Results 31 to 40 of about 35,767 (304)
Probabilistic Graph Models (PGMs) for Feature Selection in Time Series Analysis and Forecasting
JISR on Computing, 2021 Time series or longitudinal analysis has a very important aspect in the field of research. Day by day new and better analyses are getting developed in this field.
Syed Ali Raza Naqvi
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Sum of Bernoulli Mixtures: Beyond Conditional Independence
Journal of Probability and Statistics, 2014 We consider the distribution of the sum of Bernoulli mixtures under a general dependence structure. The level of dependence is measured in terms of a limiting conditional correlation between two of the Bernoulli random variables.
Taehan Bae, Ian Iscoe
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Conditional Demand and Endogeneity? A Case Study of Demand for Juice Products
Journal of Agricultural and Resource Economics, 1994 The question of endogeneity of conditional expenditures, as well as prices, in conditional demand equations for justices is examined. Both conditional expenditures and prices were found to be uncorrelated with the conditional demand errors, based on Wu ...
Mark G. Brown +2 more
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Approximate Kernel-Based Conditional Independence Tests for Fast Non-Parametric Causal Discovery
Journal of Causal Inference, 2019 Constraint-based causal discovery (CCD) algorithms require fast and accurate conditional independence (CI) testing. The Kernel Conditional Independence Test (KCIT) is currently one of the most popular CI tests in the non-parametric setting, but many ...
Strobl Eric V. +2 more
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Gaussian Covariance Faithful Markov Trees
Journal of Probability and Statistics, 2011 Graphical models are useful for characterizing conditional and marginal independence structures in high-dimensional distributions. An important class of graphical models is covariance graph models, where the nodes of a graph represent different ...
Dhafer Malouche, Bala Rajaratnam
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The Strucplot Framework: Visualizing Multi-way Contingency Tables with vcd
Journal of Statistical Software, 2006 This paper describes the "strucplot" framework for the visualization of multi-way contingency tables. Strucplot displays include hierarchical conditional plots such as mosaic, association, and sieve plots, and can be combined into more complex ...
David Meyer, Achim Zeileis, Kurt Hornik
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Computational Test for Conditional Independence
AlgorithmsConditional Independence (CI) testing is fundamental in statistical analysis. For example, CI testing helps validate causal graphs or longitudinal data analysis with repeated measures in causal inference.
Christian B. H. Thorjussen +3 more
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$M^{4}CD$ : A Robust Change Detection Method for Intelligent Visual Surveillance
IEEE Access, 2018 In this paper, we propose a robust change detection method for intelligent visual surveillance. This method, named M4CD, includes three major steps. First, a sample-based background model that integrates color and texture cues is built and updated over ...
Kunfeng Wang, Chao Gou, Fei-Yue Wang
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A Conditional Approach to Panel Data Models with Common Shocks
Econometrics, 2016 This paper studies the effects of common shocks on the OLS estimators of the slopes’ parameters in linear panel data models. The shocks are assumed to affect both the errors and some of the explanatory variables. In contrast to existing approaches, which
Giovanni Forchini, Bin Peng
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Conditional independence in propositional logic
Artificial Intelligence, 2002 Independence -- the study of what is relevant to a given problem of reasoning -- is an important AI topic. In this paper, we investigate several notions of conditional independence in propositional logic: Darwiche and Pearl's conditional independence, and some more restricted forms of it.
Jerome Lang +2 more
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