Additive models
Target setting in additive models with preferences and interval data
... on additive models with interval data.An additive model can be converted to a multi-objective linear problem if information about preferences of the consumption of inputs and the production of ...
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Markov switching generalized additive models
... i.e. models for time series regression analyses where the functional relationship between covariates and response is subject to regime switching controlled by an unobservable Markov ...an additive structure ...
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Bivariate copula additive models for location, scale and shape
... generalized additive models for location, scale and shape (GAMLSS), the response dis- tribution is not restricted to belong to the exponential family and all the model’s parameters can be made dependent on ...
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Model Detection for Additive Models with Longitudinal Data
... of additive models with longitudinal data has also been considered by some ...of additive model with longitudinal ...nonparametric additive time-varying regression model for longitudinal ...
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Combining Speech Retrieval Results with Generalized Additive Models
... System combination has a long history in infor- mation retrieval. Most often, the goal is to combine results from systems that search different content (“collection fusion”) or to combine results from dif- ferent systems ...
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Fast Automatic Smoothing for Generalized Additive Models
... The two learning strategies for generalized additive models are performance iteration (Gu, 1992) and outer iteration (O’Sullivan et al., 1986), and optimize a criterion for the smooth- ing hyper-parameters ...
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Projecting UK mortality by using Bayesian generalized additive models
... The future level of mortality is of vital interest to policy makers and private insurers alike, as lower mortality results in greater expenditure on pension payments and higher social care spending. Individuals are ...
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Use of generalised additive models to categorise continuous variables in clinical prediction
... clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine the relationship between the continuous predictor and the ...An additive logistic ...
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Learning additive models online with fast evaluating kernels
... Abstract. We develop three new techniques to build on the recent ad- vances in online learning with kernels. First, we show that an exponential speed-up in prediction time per trial is possible for such algorithms as the ...
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A Generative Joint, Additive, Sequential Model of Topics and Speech Acts in Patient Doctor Communication
... Sparse Additive Generative (SAGE) model (Eisenstein et ...developed additive models (Paul and Dredze, 2012; Paul et ...Joint, Additive, Sequential model as ...
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Quantitative modeling of the neural representation of adjective noun phrases to account for fMRI activation
... an additive model, a multiplicative model, a weighted additive model, a Kintsch (2001) model, and a model which combines multiplicative and additive models can be used to model human behavior ...
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Exploring the density dependent structure of blowfly populations by nonparametric additive modeling
... metric models have the benefits of easy interpretation and a well-developed inferential ...nonparametric models are potentially very use- ...such models allow the data to ‘‘speak for them- ...
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Contributions to Statistical Methods for Functional Data Analysis and Generalized Additive Model.
... continuously additive models (CAM) proposed by Müller et ...regression models coupling functional predictors and scalar ...frequency-additive models that had been proposed before ...
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Incorporating shape constraints in generalized additive modelling of the height-diameter relationship for Norway spruce
... (h-d) models that predict tree height from dbh, age and other covariates are ...generalized additive models as an extension of existing h-d model ...the models and to enable predictions under ...
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Modeling diarrhea disease in children less than 5 years old: a GAM and GLM approach
... A unique aspect of generalized additive models is the non-parametric functions of the predictor variables. Specifically, instead of some kind of simple or complex parametric functions, Hastie and Tibshirani ...
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Weighted Additive DEA Models Associated with Dataset Standardization Techniques
... weighted additive data envelopment analysis (WADD) models associated with dataset standardization ...WADD models seems random and confused for users, the study investigates the correspondence ...
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Bayesian Inference for High Dimensional Models: Convergence Properties and Computational Issues.
... in additive models, to the best of our knowledge, there is no Bayesian variable selection method for GAPLMs available in the ...different models can be extremely unre- liable when the number of ...
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Risk of cancer in the vicinity of municipal solid waste incinerators: importance of using a flexible modelling strategy
... To assess the association between the risk of cancer and past exposure to MSWIs, a Poisson regression analysis was performed taking into account the confounding factors. In particular, the study of the dose-response ...
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Additive manufacturing and business models: Current knowledge and missing perspectives
... through additive manufacturing: rapid prototyping and innovations, for instance (Berman, 2012; Maric et ...link additive manu- facturing to business performance or business impact more generally (Niaki ...
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Generalised additive dependency inflated models including aggregated covariates
... The relevant age-period-cohort density version of GADIMAC is used to fore- cast the future asbestos-related deaths in the United Kingdom in the application in Section 4.3. Asbestos mortality data is characterized by its ...
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