Using many valid instrumental variables has the potential to improve efficiency but makes the usual inference procedures inaccurate. We give corrected standard errors, an extension of Bekker to ...

This study proposes a comprehensive strategy to optimize the operation of real-world gas pipeline networks and support decision-making. The goal is to improve environmental sustainability by ...

Concomitant-variable models supplement latent-class models incorporating grouping by providing more parsimonious representations of data for some cases. Also, concomitant-variable models are useful ...

Learn about the Sikkim TET Syllabus 2025, including topic-wise syllabus, weightage, preparation tips, and more on this page.

Moreover, innovative work addressing sparse plus low-rank structures in autoregressive graphical models has further broadened the applicability of these techniques, enabling more robust ...

To address these challenges, we propose a density-based probabilistic graphical model (DB-PGM) to achieve adaptive multi-target encirclement. DB-PGM models the cooperative encirclement of multiple ...

Gaussian Graphical Models (GGMs) are a type of network modeling that uses partial correlation rather than correlation for representing complex relationships among multiple variables. The advantage of ...

We study the problem of learning graphs in Gaussian graphic models by assuming that the underlying precision matrix has a "low-rank and diagonal" (LRaD) structure. This assumption enjoys a latent ...

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