An improved conflicting evidence combination approach based on a new supporting probability distance

To avoid counter-intuitive result of classical Dempster's combination rule when dealing with highly conflict information, many improved combination methods have been developed through modifying the basic probability assignments (BPAs) of bodies of evidence (BOEs) by using a certain measure of the degree of conflict or uncertain information, such as Jousselme's distance, the pignistic probability distance and the ambiguity measure. However, if BOEs contain some non-singleton elements and the differences among their BPAs are larger than 0.5, the current conflict measure methods have limitations in describing the interrelationship among the conflict BOEs and may even lead to wrong combination results. In order to solve this problem, a new distance function, which is called supporting probability distance, is proposed to characterize the differences among BOEs. With the new distance, the information of how much a focal element is supported by the other focal elements in BOEs can be given. Also, a new combination rule based on the supporting probability distance is proposed for the combination of the conflicting evidences. The credibility and the discounting factor of each BOE are generated by the supporting probability distance and the weighted BOEs are combined directly using Dempster's rules. Analytical results of numerical examples show that the new distance has a better capability of describing the interrelationships among BOEs, especially for the highly conflicting BOEs containing non-singleton elements and the proposed new combination method has better applicability and effectiveness compared with the existing methods.

The value of corporate reputation and the Defamation Act 2013:a brave new world or road to ruin?

Questions whether the focus on freedom of expression under the Defamation Act 2013 could undermine the value of corporate reputation as a commercial asset.

On the Coherence Between Probability and Possibility Measures

* This paper is supported by CICYT (Spain) under Project TIN 2005-08943-C02-01.

Evaluating Misclassification Probability Using Empirical Risk

* The work is supported by RFBR, grant 04-01-00858-a

The B-Terminal Busy Probability Prediction

In the teletraffic engineering of all the telecommunication networks, parameters characterizing the terminal traffic are used. One of the most important of them is the probability of finding the called (B-terminal) busy. This parameter is studied in some of the first and last papers in Teletraffic Theory. We propose a solution in this topic in the case of (virtual) channel systems, such as PSTN and GSM. We propose a detailed conceptual traffic model and, based on it, an analytical macro-state model of the system in stationary state, with: Bernoulli– Poisson–Pascal input flow; repeated calls; limited number of homogeneous terminals; losses due to abandoned and interrupted dialling, blocked and interrupted switching, not available intent terminal, blocked and abandoned ringing and abandoned conversation. Proposed in this paper approach may help in determination of many network traffic characteristics at session level, in performance evaluation of the next generation mobile networks.

Conditional probability calculations for the nonlinear Schrödinger equation with additive noise

The method for the computation of the conditional probability density function for the nonlinear Schrödinger equation with additive noise is developed. We present in a constructive form the conditional probability density function in the limit of small noise and analytically derive it in a weakly nonlinear case. The general theory results are illustrated using fiber-optic communications as a particular, albeit practically very important, example.

On the Extinction Probability for Bisexual Branching Processes in Varying Environments

2000 Mathematics Subject Classification: 60J80

Randomized Push-Out Mechanisms in Priority Queuing and their Probability Characteristics

2002 Mathematics Subject Classification: 60K25.

Sensitivity Analysis of Some Applied Probability Models

2000 Mathematics Subject Classi cation: Primary 90C31. Secondary 62C12, 62P05, 93C41.

On the Moving Boundary Hitting Probability for the Brownian Motion

2000 Mathematics Subject Classification: 60J65.

An Estimate of the Probability Pr(X

2000 Mathematics Subject Classification: 33C90, 62E99

On the Recursive Estimation of the Location and of the Size of the Mode of a Probability Density

2000 Mathematics Subject Classification: 62G07, 62L20.

Estimation of a Regression Function on a Point Process and its Application to Financial Ruin Risk Forecast

2000 Mathematics Subject Classification: Primary 60G55; secondary 60G25.

Néhány megjegyzés a kockázat, bizonytalanság, valószínűség kérdéséhez (Some remarks about uncertainty, risk and probability)

A címben említett három fogalom a közgazdasági elméletben központi szerepet foglal el. Ezek viszonya elsősorban a közgazdaságtudományi megismerés határait feszegeti. Mit tudunk a gazdasági döntésekről? Milyen információk alapján születnek a döntések? Lehet-e a gazdasági döntéseket „tudományos” alapra helyezni? A bizonytalanság kérdéséről az 1920-as években való megjelenése óta mindent elmondtak. Megvizsgálták a kérdést filozófiailag, matematikailag. Tárgyalták a kérdés számtalan elméleti és gyakorlati aspektusát. Akkor miért kell sokadszorra is foglalkozni a témával? A válasz igen egyszerű: azért, mert a kérdés minden szempontból ténylegesen alapvető, és mindenkor releváns. Úgy hírlik, hogy a római diadalmenetekben a győztes szekerén mindig volt egy rabszolga is, aki folyamatosan figyelmeztette a diadaltól megmámorosodott vezért, hogy ő is csak egy ember, ezt ne feledje el. A gazdasági döntéshozókat hasonló módon újra és újra figyelmeztetni kell arra, hogy a gazdasági döntések a bizonytalanság jegyében születnek. A gazdasági folyamatok megérthetőségének és kontrollálhatóságának van egy igen szoros korlátja. Ezt a korlátot a folyamatok inherens bizonytalansága adja. A gazdasági döntéshozók fülébe folyamatosan duruzsolni kell: ők is csak emberek, és ezért ismereteik igen korlátozottak. A „bátor” döntések során az eredmény bizonytalan, a tévedés azonban bizonyosra vehető. / === / In the article the author presents some remarks on the application of probability theory in financial decision making. From mathematical point of view the risk neutral measures used in finance are some version of separating hyperplanes used in optimization theory and in general equilibrium theory. Therefore they are just formally a probabilities. They interpretation as probabilities are misleading analogies leading to wrong decisions.

Valószínűség, esély, relatív súlyok. Opciók és reálopciók (Probability, chance, relative weights)

There is a long debate (going back to Keynes) how to interpret the concept of probability in economics, in business decisions, in finance. Iván Bélyácz suggested that the Black–Scholes– Merton analysis of fi nancial derivatives has a contribution to this risk vs. uncertainty debate. This article tries to interpret this suggestion, from the viewpoint of traded options, real options, Arrow–Debreu model, Heath–Jarrow–Morton model, insurance business. The article suggests making clear distinction and using different naming ● when the frequents approach and the statistics is relevant, ● when we just use consequent relative weights during the no-arbitrage pricing, and these weight are just interpreted as probabilities, ● when we just lack the necessary information, and there is a basic uncertainty in the business decision making process. The paper suggests making a sharp distinction between fi nancial derivatives used for market risk management and credit risk type derivatives (CDO, CDS, etc) in the reregulation process of the fi nancial markets.