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Showing 1 to 7 of 7 for “"Composite likelihood"”.
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Composite Likelihood: Multiple Comparisons and Non-Standard Conditions in Hypothesis Testing
Computational intensity in using full likelihood estimation of multivariate and correlated data is a valid motivation to employ composite likelihood as an alternative that eases the process by using marginal or conditional densities and reducing the dimension. We study the problem of multiple …
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A Predictive Time-to-Event Modeling Approach with Longitudinal Measurements and Missing Data
… spaced time points, we propose a smoothed composite likelihood approach for estimations. The forward intensity function approach intrinsically incorporates the future dynamics in the predictor variables that affect the stochastic occurrence of the future event. Thus the proposed framework …
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High-Dimensional Covariate-Dependent Gaussian Graphical Models
… through a novel parameterization. Utilizing a likelihood framework, our methodology jointly estimates all edge and vertex parameters. We further develop statistical inference procedures to test the dynamic nature of the underlying network. Concerning large-scale networks, we perform composite …
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Copula-Based Multivariate Hydrologic Frequency Analysis
… data in the analysis. A new copula-based “Composite Likelihood Approach” that allows all available multivariate data of varying lengths to be combined and analyzed in an integrated manner has been developed. This approach yields additional information, enhancing the precision of parameter …
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Copulas for High Dimensions: Models, Estimation, Inference, and Applications
… of the new class of copulas is conducted using a composite likelihood, making the model feasible even for hundreds of variables. A realistic simulation study verifies that multistage estimation with composite likelihood results in small loss in efficiency and large gain in computation speed. …
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Vision-Enhanced Communications: On the Benefits of NLOS/LOS Knowledge in Wireless Systems
… labeled vs unlabeled information. Bayes risk and composite likelihood ratio test (LRT) methods are used to derive the optimal decision rule in both constant false-alarm rate (CFAR) and minimum probability of error (min(Pe)) paradigms. It is shown that a dynamic detection scheme utilizing labeled …
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Semiparametric estimation with clustered right censored data via multivariate gaussian random fields
Consider a fixed number of clustered areas identified by their geographical coordinate that are monitored for the occurrences of an event such as pandemic, epidemic, migration to name a few. Data collected on units at all areas include time varying covariates and other environmental factors that …