Search results for "Conditional"

Statistical Dependence and Independence

2005

Statistical dependence is a type of relation between different characteristics measured on the same units. At one extreme is deterministic dependence; at the other is statistical independence, where the distribution of one variable is the same for all levels of the other. With more than two variables, an important distinction is between marginal and conditional dependence. In many contexts, the degree of dependence may be summarized by a suitable measure of association, perhaps as part of a general model. Reference is made to graphical models. Keywords: association; correlation; marginal; conditional; exponential family; graphical Markov models

Contribution à l'estimation non paramétrique des quantiles géométriques et à l'analyse des données fonctionnelles

2008

In this dissertation we study the nonparametric geometric quantile estimation, conditional geometric quantiles estimation and functional data analysis. First, we are interested to the definition of geometric quantiles. Different simulations show that Transformation-Retransformation technique should be used to estimate geometric quantiles when the distribution is not spheric. A real study shows that, data are better modelized by geometric quantiles than by marginal one's, especially when variables that make up the random vector are correlated. Then we estimate geometric quantiles when data are obtained by survey sampling techniques. First, we propose an unbaised estimator, then using lineari…

Automated uncertainty quantification analysis using a system model and data

2015

International audience; Understanding the sources of, and quantifying the magnitude of, uncertainty can improve decision-making and, thereby, make manufacturing systems more efficient. Achieving this goal requires knowledge in two separate domains: data science and manufacturing. In this paper, we focus on quantifying uncertainty, usually called uncertainty quantification (UQ). More specifically, we propose a methodology to perform UQ automatically using Bayesian networks (BN) constructed from three types of sources: a descriptive system model, physics-based mathematical models, and data. The system model is a high-level model describing the system and its parameters; we develop this model …

Implicit learning of non-local musical rules : A comment on Kuhn and Dienes

2009

International audience; In a recent study, G. Kuhn and Z. Dienes (2005) reported that participants previously exposed to a set of musical tunes generated by a biconditional grammar subsequently preferred new tunes that respected the grammar over new ungrammatical tunes. Because the study and test tunes did not share any chunks of adjacent intervals, this result may be construed as straightforward evidence for the implicit learning of a structure that was only governed by nonlocal dependency rules. It is shown here that the grammar modified the statistical distribution of perceptually salient musical events, such as the probability that tunes covered an entire octave. When the influence of t…

Modeling user preferences in content-based image retrieval: A novel attempt to bridge the semantic gap

2015

This paper is concerned with content-based image retrieval from a stochastic point of view. The semantic gap problem is addressed in two ways. First, a dimensional reduction is applied using the (pre-calculated) distances among images. The dimension of the reduced vector is the number of preferences that we allow the user to choose from, in this case, three levels. Second, the conditional probability distribution of the random user preference, given this reduced feature vector, is modeled using a proportional odds model. A new model is fitted at each iteration. The score used to rank the image database is based on the estimated probability function of the random preference. Additionally, so…

A principled approach to network-based classification and data representation

2013

Measures of similarity are fundamental in pattern recognition and data mining. Typically the Euclidean metric is used in this context, weighting all variables equally and therefore assuming equal relevance, which is very rare in real applications. In contrast, given an estimate of a conditional density function, the Fisher information calculated in primary data space implicitly measures the relevance of variables in a principled way by reference to auxiliary data such as class labels. This paper proposes a framework that uses a distance metric based on Fisher information to construct similarity networks that achieve a more informative and principled representation of data. The framework ena…

Trusted Computing and DRM

2015

Trusted Computing is a special branch of computer security. One branch of computer security involves protection of systems against external attacks. In that branch we include all methods that are used by system owners against external attackers, for example Firewalls, IDS, IPS etc. In all those cases the system owner installs software that uses its own means to determine if a remote user is malicious and terminates the attack. (Such means can be very simple such as detecting signatures of attacks or very complex such as machine learning and detecting anomalies in the usage pattern of the remote user). Another branch of attacks requires protection by the system owner against internal users. …

Assessment of qualitative judgements for conditional events in expert systems

1991

An algorithm for earthquakes clustering based on maximum likelihood

2007

In this paper we propose a clustering technique set up to separate and find out the two main components of seismicity: the background seismicity and the triggered one. We suppose that a seismic catalogue is the realization of a non homogeneous space-time Poisson clustered process, with a different parametrization for the intensity function of the Poisson-type component and of the clustered (triggered) component. The method here proposed assigns each earthquake to the cluster of earthquakes, or to the set of independent events, according to the increment to the likelihood function, computed using the conditional intensity function estimated by maximum likelihood methods and iteratively chang…

Determinants of individual tourist expenditure as a network: Empirical findings from Uruguay

2014

Abstract This paper introduces the use of graphical models for assessing the determinants of individual tourist spending. These models have the advantage of synthesizing and visualizing the relationships occurring within large sets of random variables, through an easy to interpret output. To this end, individual data from a large official survey of international tourists in Uruguay are used. Symmetric conditional independence structures are first investigated. Then subgraphs of each expenditure item's neighbourhood are extracted in order to assess the impact of main effects and interactions through proportional ordinal logistic regression. Results highlight the marginal role of socio-demogr…