Search results for "uncertainty."

showing 10 items of 972 documents

Random Logistic Maps II. The Critical Case

2003

Let (X n )∞ 0 be a Markov chain with state space S=[0,1] generated by the iteration of i.i.d. random logistic maps, i.e., X n+1=C n+1 X n (1−X n ),n≥0, where (C n )∞ 1 are i.i.d. random variables with values in [0, 4] and independent of X 0. In the critical case, i.e., when E(log C 1)=0, Athreya and Dai(2) have shown that X n → P 0. In this paper it is shown that if P(C 1=1)<1 and E(log C 1)=0 then (i) X n does not go to zero with probability one (w.p.1) and in fact, there exists a 0<β<1 and a countable set ▵⊂(0,1) such that for all x∈A≔(0,1)∖▵, P x (X n ≥β for infinitely many n≥1)=1, where P x stands for the probability distribution of (X n )∞ 0 with X 0=x w.p.1. A is a closed set for (X n…

Statistics and ProbabilityCombinatoricsDiscrete mathematicsDistribution (mathematics)Multivariate random variableInitial distributionGeneral MathematicsZero (complex analysis)Random elementProbability distributionStatistics Probability and UncertaintyRandom variableMathematicsJournal of Theoretical Probability
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A Unified Approach to Likelihood Inference on Stochastic Orderings in a Nonparametric Context

1998

Abstract For data in a two-way contingency table with ordered margins, we consider various hypotheses of stochastic orders among the conditional distributions considered by rows and show that each is equivalent to requiring that an invertible transformation of the vectors of conditional row probabilities satisfies an appropriate set of linear inequalities. This leads to the construction of a general algorithm for maximum likelihood estimation under multinomial sampling and provides a simple framework for deriving the asymptotic distribution of log-likelihood ratio tests. The usual stochastic ordering and the so called uniform and likelihood ratio orderings are considered as special cases. I…

Statistics and ProbabilityCombinatoricsIndependent and identically distributed random variablesLinear inequalityTransformation (function)Likelihood-ratio testAsymptotic distributionApplied mathematicsConditional probability distributionStatistics Probability and UncertaintyStochastic orderingStatistical hypothesis testingMathematicsJournal of the American Statistical Association
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Relación entre conos de direcciones decrecientes y conos de direcciones de descenso

1984

Let f: N ? R a convex function and x I Ni, where N is a convex set in a real linear space. It is stated that, if Df<(x) is not empty, then Df<(x) is the algebraic interior of Df=(x).

Statistics and ProbabilityCombinatoricsLinear spaceCalculusConvex setStatistics Probability and UncertaintyAlgebraic numberConvex functionMathematicsTrabajos de Estadistica y de Investigacion Operativa
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Una solucion bayesiana a la Paradoja de Stein

1982

If we are interested in making inferences about the square norm of the mean in a multivariate normal model, the usual uniform prior for the mean is not sound, as revealed by Stein in his 1959 work. This paper studies in what sense this prior must be modified by using the maximization of missing information procedure (Bernardo, 1979)

Statistics and ProbabilityCombinatoricsNorm (mathematics)Multivariate normal distributionMaximizationStatistics Probability and UncertaintyPsychologyCartographyTrabajos de Estadistica Y de Investigacion Operativa
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Multiple testing of pairs of one-sided hypotheses

1986

Two-sided test procedures fork real parameters should point out in the case of rejection whether the left or the right alternative can be assumed. This sets up a multiple testing problem fork pairs of one-sided hypotheses. Holm's (1979, Scandinavian Journal of Statistics 6:65–70) sequentially rejective test provides a solution the critical levels of which are slightly improved. Considerable improvement is obtained when the hypotheses are redefined to be disjoint in pairs.

Statistics and ProbabilityCombinatoricsProbability theoryOne sidedTest proceduresStatisticsMultiple comparisons problemPoint (geometry)Disjoint setsStatistics Probability and UncertaintyFork (software development)MathematicsTest (assessment)Metrika
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A generalized predictive criterion for model selection

2002

Given a random sample from some unknown model belonging to a finite class of parametric models, assume that the estimate of the density of a future observation is of interest San Martini & Spezzaferri (1984) proposed for this problem a predictive criterion based on the logarithmic utility function. The present authors investigate a generalization of this criterion that uses as a loss function an element of the class of α-divergences discussed by Ali & Silvey (1966) and Csiszar (1967). They also discuss briefly the case in which the class of models considered is not exhaustive. Un critere de prevision generalise pour la selection de modeles Supposons que l'on cherche a estimer la densite d'u…

Statistics and ProbabilityCombinatoricsmodel selectionModel selectionCalculusloss function; model selection; α-divergencesStatistics Probability and Uncertaintyα-divergencesMathematicsloss function
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Quasi Competition — a New Aspect

1978

The model of quasi competition put forward in 1967 is reinvestigated under the aspect that only large (N ∞) populations are considered. Under this new angle the conclusion that myomas develop from single cells seems better justified than the original discussion indicated.

Statistics and ProbabilityCompetition (economics)EconomicsGeneral MedicineStatistics Probability and UncertaintyMathematical economicsBiometrical Journal
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Fast and universal estimation of latent variable models using extended variational approximations

2022

AbstractGeneralized linear latent variable models (GLLVMs) are a class of methods for analyzing multi-response data which has gained considerable popularity in recent years, e.g., in the analysis of multivariate abundance data in ecology. One of the main features of GLLVMs is their capacity to handle a variety of responses types, such as (overdispersed) counts, binomial and (semi-)continuous responses, and proportions data. On the other hand, the inclusion of unobserved latent variables poses a major computational challenge, as the resulting marginal likelihood function involves an intractable integral for non-normally distributed responses. This has spurred research into a number of approx…

Statistics and ProbabilityComputational Theory and Mathematicsmultivariate abundance datamuuttujatlaplace approximationmulti-response dataordinationStatistics Probability and Uncertaintyvariational approximationsgeneralized linear latent variable modelsestimointiTheoretical Computer ScienceStatistics and Computing
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A Neo2 bayesian foundation of the maxmin value for two-person zero-sum games

1994

A joint derivation of utility and value for two-person zero-sum games is obtained using a decision theoretic approach. Acts map states to consequences. The latter are lotteries over prizes, and the set of states is a product of two finite sets (m rows andn columns). Preferences over acts are complete, transitive, continuous, monotonie and certainty-independent (Gilboa and Schmeidler (1989)), and satisfy a new axiom which we introduce. These axioms are shown to characterize preferences such that (i) the induced preferences on consequences are represented by a von Neumann-Morgenstern utility function, and (ii) each act is ranked according to the maxmin value of the correspondingm × n utility …

Statistics and ProbabilityComputer Science::Computer Science and Game TheoryEconomics and EconometricsTransitive relationVon Neumann–Morgenstern utility theoremMathematics (miscellaneous)Zero-sum gameExample of a game without a valueCardinal utilityStatistics Probability and UncertaintyTransferable utilityMathematical economicsFinite setSocial Sciences (miscellaneous)AxiomMathematicsInternational Journal of Game Theory
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Modeling the coupled return-spread high frequency dynamics of large tick assets

2015

Large tick assets, i.e. assets where one tick movement is a significant fraction of the price and bid-ask spread is almost always equal to one tick, display a dynamics in which price changes and spread are strongly coupled. We introduce a Markov-switching modeling approach for price change, where the latent Markov process is the transition between spreads. We then use a finite Markov mixture of logit regressions on past squared returns to describe the dependence of the probability of price changes. The model can thus be seen as a Double Chain Markov Model. We show that the model describes the shape of return distribution at different time aggregations, volatility clustering, and the anomalo…

Statistics and ProbabilityComputer Science::Computer Science and Game TheoryVolatility clusteringQuantitative Finance - Trading and Market MicrostructureMarkov chainLogitMarkov processStatistical and Nonlinear PhysicsMarkov modelmodels of financial markets nonlinear dynamics stochastic processesTrading and Market Microstructure (q-fin.TR)FOS: Economics and businesssymbols.namesakesymbolsEconometricsKurtosisFraction (mathematics)Almost surelyStatistics Probability and Uncertainty60J20Mathematics
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