Chagrin
发表于 2025-3-28 17:56:12
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ALOFT
发表于 2025-3-28 20:46:05
National Football League Strategiesr discretization of the time axis. That approach easily allows non-proportional hazard models, that are special cases of time-varying coefficients models. It is shown how the effective dimension of the general non-proportional hazards model can be controlled by either reduced rank regression methods of P-splines methodology.
Bronchial-Tubes
发表于 2025-3-29 00:48:02
https://doi.org/10.1007/978-90-481-3233-1A practical application with simulated data will be included where the accuracy of the proposed principal component logistic regression model will be evaluated starting from the estimated parameters and probabilities.
课程
发表于 2025-3-29 05:25:06
GBMs: GLMs with bilinear terms combined: exploratory analysis and explicit modeling. It turns out that the wide diversity of correlative methods can be considered as minor variations of a single model which is introduced in the standard framework set for generalized linear models. The paper presents this unifying approach and illustrates some its strengths.
高谈阔论
发表于 2025-3-29 07:52:32
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DAMN
发表于 2025-3-29 13:28:40
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的’
发表于 2025-3-29 17:33:21
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急急忙忙
发表于 2025-3-29 20:07:25
Non-proportional hazards models in survival analysisr discretization of the time axis. That approach easily allows non-proportional hazard models, that are special cases of time-varying coefficients models. It is shown how the effective dimension of the general non-proportional hazards model can be controlled by either reduced rank regression methods of P-splines methodology.
间接
发表于 2025-3-30 02:21:37
Principal component logistic regressionA practical application with simulated data will be included where the accuracy of the proposed principal component logistic regression model will be evaluated starting from the estimated parameters and probabilities.
调整
发表于 2025-3-30 04:47:36
National Environmental PoliciesThe nature of the new science of data mining is examined, drawing attention to the concepts and ideas it has inherited from areas such as statistics, machine learning, and database technology. Particular issues looked at include the emphasis on algorithms as well as models, and the fundamental importance of data quality to data mining exercises.