Bayesian density regression

By David B. Dunson, Natesh S. Pillai, Juhyun Park. 2007

280 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/0832510cf3b8c99dadbdd304e188d6cc557b9b0a

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Citations in the corpus

Additive Functional Regression for Densities as Responses (2020, background): “…usually considered in the general framework of nonparametric regression and has a rich literature (see, e.g., Roussas 1969; Bhattacharya and Gangopadhyay 1990; Koenker, Ng, and Portnoy 1994; Hall, Wolff, and Yao 1999; Hall and Müller 2003; Dunson, Pillai, and Park 2007; Li, Lin, and Racine 2013).”
The Nested Dirichlet Process (2008, methodology): “Dunson (2006) extended this idea to a time setting, and Dunson, Pillai, and Park (2007b) proposed a model for density regression using a kernel-weighted mixture of DPs defined at each value of the covariate.”
On the Support of MacEachern’s Dependent Dirichlet Processes and Extensions (2012, background): “We refer the reader to Müller et al. (1996), Dunson et al. (2007), Dunson and Park (2008), and Chung and Dunson (2009), and references therein, for other DP–based models for related probability distributions.”
Distance dependent Chinese restaurant processes (2009, unknown): “An alternative to the DDP formalism is the Bayesian density regression (BDR) model of Dunson et al. (2007).”
Smoothly mixing regressions (2007, methodology): “These approaches are complementary, and promising avenues for future research are to either increase the flexibility of p 1 in approaches like that of Dunson and Pillai (2004) and Griffin and Steel (2005), or to take up an explicitly nonparametric specification of the mixture components in SMR.”
The matrix stick-breaking process for flexible multi-task learning (2007, background): “We follow recent authors (Gri.n & Steel, 2006; Dunson et al., 2007a) by incorporating dependency through the stickbreaking weights.”
Bayesian Mode Regression (2012, methodology): “Similarly, conditional mode estimation is typically carried out by conditional density estimation via diﬀerent nonparametric methods (Gasser et al. (1998), Hall and Huang (2001) and Hall et al. (2001), Brunner (1992), Ho (2006), Dunson et al. (2007) among others).”
POSTERIOR CONSISTENCY IN CONDITIONAL DENSITY ESTIMATION BY COVARIATE DEPENDENT MIXTURES (2011, background): “, M. Villani, and R. Kohn (2010): “Flexible modeling of conditional distributions using smooth mixtures of asymmetric student t densities,” Journal of Statistical Planning and Inference, 140, 3638–3654.”
Simultaneous Linear Quantile Regression: A Semiparametric Bayesian Approach (2012, background): “This approach has recently gained attention in the Bayesian literature with the introduction of a number of non-parametric and semi-parametric prior distributions on conditional densities (Müller et al. 1996; MacEachern 1999, 2000; Griffin and Steel 2006; Dunson et al. 2007; Tokdar et al. 2010).”
Bayesian dynamic density estimation (2008, methodology): “…work has started to develop methods for dependent distributions, either by forming convex combinations of independent processes (Müller et al. 2004; Dunson et al. 2007b; Griffin and Steel 2007; Dunson 2006) or by introducing dependence in the elements of the stick-breaking representation of the…”
Stick-breaking autoregressive processes (2011, background): “…y, the infinite mixture model can be extended by allowing the kernel k to depend on x (Leslie et al., 2007; Chib and Greenberg, 2009), the mixing measure G to depend on x (De Iorio et al., 2004; Müller et al., 2004; Griffin and Steel, 2006; Dunson et al., 2007) or both (Geweke and Keane, 2007).”
Bayesian empirical likelihood for quantile regression (2012, methodology): “…development of Bayesian (conditional) density estimation us-ing mixture models enables nonparametric regression models on all quan-tiles simultaneously; see M¨uller, Erkanli and West (1996), M¨uller and Quin-tana ( 2004), Dunson, Pillai and Park (2007) and Chung and Dunson (2009), among others.”