Results 71 to 80 of about 25,321,415 (248)
Generalized Additive Models for Pair-Copula Constructions [PDF]
Journal of Computational And Graphical Statistics, 2016 Pair-copula constructions are flexible dependence models that use bivariate copulas as building blocks. In this article, we extend them with generalized additive models to allow covariates effects. Borrowing ideas from a traditionally univariate context,
Thibault Vatter, T. Nagler
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Partially Linear Functional Additive Models for Multivariate Functional Data
Journal of the American Statistical Association, 2018 We investigate a class of partially linear functional additive models (PLFAM) that predicts a scalar response by both parametric effects of a multivariate predictor and nonparametric effects of a multivariate functional predictor.
R. K. Wong, Yehua Li, Zhengyuan Zhu
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Boosting Nonlinear Additive Autoregressive Time Series [PDF]
, 2007 Within the last years several methods for the analysis of nonlinear autoregressive time series have been proposed. As in linear autoregressive models main problems are model identification, estimation and prediction.
Tutz, Gerhard, Shafik, Nivien
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Shape-constrained semiparametric additive stochastic volatility models
Statistical Theory and Related Fields, 2019 Nonparametric stochastic volatility models, although providing great flexibility for modelling the volatility equation, often fail to account for useful shape information.
Jiangyong Yin +3 more
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Generalized Additive Models: An Introduction with R
Journal of Statistical Software, 2006 s not available for ...
John Maindonald
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PLoS ONE, 2018 Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city—São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in turn,
O. Baquero +2 more
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Kolmogorov GAM Networks Are All You Need!
EntropyKolmogorov GAM (K-GAM) networks have been shown to be an efficient architecture for both training and inference. They are additive models with embeddings that are independent of the target function of interest.
Sarah Polson, Vadim Sokolov
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Additive models in censored regression [PDF]
Computational Statistics & Data Analysis, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jacobo de Uña-Álvarez +1 more
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BAMLSS: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)
Journal of Computational And Graphical Statistics, 2018 Bayesian analysis provides a convenient setting for the estimation of complex generalized additive regression models (GAMs). Since computational power has tremendously increased in the past decade, it is now possible to tackle complicated inferential ...
Nikolaus Umlauf, N. Klein, A. Zeileis
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Nonparametric estimation of an additive quantile regression model [PDF]
, 2004 This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of n^{-r/(2+10)} when ...
Joel L. Horowitz +5 more
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