Search results for "Conditional"
showing 10 items of 294 documents
Univariate and multivariate conditional entropy measures for the characterization of short-term cardiovascular complexity under physiological stress
2017
Objective: A defining feature of physiological systems under the neuroautonomic regulation is their dynamical complexity. The most common approach to assess physiological complexity from short-term recordings, i.e. to compute the rate of entropy generation of an individual system by means of measures of conditional entropy (CE), does not consider that complexity may change when the investigated system is part of a network of physiological interactions. This study aims at extending the concept of short-term complexity towards the perspective of network physiology, defining multivariate CE measures whereby multiple physiological processes are accounted for in the computation of entropy rates.…
Spelling out consequences : conditional constructions as a means to resist proposals in organisational planning process
2016
Organisational planning processes often materialise as a series of meetings, where the future of the organisation is jointly discussed and negotiated as a part of local decision-making sequences. Using conversation and discourse analytical approaches, this article investigates how proposals concerning the future can also be resisted by employing a specific device, a conditional construction ( if X, then Y). The data for the study originate from a city organisation, whose customer services are being developed. The results show how the conditional constructions work in two interrelated ways. First, by introducing a problematic hypothetical situation, they outline the undesirable consequences…
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 …
Robustness of the risk–return relationship in the U.S. stock market
2008
Abstract Using GARCH-in-Mean models, we study the robustness of the risk–return relationship in monthly U.S. stock market returns (1928:1–2004:12) with respect to the specification of the conditional mean equation. The issue is important because in this commonly used framework, unnecessarily including an intercept is known to distort conclusions. The existence of the relationship is relatively robust, but its strength depends on the prior belief concerning the intercept. The latter applies in particular to the first half of the sample, where also the coefficient of the relative risk aversion is smaller and the equity premium greater than in the latter half.
Parameter orthogonality and conditional profile likelihood: the exponential power function case
1999
Orthogonality, according to Fisher’s metrics, between the parameters of a probability density function, as well as giving rise to a series of statistical implications, makes it possible to express a function of conditional profile likelihood with better properties than the ordinary profile likelihood function. In the present paper the parameters of exponential power function are made orthogonal and the conditional profile likelihood of the shape parameter p is determined in order to study its properties with reference to p estimation. Moreover, by means of a simulation plan, a comparison is made between the estimates of p obtained from the conditional profile log-likelihood and those obtain…
Comment on “A simple way to incorporate uncertainty and risk into forest harvest scheduling”
2017
In a recent research article, Robinson et al. (2016) described a method of estimating uncertainty of harvesting outcomes by analyzing the historical yield to the associated prediction for a large number of harvest operations. We agree with this analysis, and consider it a useful tool to integrate estimates of uncertainty into the optimization process. The authors attempt to manage the risk using two different methods, based on deterministic integer linear programming. The first method focused on maximizing the 10th quantile of the distribution of predicted volume subject to area constraint, while the second method focused on minimizing the variation of total quantity of volume harvested sub…
Oligodendrocyte-specific FADD deletion protects mice from autoimmune-mediated demyelination.
2010
Abstract Apoptosis of oligodendrocytes (ODCs), the myelin-producing glial cells in the CNS, plays a central role in demyelinating diseases such as multiple sclerosis and experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis. To investigate the mechanism behind ODC apoptosis in EAE, we made use of conditional knockout mice lacking the adaptor protein FADD specifically in ODCs (FADDODC-KO). FADD mediates apoptosis by coupling death receptors with downstream caspase activation. In line with this, ODCs from FADDODC-KO mice were completely resistant to death receptor-induced apoptosis in vitro. In the EAE model, FADDODC-KO mice followed an ameliorated clinical di…
Recursive estimation of the conditional geometric median in Hilbert spaces
2012
International audience; A recursive estimator of the conditional geometric median in Hilbert spaces is studied. It is based on a stochastic gradient algorithm whose aim is to minimize a weighted L1 criterion and is consequently well adapted for robust online estimation. The weights are controlled by a kernel function and an associated bandwidth. Almost sure convergence and L2 rates of convergence are proved under general conditions on the conditional distribution as well as the sequence of descent steps of the algorithm and the sequence of bandwidths. Asymptotic normality is also proved for the averaged version of the algorithm with an optimal rate of convergence. A simulation study confirm…
Graphical Models for Dependencies and Associations
1992
The role of graphical representations is described in distinguishing various special forms of independency structure that can arise with multivariate data, especially in observational studies in the social sciences. Conventions for constructing the graphs and strategies for analysing three sets of data are summarized. Finally some directions for desirable future work are outlined.