Search results for "Uncertainty"
showing 10 items of 1010 documents
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).
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)
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.
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…
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.
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…
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 …
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…
An overview of robust Bayesian analysis
1994
Robust Bayesian analysis is the study of the sensitivity of Bayesian answers to uncertain inputs. This paper seeks to provide an overview of the subject, one that is accessible to statisticians outside the field. Recent developments in the area are also reviewed, though with very uneven emphasis. © 1994 SEIO.
Online Principal Component Analysis in High Dimension: Which Algorithm to Choose?
2017
Summary Principal component analysis (PCA) is a method of choice for dimension reduction. In the current context of data explosion, online techniques that do not require storing all data in memory are indispensable to perform the PCA of streaming data and/or massive data. Despite the wide availability of recursive algorithms that can efficiently update the PCA when new data are observed, the literature offers little guidance on how to select a suitable algorithm for a given application. This paper reviews the main approaches to online PCA, namely, perturbation techniques, incremental methods and stochastic optimisation, and compares the most widely employed techniques in terms statistical a…