Search results for " independence"
showing 10 items of 128 documents
Binary distributions of concentric rings
2014
We introduce families of jointly symmetric, binary distributions that are generated over directed star graphs whose nodes represent variables and whose edges indicate positive dependences. The families are parametrized in terms of a single parameter. It is an outstanding feature of these distributions that joint probabilities relate to evenly spaced concentric rings. Kronecker product characterizations make them computationally attractive for a large number of variables. We study the behavior of different measures of dependence and derive maximum likelihood estimates when all nodes are observed and when the inner node is hidden.
Explicit, identical maximum likelihood estimates for some cyclic Gaussian and cyclic Ising models
2017
Cyclic models are a subclass of graphical Markov models with simple, undirected probability graphs that are chordless cycles. In general, all currently known distributions require iterative procedures to obtain maximum likelihood estimates in such cyclic models. For exponential families, the relevant conditional independence constraint for a variable pair is given all remaining variables, and it is captured by vanishing canonical parameters involving this pair. For Gaussian models, the canonical parameter is a concentration, that is, an off-diagonal element in the inverse covariance matrix, while for Ising models, it is a conditional log-linear, two-factor interaction. We give conditions un…
Latent class models for multiple ordered categorical health data: testing violation of the local independence assumption
2019
Latent class models are now widely applied in health economics to analyse heterogeneity in multiple outcomes generated by subgroups of individuals who vary in unobservable characteristics, such as genetic information or latent traits. These models rely on the underlying assumption that associations between observed outcomes are due to their relationship to underlying subgroups, captured in these models by conditioning on a set of latent classes. This implies that outcomes are locally independent within a class. Local independence assumption, however, is sometimes violated in practical applications when there is uncaptured unobserved heterogeneity resulting in residual associations between c…
Pairwise Markov properties for regression graphs
2016
With a sequence of regressions, one may generate joint probability distributions. One starts with a joint, marginal distribution of context variables having possibly a concentration graph structure and continues with an ordered sequence of conditional distributions, named regressions in joint responses. The involved random variables may be discrete, continuous or of both types. Such a generating process specifies for each response a conditioning set that contains just its regressor variables, and it leads to at least one valid ordering of all nodes in the corresponding regression graph that has three types of edge: one for undirected dependences among context variables, another for undirect…
Affine-invariant rank tests for multivariate independence in independent component models
2016
We consider the problem of testing for multivariate independence in independent component (IC) models. Under a symmetry assumption, we develop parametric and nonparametric (signed-rank) tests. Unlike in independent component analysis (ICA), we allow for the singular cases involving more than one Gaussian independent component. The proposed rank tests are based on componentwise signed ranks, à la Puri and Sen. Unlike the Puri and Sen tests, however, our tests (i) are affine-invariant and (ii) are, for adequately chosen scores, locally and asymptotically optimal (in the Le Cam sense) at prespecified densities. Asymptotic local powers and asymptotic relative efficiencies with respect to Wilks’…
On (n-l)-wise and joint independence and normality of n Random variables: an example
1981
An example is given of a vector of n random variables such that any (n-1)-dimensional subvector consists of n-1 independent standard normal variables. The whole vector however is neither independent nor normal.
Selecting the tuning parameter in penalized Gaussian graphical models
2019
Penalized inference of Gaussian graphical models is a way to assess the conditional independence structure in multivariate problems. In this setting, the conditional independence structure, corresponding to a graph, is related to the choice of the tuning parameter, which determines the model complexity or degrees of freedom. There has been little research on the degrees of freedom for penalized Gaussian graphical models. In this paper, we propose an estimator of the degrees of freedom in $$\ell _1$$ -penalized Gaussian graphical models. Specifically, we derive an estimator inspired by the generalized information criterion and propose to use this estimator as the bias term for two informatio…
Interdependence Between Tool Fracture and Wear
1985
Wear and fracture are the main causes of tool scrapping. However fracture plays a major role for increasing values of the hardness and brittleness of tool materials or when low-cobalt tungsten carbides are used or in interrupted cutting conditions where it is the most relevant factor for tool scrapping. In order to obtain the optimal values of the cutting speed both these factors should be considered. The hypothesis of stochastic independence among them simplifies the mathematical formulation of the optimization problem; but experimental investigations do not agree with this assumption and, as a matter of fact, the probability density function of tool fracture results to be dependent on the…
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.
Corporate social and environmental disclosure as a sustainable development tool provided by board sub-committees: Do women directors play a relevant …
2021
This is the pre-peer reviewed version of the following article: Corporate social and environmental disclosure as a sustainable development tool provided by board sub-committees: Do women directors play a relevant moderating role?, which has been published in final form at https://doi.org/10.1002/bse.2815. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions The aim of this research is to examine the impact of three audit committee characteristics on corporate social and environmental responsibility (CSR) disclosure: the existence of an audit committee, audit committee independence, and audit committee financial …