Results 31 to 40 of about 1,323,956 (316)
Testing Nonlinearity: Decision Rules for Selecting between Logistic and Exponential STAR Models [PDF]
, 2001 A new LM specification procedure to choose between Logistic and Exponential Smooth Transition Autoregressive (STAR) models is introduced. The new decision rule has better properties than those previously available in the literature when the model is ...
Escribano, Álvaro, Jordá, Óscar
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Medicina, 2022 Background and objectives: Acute cholecystitis causes acute abdominal pain and may necessitate emergency surgery or intensive antibiotic therapy and percutaneous drainage, depending on the patient’s condition. The symptoms of acute cholecystitis in older
Hirotaka Ikeda +2 more
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Frontiers in Plant Science, 2022 Late leaf spot (LLS), caused by Nothopassalora personata (Berk. & M.A Curt.), and groundnut rosette disease (GRD), [caused by groundnut rosette virus (GRV)], represent the most important biotic constraints to groundnut production in Uganda ...
Ivan Chapu +5 more
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Logistic regression analysis of populations of electrophysiological models to assess proarrythmic risk. [PDF]
, 2016 Population-based computational approaches have been developed in recent years and helped to gain insight into arrhythmia mechanisms, and intra- and inter-patient variability (e.g., in drug responses). Here, we illustrate the use of multivariable logistic
Grandi, Eleonora, Morotti, Stefano
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Analysis of influencing factors of dismal prognosis in severe tuberculous meningitis
Chinese Journal of Contemporary Neurology and Neurosurgery, 2023 Objective To investigate the influencing factors related to long ⁃ term prognosis in patients with severe tuberculous meningitis (TBM). Methods One hundred sixty⁃three patients with severe TBM admitted to Tianjin Haihe Hospital from June 2012 to December
LIU Chen⁃chao +6 more
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Fitting logistic IRT models: small wonder. [PDF]
, 1999 Sin ...
García-pérez, Miguel A.
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Uncertain logistic regression models
AIMS MathematicsLogistic regression is a generalized nonlinear regression analysis model and is often used for data mining, automatic disease diagnosis, economic prediction, and other fields.
Jinling Gao , Zengtai Gong
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Automatic covariate selection in logistic models for chest pain diagnosis: A new approach [PDF]
, 2008 A newly established method for optimizing logistic models via a minorization-majorization procedure is applied to the problem of diagnosing acute coronary syndromes (ACS).
Baxt +39 more
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Mathematical and Computer Modelling, 1988 Abstract A class of models indexed by two shape parameters is introduced, both to extend the scope of the standard logistic model to asymmetric probability curves and improve the fit in the noncentral probability regions. One-parameter subclasses can be used to examine symmetric or asymmetric deviations from the logistic model.
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Conditionally conjugate mean-field variational Bayes for logistic models
, 2018 Variational Bayes (VB) is a common strategy for approximate Bayesian inference, but simple methods are only available for specific classes of models including, in particular, representations having conditionally conjugate constructions within an ...
Durante, Daniele, Rigon, Tommaso
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