a septic system drainfield as a function of aquifer properties, septic system density and drainfield size. We show that high spatial septic system density poses a high probability of pumping septic system leachate. The hydraulic conductivity of the aquifer has a strong influence on the intersection probability. We find that mass balance calculations applied on a regional scale underestimate the contamination risk of individual drinking water wells by septic systems. This is particularly relevant for contaminants released at high concentrations, for substances that experience limited attenuation, and those that are harmful even at low concentrations (e.g., pathogens.

Analytical and numerical studies of creation probabilities of hierarchical trees

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S.S. Borysov

2011-03-01

Full Text Available We consider the creation conditions of diverse hierarchical trees both analytically and numerically. A connection between the probabilities to create hierarchical levels and the probability to associate these levels into a united structure is studied. We argue that a consistent probabilistic picture requires the use of deformed algebra. Our consideration is based on the study of the main types of hierarchical trees, among which both regular and degenerate ones are studied analytically, while the creation probabilities of Fibonacci, scale-free and arbitrary trees are determined numerically.

Representation of Probability Density Functions from Orbit Determination using the Particle Filter

Science.gov (United States)

Mashiku, Alinda K.; Garrison, James; Carpenter, J. Russell

2012-01-01

Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty. In order to obtain an accurate representation of the probability density function (PDF) that incorporates higher order statistical information, we propose the use of nonlinear estimation methods such as the Particle Filter. The Particle Filter (PF) is capable of providing a PDF representation of the state estimates whose accuracy is dependent on the number of particles or samples used. For this method to be applicable to real case scenarios, we need a way of accurately representing the PDF in a compressed manner with little information loss. Hence we propose using the Independent Component Analysis (ICA) as a non-Gaussian dimensional reduction method that is capable of maintaining higher order statistical information obtained using the PF. Methods such as the Principal Component Analysis (PCA) are based on utilizing up to second order statistics, hence will not suffice in maintaining maximum information content. Both the PCA and the ICA are applied to two scenarios that involve a highly eccentric orbit with a lower apriori uncertainty covariance and a less eccentric orbit with a higher a priori uncertainty covariance, to illustrate the capability of the ICA in relation to the PCA.

Oil spill contamination probability in the southeastern Levantine basin.

Science.gov (United States)

Goldman, Ron; Biton, Eli; Brokovich, Eran; Kark, Salit; Levin, Noam

2015-02-15

Recent gas discoveries in the eastern Mediterranean Sea led to multiple operations with substantial economic interest, and with them there is a risk of oil spills and their potential environmental impacts. To examine the potential spatial distribution of this threat, we created seasonal maps of the probability of oil spill pollution reaching an area in the Israeli coastal and exclusive economic zones, given knowledge of its initial sources. We performed simulations of virtual oil spills using realistic atmospheric and oceanic conditions. The resulting maps show dominance of the alongshore northerly current, which causes the high probability areas to be stretched parallel to the coast, increasing contamination probability downstream of source points. The seasonal westerly wind forcing determines how wide the high probability areas are, and may also restrict these to a small coastal region near source points. Seasonal variability in probability distribution, oil state, and pollution time is also discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

On a paradox of probability theory

International Nuclear Information System (INIS)

Stuart, C.I.J.M.

1989-01-01

Costa de Beauregard's proposal concerning physical retrocausality has been shown to fail on two crucial points. However, it is argued that his proposal still merits serious attention. The argument arises from showing that his proposal reveals a paradox involving relations between conditional probabilities, statistical correlations and reciprocal causalities of the type exhibited by cooperative dynamics in physical systems. 4 refs. (Author)

I. Fission Probabilities, Fission Barriers, and Shell Effects. II. Particle Structure Functions

Energy Technology Data Exchange (ETDEWEB)

Jing, Kexing [Univ. of California, Berkeley, CA (United States)

1999-05-01

In Part I, fission excitation functions of osmium isotopes ^{185,186, 187, 189} Os produced in ³He +^{182,183, 184, 186}W reactions, and of polonium isotopes ^{209,210, 211, 212}Po produced in ³He/⁴He + ^{206, 207, 208}Pb reactions, were measured with high precision. These excitation functions have been analyzed in detail based upon the transition state formalism. The fission barriers, and shell effects for the corresponding nuclei are extracted from the detailed analyses. A novel approach has been developed to determine upper limits of the transient time of the fission process. The upper limits are constrained by the fission probabilities of neighboring isotopes. The upper limits for the transient time set with this new method are 15x 10^–21 sec and 25x 10^–21 sec for 0s and Po compound nuclei, respectively. In Part II, we report on a search for evidence of the optical modulations in the energy spectra of alpha particles emitted from hot compound nuclei. The optical modulations are expected to arise from the ~-particle interaction with the rest of the nucleus as the particle prepares to exit. Some evidence for the modulations has been observed in the alpha spectra measured in the 3He-induced reactions, ³He + ^natAg in particular. The identification of the modulations involves a technique that subtracts the bulk statistical background from the measured alpha spectra, in order for the modulations to become visible in the residuals. Due to insufficient knowledge of the background spectra, however, the presented evidence should only be regarded as preliminary and tentative.

Interpretation of the results of statistical measurements. [search for basic probability model

Science.gov (United States)

Olshevskiy, V. V.

1973-01-01

For random processes, the calculated probability characteristic, and the measured statistical estimate are used in a quality functional, which defines the difference between the two functions. Based on the assumption that the statistical measurement procedure is organized so that the parameters for a selected model are optimized, it is shown that the interpretation of experimental research is a search for a basic probability model.

Quantization conditions and functional equations in ABJ(M) theories

International Nuclear Information System (INIS)

Grassi, Alba; Marino, Marcos; Hatsuda, Yasuyuki

2014-12-01

The partition function of ABJ(M) theories on the three-sphere can be regarded as the canonical partition function of an ideal Fermi gas with a non-trivial Hamiltonian. We propose an exact expression for the spectral determinant of this Hamiltonian, which generalizes recent results obtained in the maximally supersymmetric case. As a consequence, we find an exact WKB quantization condition determining the spectrum which is in agreement with numerical results. In addition, we investigate the factorization properties and functional equations for our conjectured spectral determinants. These functional equations relate the spectral determinants of ABJ theories with consecutive ranks of gauge groups but the same Chern-Simons coupling.

LARF: Instrumental Variable Estimation of Causal Effects through Local Average Response Functions

Directory of Open Access Journals (Sweden)

Weihua An

2016-07-01

Full Text Available LARF is an R package that provides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument (i.e., the treatment inducement are binary. The method (Abadie 2003 involves two steps. First, pseudo-weights are constructed from the probability of receiving the treatment inducement. By default LARF estimates the probability by a probit regression. It also provides semiparametric power series estimation of the probability and allows users to employ other external methods to estimate the probability. Second, the pseudo-weights are used to estimate the local average response function conditional on treatment and covariates. LARF provides both least squares and maximum likelihood estimates of the conditional treatment effects.

Changes in working conditions and physical health functioning among midlife and ageing employees.

Science.gov (United States)

Mänty, Minna; Kouvonen, Anne; Lallukka, Tea; Lahti, Jouni; Lahelma, Eero; Rahkonen, Ossi

2015-11-01

The aim this study was to examine the effect of changes in physical and psychosocial working conditions on physical health functioning among ageing municipal employees. Follow-up survey data were collected from midlife employees of the City of Helsinki, Finland, at three time points: wave 1 (2000-2002), wave 2 (2007), and wave 3 (2012). Changes in physical and psychosocial working conditions were assessed between waves 1 and 2. Physical health functioning was measured by the physical component summary (PCS) of the Short-Form 36 questionnaire at each of the three waves. In total, 2784 respondents (83% women) who remained employed over the follow-up were available for the analyses. Linear mixed-effect models were used to assess the associations and adjust for key covariates (age, gender, obesity, chronic diseases, and health behaviors). Repeated and increased exposure to adverse physical working conditions was associated with greater decline in physical health functioning over time. In contrast, decrease in exposures reduced the decline. Of the psychosocial working conditions, changes in job demands had no effects on physical health functioning. However, decreased job control was associated with greater decline and repeated high or increased job control reduced the decline in physical health functioning over time. Adverse changes in physical working conditions and job control were associated with greater decline in physical health functioning over time, whereas favorable changes in these exposures reduced the decline. Preventing deterioration and promoting improvement of working conditions are likely to help maintain better physical health functioning among ageing employees.

Conditional Moment Closure Modelling of a Lifted H2/N2 Turbulent Jet Flame Using the Presumed Mapping Function Approach

Directory of Open Access Journals (Sweden)

Ahmad El Sayed

2015-01-01

Full Text Available A lifted hydrogen/nitrogen turbulent jet flame issuing into a vitiated coflow is investigated using the conditional moment closure (CMC supplemented by the presumed mapping function (PMF approach for the modelling of conditional mixing and velocity statistics. Using a prescribed reference field, the PMF approach yields a presumed probability density function (PDF for the mixture fraction, which is then used in closing the conditional scalar dissipation rate (CSDR and conditional velocity in a fully consistent manner. These closures are applied to a lifted flame and the findings are compared to previous results obtained using β-PDF-based closures over a range of coflow temperatures (Tc. The PMF results are in line with those of the β-PDF and compare well to measurements. The transport budgets in mixture fraction and physical spaces and the radical history ahead of the stabilisation height indicate that the stabilisation mechanism is susceptible to Tc. As in the previous β-PDF calculations, autoignition around the “most reactive” mixture fraction remains the controlling mechanism for sufficiently high Tc. Departure from the β-PDF predictions is observed when Tc is decreased as PMF predicts stabilisation by means of premixed flame propagation. This conclusion is based on the observation that lean mixtures are heated by downstream burning mixtures in a preheat zone developing ahead of the stabilization height. The spurious sources, which stem from inconsistent CSDR modelling, are further investigated. The findings reveal that their effect is small but nonnegligible, most notably within the flame zone.

Models for probability and statistical inference theory and applications

CERN Document Server

Stapleton, James H

2007-01-01

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses mo...

Effort, anhedonia, and function in schizophrenia: reduced effort allocation predicts amotivation and functional impairment.

Science.gov (United States)

Barch, Deanna M; Treadway, Michael T; Schoen, Nathan

2014-05-01

One of the most debilitating aspects of schizophrenia is an apparent interest in or ability to exert effort for rewards. Such "negative symptoms" may prevent individuals from obtaining potentially beneficial outcomes in educational, occupational, or social domains. In animal models, dopamine abnormalities decrease willingness to work for rewards, implicating dopamine (DA) function as a candidate substrate for negative symptoms given that schizophrenia involves dysregulation of the dopamine system. We used the effort-expenditure for rewards task (EEfRT) to assess the degree to which individuals with schizophrenia were wiling to exert increased effort for either larger magnitude rewards or for rewards that were more probable. Fifty-nine individuals with schizophrenia and 39 demographically similar controls performed the EEfRT task, which involves making choices between "easy" and "hard" tasks to earn potential rewards. Individuals with schizophrenia showed less of an increase in effort allocation as either reward magnitude or probability increased. In controls, the frequency of choosing the hard task in high reward magnitude and probability conditions was negatively correlated with depression severity and anhedonia. In schizophrenia, fewer hard task choices were associated with more severe negative symptoms and worse community and work function as assessed by a caretaker. Consistent with patterns of disrupted dopamine functioning observed in animal models of schizophrenia, these results suggest that 1 mechanism contributing to impaired function and motivational drive in schizophrenia may be a reduced allocation of greater effort for higher magnitude or higher probability rewards.

Probability 1/e

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Koo, Reginald; Jones, Martin L.

2011-01-01

Quite a number of interesting problems in probability feature an event with probability equal to 1/e. This article discusses three such problems and attempts to explain why this probability occurs with such frequency.

The paradoxical effect of low reward probabilities in suboptimal choice.

Science.gov (United States)

Fortes, Inês; Pinto, Carlos; Machado, Armando; Vasconcelos, Marco

2018-04-01

When offered a choice between 2 alternatives, animals sometimes prefer the option yielding less food. For instance, pigeons and starlings prefer an option that on 20% of the trials presents a stimulus always followed by food, and on the remaining 80% of the trials presents a stimulus never followed by food (the Informative Option), over an option that provides food on 50% of the trials regardless of the stimulus presented (the Noninformative Option). To explain this suboptimal behavior, it has been hypothesized that animals ignore (or do not engage with) the stimulus that is never followed by food in the Informative Option. To assess when pigeons attend to the stimulus usually not followed by food, we increased the probability of reinforcement, p, in the presence of that stimulus. Across 2 experiments, we found that the value of the Informative Option decreased with p. To account for the results, we added to the Reinforcement Rate Model (and also to the Hyperbolic Discounting Model) an engagement function, f(p), that specified the likelihood the animal attends to a stimulus followed by reward with probability p, and then derived the model predictions for 2 forms of f(p), a linear function, and an all-or-none threshold function. Both models predicted the observed findings with a linear engagement function: The higher the probability of reinforcement after a stimulus, the higher the probability of engaging the stimulus, and, surprisingly, the less the value of the option comprising the stimulus. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Effects of concurrent caffeine and mobile phone exposure on local target probability processing in the human brain.

Science.gov (United States)

Trunk, Attila; Stefanics, Gábor; Zentai, Norbert; Bacskay, Ivett; Felinger, Attila; Thuróczy, György; Hernádi, István

2015-09-23

Millions of people use mobile phones (MP) while drinking coffee or other caffeine containing beverages. Little is known about the potential combined effects of MP irradiation and caffeine on cognitive functions. Here we investigated whether caffeine intake and concurrent exposure to Universal Mobile Telecommunications System (UMTS) MP-like irradiation may interactively influence neuro-cognitive function in an active visual oddball paradigm. In a full factorial experimental design, 25 participants performed a simple visual target detection task while reaction time (RT) and electroencephalogram (EEG) was recorded. Target trials were divided into Low and High probability sets based on target-to-target distance. We analyzed single trial RT and alpha-band power (amplitude) in the pre-target interval. We found that RT was shorter in High vs. Low local probability trials, and caffeine further shortened RT in High probability trials relative to the baseline condition suggesting that caffeine improves the efficiency of implicit short-term memory. Caffeine also decreased pre-target alpha amplitude resulting in higher arousal level. Furthermore, pre-target gamma power positively correlated with RT, which may have facilitated target detection. However, in the present pharmacologically validated study UMTS exposure either alone or in combination with caffeine did not alter RT or pre-stimulus oscillatory brain activity.

Statistical tests for whether a given set of independent, identically distributed draws comes from a specified probability density.

Science.gov (United States)

Tygert, Mark

2010-09-21

We discuss several tests for determining whether a given set of independent and identically distributed (i.i.d.) draws does not come from a specified probability density function. The most commonly used are Kolmogorov-Smirnov tests, particularly Kuiper's variant, which focus on discrepancies between the cumulative distribution function for the specified probability density and the empirical cumulative distribution function for the given set of i.i.d. draws. Unfortunately, variations in the probability density function often get smoothed over in the cumulative distribution function, making it difficult to detect discrepancies in regions where the probability density is small in comparison with its values in surrounding regions. We discuss tests without this deficiency, complementing the classical methods. The tests of the present paper are based on the plain fact that it is unlikely to draw a random number whose probability is small, provided that the draw is taken from the same distribution used in calculating the probability (thus, if we draw a random number whose probability is small, then we can be confident that we did not draw the number from the same distribution used in calculating the probability).

Some applications of the fractional Poisson probability distribution

International Nuclear Information System (INIS)

Laskin, Nick

2009-01-01

Physical and mathematical applications of the recently invented fractional Poisson probability distribution have been presented. As a physical application, a new family of quantum coherent states has been introduced and studied. As mathematical applications, we have developed the fractional generalization of Bell polynomials, Bell numbers, and Stirling numbers of the second kind. The appearance of fractional Bell polynomials is natural if one evaluates the diagonal matrix element of the evolution operator in the basis of newly introduced quantum coherent states. Fractional Stirling numbers of the second kind have been introduced and applied to evaluate the skewness and kurtosis of the fractional Poisson probability distribution function. A representation of the Bernoulli numbers in terms of fractional Stirling numbers of the second kind has been found. In the limit case when the fractional Poisson probability distribution becomes the Poisson probability distribution, all of the above listed developments and implementations turn into the well-known results of the quantum optics and the theory of combinatorial numbers.

Prefrontal-limbic Functional Connectivity during Acquisition and Extinction of Conditioned Fear.

Science.gov (United States)

Barrett, Douglas W; Gonzalez-Lima, F

2018-04-15

This study is a new analysis to obtain novel metabolic data on the functional connectivity of prefrontal-limbic regions in Pavlovian fear acquisition and extinction of tone-footshock conditioning. Mice were analyzed with the fluorodeoxyglucose (FDG) autoradiographic method to metabolically map regional brain activity. New FDG data were sampled from the nuclei of the habenula and other regions implicated in aversive conditioning, such as infralimbic cortex, amygdala and periaqueductal gray regions. The activity patterns among these regions were inter-correlated during acquisition, extinction or pseudorandom training to develop a functional connectivity model. Two subdivisions of the habenular complex showed increased activity after acquisition relative to extinction, with the pseudorandom group intermediate between the other two groups. Significant acquisition activation effects were also found in centromedial amygdala, dorsomedial and ventrolateral periaqueductal gray. FDG uptake increases during extinction were found only in dorsal and ventral infralimbic cortex. The overall pattern of activity correlations between these regions revealed extensive but differential functional connectivity during acquisition and extinction training, with less functional connectivity found after pseudorandom training. Interestingly, habenula nuclei showed a distinct pattern of inter-correlations with amygdala nuclei during extinction. The functional connectivity model revealed changing interactions among infralimbic cortex, amygdala, habenula and periaqueductal gray regions through the stages of Pavlovian fear acquisition and extinction. This study provided new data on the contributions of the habenula to fear conditioning, and revealed previously unreported infralimbic-amygdala-habenula-periaqueductal gray interactions implicated in acquisition and extinction of conditioned fear. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Association Between Chronic Conditions and Physical Function Among Veteran and Non-Veteran Women With Diabetes

Science.gov (United States)

Gray, Kristen E.; Katon, Jodie G.; Rillamas-Sun, Eileen; Bastian, Lori A.; Nelson, Karin M.; LaCroix, Andrea Z.; Reiber, Gayle E.

2016-01-01

Abstract Purpose of the Study: To compare the number of chronic conditions among a list of 12 and their association with physical function among postmenopausal non-Veteran and Veteran women with diabetes. Design and Methods: Among women with diabetes from the Women’s Health Initiative, we compared the average number of chronic conditions between non-Veterans and Veterans and the association between total number of chronic conditions on subsequent RAND-36 physical function. To examine associations between each condition and subsequent physical function, we compared women with diabetes plus one chronic condition to women with diabetes alone using linear regression in separate models for each condition and for non-Veterans and Veterans. Results: Both non-Veterans ( N = 23,542) and Veterans ( N = 618) with diabetes had a median of 3 chronic conditions. Decreases in physical function for each additional condition were larger among Veterans than non-Veterans (−6.3 vs. −4.1 points). Decreases in physical function among women with diabetes plus one chronic condition were greater than that reported for diabetes alone for all combinations and were more pronounced among Veterans (non-Veterans: −11.1 to −24.2, Veterans: −16.6 to −40.4 points). Hip fracture, peripheral artery disease, cerebrovascular disease, and coronary disease in combination with diabetes were associated with the greatest decreases in physical function. Implications: Chronic conditions were common among postmenopausal women with diabetes and were associated with large declines in physical function, particularly among Veterans. Interventions to prevent and reduce the impact of these conditions and facilitate coordination of care among women with diabetes may help them maintain physical function. PMID:26768385

Probability distribution functions for ELM bursts in a series of JET tokamak discharges

International Nuclear Information System (INIS)

Greenhough, J; Chapman, S C; Dendy, R O; Ward, D J

2003-01-01

A novel statistical treatment of the full raw edge localized mode (ELM) signal from a series of previously studied JET plasmas is tested. The approach involves constructing probability distribution functions (PDFs) for ELM amplitudes and time separations, and quantifying the fit between the measured PDFs and model distributions (Gaussian, inverse exponential) and Poisson processes. Uncertainties inherent in the discreteness of the raw signal require the application of statistically rigorous techniques to distinguish ELM data points from background, and to extrapolate peak amplitudes. The accuracy of PDF construction is further constrained by the relatively small number of ELM bursts (several hundred) in each sample. In consequence the statistical technique is found to be difficult to apply to low frequency (typically Type I) ELMs, so the focus is narrowed to four JET plasmas with high frequency (typically Type III) ELMs. The results suggest that there may be several fundamentally different kinds of Type III ELMing process at work. It is concluded that this novel statistical treatment can be made to work, may have wider applications to ELM data, and has immediate practical value as an additional quantitative discriminant between classes of ELMing behaviour

Setting up tunneling conditions by means of Bohmian mechanics

Energy Technology Data Exchange (ETDEWEB)

Sanz, A S; Miret-Artes, S, E-mail: asanz@iff.csic.es, E-mail: s.miret@iff.csic.es [Instituto de Fisica Fundamental-CSIC, Serrano 123, 28006 Madrid (Spain)

2011-12-02

Usually tunneling is established after imposing some matching conditions on the (time-independent) wavefunction and its first derivative at the boundaries of a barrier. Here an alternative scheme is proposed to determine tunneling and estimate transmission probabilities in time-dependent problems, which takes advantage of the trajectory picture provided by Bohmian mechanics. From this theory, a general functional expression for the transmission probability in terms of the system initial state can be reached. This expression is used here to analyze tunneling properties and estimate transmissions in the case of initial Gaussian wave packets colliding with ramp-like barriers. (paper)

Selected papers on analysis, probability, and statistics

CERN Document Server

Nomizu, Katsumi

1994-01-01

This book presents papers that originally appeared in the Japanese journal Sugaku. The papers fall into the general area of mathematical analysis as it pertains to probability and statistics, dynamical systems, differential equations and analytic function theory. Among the topics discussed are: stochastic differential equations, spectra of the Laplacian and Schrödinger operators, nonlinear partial differential equations which generate dissipative dynamical systems, fractal analysis on self-similar sets and the global structure of analytic functions.

Estimated Probability of Traumatic Abdominal Injury During an International Space Station Mission

Science.gov (United States)

Lewandowski, Beth E.; Brooker, John E.; Weavr, Aaron S.; Myers, Jerry G., Jr.; McRae, Michael P.

2013-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to spaceflight mission planners and medical system designers when assessing risks and optimizing medical systems. The IMM project maintains a database of medical conditions that could occur during a spaceflight. The IMM project is in the process of assigning an incidence rate, the associated functional impairment, and a best and a worst case end state for each condition. The purpose of this work was to develop the IMM Abdominal Injury Module (AIM). The AIM calculates an incidence rate of traumatic abdominal injury per person-year of spaceflight on the International Space Station (ISS). The AIM was built so that the probability of traumatic abdominal injury during one year on ISS could be predicted. This result will be incorporated into the IMM Abdominal Injury Clinical Finding Form and used within the parent IMM model.

Discrete Green's Theorem, Green's Functions and Stable Radiative FDTD Boundary Conditions

NARCIS (Netherlands)

Arnold, J.M.; Hon, de B.P.

2007-01-01

We propose a radiative boundary condition for the discrete-grid formulation of Helmholtz’ equation, based on rational approximation in the frequency domain of a Green’s function for the discretised system. This boundary condition is free from instabilities.

On the ratio probability of the smallest eigenvalues in the Laguerre unitary ensemble

Science.gov (United States)

Atkin, Max R.; Charlier, Christophe; Zohren, Stefan

2018-04-01

We study the probability distribution of the ratio between the second smallest and smallest eigenvalue in the Laguerre unitary ensemble. The probability that this ratio is greater than r  >  1 is expressed in terms of an Hankel determinant with a perturbed Laguerre weight. The limiting probability distribution for the ratio as is found as an integral over containing two functions q 1(x) and q 2(x). These functions satisfy a system of two coupled Painlevé V equations, which are derived from a Lax pair of a Riemann-Hilbert problem. We compute asymptotic behaviours of these functions as and , as well as large n asymptotics for the associated Hankel determinants in several regimes of r and x.

K-shell ionization probability in energetic nearly symmetric heavy-ion collisions

International Nuclear Information System (INIS)

Tserruya, I.; Schmidt-Boecking, H.; Schuch, R.

1977-01-01

Impact parameter dependent K-x-ray emission probabilities for the projectile and target atoms have been measured in 35 MeV Cl on Cl, Cl on Ti and Cl on Ni collisions. The sum of projectile plus target K-shell ionization probability is taken as a measure of the total 2psigma ionization probability. The 2pπ-2psigma totational coupling model is in clear disagreement with the present results. On the other hand the sum of probabilities is reproduced both in shape and absolute magnitude by the statistical model for inner-shell ionization. The K-shell ionization probability of the higher -Z collision partner is well described by this model including the 2psigma-1ssigma vacancy sharing probability calculated as a function of the impact parameter. (author)

Application of probability generating function to the essentials of nondestructive nuclear materials assay system using neutron correlation

International Nuclear Information System (INIS)

Hosoma, Takashi

2017-01-01

In the previous research (JAEA-Research 2015-009), essentials of neutron multiplicity counting mathematics were reconsidered where experiences obtained at the Plutonium Conversion Development Facility were taken into, and formulae of multiplicity distribution were algebraically derived up to septuplet using a probability generating function to make a strategic move in the future. Its principle was reported by K. Böhnel in 1985, but such a high-order expansion was the first case due to its increasing complexity. In this research, characteristics of the high-order correlation were investigated. It was found that higher-order correlation increases rapidly in response to the increase of leakage multiplication, crosses and leaves lower-order correlations behind, when leakage multiplication is > 1.3 that depends on detector efficiency and counter setting. In addition, fission rates and doubles count rates by fast neutron and by thermal neutron in their coexisting system were algebraically derived using a probability generating function again. Its principle was reported by I. Pázsit and L. Pál in 2012, but such a physical interpretation, i.e. associating their stochastic variables with fission rate, doubles count rate and leakage multiplication, is the first case. From Rossi-alpha combined distribution and measured ratio of each area obtained by Differential Die-Away Self-Interrogation (DDSI) and conventional assay data, it is possible to estimate: the number of induced fissions per unit time by fast neutron and by thermal neutron; the number of induced fissions (< 1) by one source neutron; and individual doubles count rates. During the research, a hypothesis introduced in their report was proved to be true. Provisional calculations were done for UO_2 of 1∼10 kgU containing ∼ 0.009 wt% "2"4"4Cm. (author)

Pemodelan Markov Switching Dengan Time-varying Transition Probability

OpenAIRE

Savitri, Anggita Puri; Warsito, Budi; Rahmawati, Rita

2016-01-01

Exchange rate or currency is an economic variable which reflects country's state of economy. It fluctuates over time because of its ability to switch the condition or regime caused by economic and political factors. The changes in the exchange rate are depreciation and appreciation. Therefore, it could be modeled using Markov Switching with Time-Varying Transition Probability which observe the conditional changes and use information variable. From this model, time-varying transition probabili...

The probability representation as a new formulation of quantum mechanics

International Nuclear Information System (INIS)

Man'ko, Margarita A; Man'ko, Vladimir I

2012-01-01

We present a new formulation of conventional quantum mechanics, in which the notion of a quantum state is identified via a fair probability distribution of the position measured in a reference frame of the phase space with rotated axes. In this formulation, the quantum evolution equation as well as the equation for finding energy levels are expressed as linear equations for the probability distributions that determine the quantum states. We also give the integral transforms relating the probability distribution (called the tomographic-probability distribution or the state tomogram) to the density matrix and the Wigner function and discuss their connection with the Radon transform. Qudit states are considered and the invertible map of the state density operators onto the probability vectors is discussed. The tomographic entropies and entropic uncertainty relations are reviewed. We demonstrate the uncertainty relations for the position and momentum and the entropic uncertainty relations in the tomographic-probability representation, which is suitable for an experimental check of the uncertainty relations.

Non-Archimedean Probability

NARCIS (Netherlands)

Benci, Vieri; Horsten, Leon; Wenmackers, Sylvia

We propose an alternative approach to probability theory closely related to the framework of numerosity theory: non-Archimedean probability (NAP). In our approach, unlike in classical probability theory, all subsets of an infinite sample space are measurable and only the empty set gets assigned

Allelic drop-out probabilities estimated by logistic regression

DEFF Research Database (Denmark)

Tvedebrink, Torben; Eriksen, Poul Svante; Asplund, Maria

2012-01-01

We discuss the model for estimating drop-out probabilities presented by Tvedebrink et al. [7] and the concerns, that have been raised. The criticism of the model has demonstrated that the model is not perfect. However, the model is very useful for advanced forensic genetic work, where allelic drop-out...... is occurring. With this discussion, we hope to improve the drop-out model, so that it can be used for practical forensic genetics and stimulate further discussions. We discuss how to estimate drop-out probabilities when using a varying number of PCR cycles and other experimental conditions....

Protein single-model quality assessment by feature-based probability density functions.

Science.gov (United States)

Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

Handbook of probability

CERN Document Server

Florescu, Ionut

2013-01-01

THE COMPLETE COLLECTION NECESSARY FOR A CONCRETE UNDERSTANDING OF PROBABILITY Written in a clear, accessible, and comprehensive manner, the Handbook of Probability presents the fundamentals of probability with an emphasis on the balance of theory, application, and methodology. Utilizing basic examples throughout, the handbook expertly transitions between concepts and practice to allow readers an inclusive introduction to the field of probability. The book provides a useful format with self-contained chapters, allowing the reader easy and quick reference. Each chapter includes an introductio

Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

Science.gov (United States)

Malley, J. D.; Kruppa, J.; Dasgupta, A.; Malley, K. G.; Ziegler, A.

2011-01-01

Summary Background Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. Objectives The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Methods Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Results Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Conclusions Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications. PMID:21915433

Site-to-Source Finite Fault Distance Probability Distribution in Probabilistic Seismic Hazard and the Relationship Between Minimum Distances

Science.gov (United States)

Ortega, R.; Gutierrez, E.; Carciumaru, D. D.; Huesca-Perez, E.

2017-12-01

We present a method to compute the conditional and no-conditional probability density function (PDF) of the finite fault distance distribution (FFDD). Two cases are described: lines and areas. The case of lines has a simple analytical solution while, in the case of areas, the geometrical probability of a fault based on the strike, dip, and fault segment vertices is obtained using the projection of spheres in a piecewise rectangular surface. The cumulative distribution is computed by measuring the projection of a sphere of radius r in an effective area using an algorithm that estimates the area of a circle within a rectangle. In addition, we introduce the finite fault distance metrics. This distance is the distance where the maximum stress release occurs within the fault plane and generates a peak ground motion. Later, we can apply the appropriate ground motion prediction equations (GMPE) for PSHA. The conditional probability of distance given magnitude is also presented using different scaling laws. A simple model of constant distribution of the centroid at the geometrical mean is discussed, in this model hazard is reduced at the edges because the effective size is reduced. Nowadays there is a trend of using extended source distances in PSHA, however it is not possible to separate the fault geometry from the GMPE. With this new approach, it is possible to add fault rupture models separating geometrical and propagation effects.

Jump probabilities in the non-Markovian quantum jump method

International Nuclear Information System (INIS)

Haerkoenen, Kari

2010-01-01

The dynamics of a non-Markovian open quantum system described by a general time-local master equation is studied. The propagation of the density operator is constructed in terms of two processes: (i) deterministic evolution and (ii) evolution of a probability density functional in the projective Hilbert space. The analysis provides a derivation for the jump probabilities used in the recently developed non-Markovian quantum jump (NMQJ) method (Piilo et al 2008 Phys. Rev. Lett. 100 180402).

Conditioning from an information processing perspective.

Science.gov (United States)

Gallistel, C R.

2003-04-28

The framework provided by Claude Shannon's [Bell Syst. Technol. J. 27 (1948) 623] theory of information leads to a quantitatively oriented reconceptualization of the processes that mediate conditioning. The focus shifts from processes set in motion by individual events to processes sensitive to the information carried by the flow of events. The conception of what properties of the conditioned and unconditioned stimuli are important shifts from the tangible properties to the intangible properties of number, duration, frequency and contingency. In this view, a stimulus becomes a CS if its onset substantially reduces the subject's uncertainty about the time of occurrence of the next US. One way to represent the subject's knowledge of that time of occurrence is by the cumulative probability function, which has two limiting forms: (1) The state of maximal uncertainty (minimal knowledge) is represented by the inverse exponential function for the random rate condition, in which the US is equally likely at any moment. (2) The limit to the subject's attainable certainty is represented by the cumulative normal function, whose momentary expectation is the CS-US latency minus the time elapsed since CS onset. Its standard deviation is the Weber fraction times the CS-US latency.

75 FR 70092 - Special Conditions: Bombardier Inc. Model CL-600-2E25 Airplane, Interaction of Systems and...

Science.gov (United States)

2010-11-17

... factors of safety) for failure conditions, as a function of system reliability. The Administrator... in the flight manual (speed limitations or avoidance of severe weather conditions, for example). (3... failure-annunciation-system reliability must be included in probability calculations for paragraph (d)(2...

Bounds on survival probability given mean probability of failure per demand; and the paradoxical advantages of uncertainty

International Nuclear Information System (INIS)

Strigini, Lorenzo; Wright, David

2014-01-01

When deciding whether to accept into service a new safety-critical system, or choosing between alternative systems, uncertainty about the parameters that affect future failure probability may be a major problem. This uncertainty can be extreme if there is the possibility of unknown design errors (e.g. in software), or wide variation between nominally equivalent components. We study the effect of parameter uncertainty on future reliability (survival probability), for systems required to have low risk of even only one failure or accident over the long term (e.g. their whole operational lifetime) and characterised by a single reliability parameter (e.g. probability of failure per demand – pfd). A complete mathematical treatment requires stating a probability distribution for any parameter with uncertain value. This is hard, so calculations are often performed using point estimates, like the expected value. We investigate conditions under which such simplified descriptions yield reliability values that are sure to be pessimistic (or optimistic) bounds for a prediction based on the true distribution. Two important observations are (i) using the expected value of the reliability parameter as its true value guarantees a pessimistic estimate of reliability, a useful property in most safety-related decisions; (ii) with a given expected pfd, broader distributions (in a formally defined meaning of “broader”), that is, systems that are a priori “less predictable”, lower the risk of failures or accidents. Result (i) justifies the simplification of using a mean in reliability modelling; we discuss within which scope this justification applies, and explore related scenarios, e.g. how things improve if we can test the system before operation. Result (ii) not only offers more flexible ways of bounding reliability predictions, but also has important, often counter-intuitive implications for decision making in various areas, like selection of components, project management

Characteristics of the probability function for three random-walk models of reaction--diffusion processes

International Nuclear Information System (INIS)

Musho, M.K.; Kozak, J.J.

1984-01-01

A method is presented for calculating exactly the relative width (sigma 2 )/sup 1/2// , the skewness γ 1 , and the kurtosis γ 2 characterizing the probability distribution function for three random-walk models of diffusion-controlled processes. For processes in which a diffusing coreactant A reacts irreversibly with a target molecule B situated at a reaction center, three models are considered. The first is the traditional one of an unbiased, nearest-neighbor random walk on a d-dimensional periodic/confining lattice with traps; the second involves the consideration of unbiased, non-nearest-neigh bor (i.e., variable-step length) walks on the same d-dimensional lattice; and, the third deals with the case of a biased, nearest-neighbor walk on a d-dimensional lattice (wherein a walker experiences a potential centered at the deep trap site of the lattice). Our method, which has been described in detail elsewhere [P.A. Politowicz and J. J. Kozak, Phys. Rev. B 28, 5549 (1983)] is based on the use of group theoretic arguments within the framework of the theory of finite Markov processes

Parisian ruin probability for spectrally negative L\\'{e}vy processes

OpenAIRE

Ronnie Loeffen; Irmina Czarna; Zbigniew Palmowski

2011-01-01

In this note we give, for a spectrally negative Lévy process, a compact formula for the Parisian ruin probability, which is defined by the probability that the process exhibits an excursion below zero, with a length that exceeds a certain fixed period $r$. The formula involves only the scale function of the spectrally negative Lévy process and the distribution of the process at time $r$.

Impact probabilities of meteoroid streams with artificial satellites: An assessment

International Nuclear Information System (INIS)

Foschini, L.; Cevolani, G.

1997-01-01

Impact probabilities of artificial satellites with meteoroid streams were calculated using data collected with the CNR forward scatter (FS) bistatic radar over the Bologna-Lecce baseline (about 700 km). Results show that impact probabilities are 2 times higher than other previously calculated values. Nevertheless, although catastrophic impacts are still rare even in the case of meteor storm conditions, it is expected that high meteoroid fluxes can erode satellites surfaces and weaken their external structures

Quantum Zeno and anti-Zeno effects measured by transition probabilities

Energy Technology Data Exchange (ETDEWEB)

Zhang, Wenxian, E-mail: wxzhang@whu.edu.cn [School of Physics and Technology, Wuhan University, Wuhan, Hubei 430072 (China); Department of Optical Science and Engineering, Fudan University, Shanghai 200433 (China); CEMS, RIKEN, Saitama 351-0198 (Japan); Kavli Institute for Theoretical Physics China, CAS, Beijing 100190 (China); Kofman, A.G. [CEMS, RIKEN, Saitama 351-0198 (Japan); Department of Physics, The University of Michigan, Ann Arbor, MI 48109-1040 (United States); Zhuang, Jun [Department of Optical Science and Engineering, Fudan University, Shanghai 200433 (China); You, J.Q. [Beijing Computational Science Research Center, Beijing 10084 (China); Department of Physics, Fudan University, Shanghai 200433 (China); CEMS, RIKEN, Saitama 351-0198 (Japan); Nori, Franco [CEMS, RIKEN, Saitama 351-0198 (Japan); Department of Physics, The University of Michigan, Ann Arbor, MI 48109-1040 (United States)

2013-10-30