Titlebook: Ordinal Data Modeling; Valen E. Johnson,James H. Albert Textbook 1999 Springer Science+Business Media New York 1999 Bayesian inference.DEX

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2199-7357 uate students and researchers in the statistical and social sciences, this book describes a coherent framework for understanding binary and ordinal regression models, item response models, graded response models, and ROC analyses, and for exposing the close connection between these models. A unique

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Graded Response Models: A Case Study of Undergraduate Grade Data,

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solutions for problems in opportunistic Information-Centric Networks. Among those are mechanisms for efficient content discovery in neighbour nodes, resume mechanisms to recover from intermittent connectivity disruptions, a novel agent delegation mechanisms to offload content discovery and delivery

思考而得

Valen E. Johnson,James H. Albertted with heterogeneous devices, which are using different technologies for communication. Because of communication technology diversity, research challenges are to uniquely identify devices, and to enable them to communicate securely. To tackle the former, previously proposed, a unique identifying s

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Valen E. Johnson,James H. Albertode can send a short response (less than 1?KB) that fits in a single UDP message. This means that any node possessing an extended-CRL, including Road Side Units (RSUs) or intermediate vehicles, can produce short certificate-status responses that can be easily authenticated. The main procedures invol

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Valen E. Johnson,James H. Albertode can send a short response (less than 1?KB) that fits in a single UDP message. This means that any node possessing an extended-CRL, including Road Side Units (RSUs) or intermediate vehicles, can produce short certificate-status responses that can be easily authenticated. The main procedures invol