نتایج جستجو برای: generalized additive model
تعداد نتایج: 2281171 فیلتر نتایج به سال:
Dynamic treatment regimes are fast becoming an important part of medicine, with the corresponding change in emphasis from treatment of the disease to treatment of the individual patient. Because of the limited number of trials to evaluate personally tailored treatment sequences, inferring optimal treatment regimes from observational data has increased importance. Q-learning is a popular method ...
Many risk management strategies, including hedging the price risk using forward or futures contracts require accurate forecasts of basis, i.e., spot price minus the futures price. Recent literature in this area has applied nonlinear time-series models, which are refinements of the linear autoregressive models that allow the parameters to transition from one regime to another. These parametric n...
This paper discusses a nonparametric regression model that naturally generalizes neural network models. The model is based on a finite number of one-dimensional transformations and can be estimated with a one-dimensional rate of convergence. The model contains the generalized additive model with unknown link function as a special case. For this case, it is shown that the additive components and...
since esp received universal attention to smooth the path for academic studies and productions, a great deal of research and studies have been directed towards this area. swales’ (1990) model of ra introduction move analysis has served a pioneering role of guiding many relevant studies and has proven to be productive in terms of helpful guidelines that are the outcome of voluminous productions ...
OBJECTIVE To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. DESIGN Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010. PATIENTS 50,318 adult patients undergoing major surgery. MEASUREMENTS We evaluated the performance of logistic regression, generalized additive models, naïve Bayes...
Gaussian process models are flexible, Bayesian non-parametric approaches to regression. Properties of multivariate Gaussians mean that they can be combined linearly in the manner of additive models and via a link function (like in generalized linear models) to handle non-Gaussian data. However, the link function formalism is restrictive, link functions are always invertible and must convert a p...
Generalized additive models are useful in finding predictor-response relationships in many kinds of data without using a specific model. They combine the ability to explore many nonparametric relationships simultaneously with the distributional flexibility of generalized linear models. The approach often brings to light nonlinear dependency structures in your data. This paper discusses an examp...
Using the Hyers-Ulam-Rassias stability method, weinvestigate isomorphisms in Banach algebras and derivations onBanach algebras associated with the following generalized additivefunctional inequalitybegin{eqnarray}|af(x)+bf(y)+cf(z)| le |f(alpha x+ beta y+gamma z)| .end{eqnarray}Moreover, we prove the Hyers-Ulam-Rassias stability of homomorphismsin Banach algebras and of derivations on Banach ...
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