Zobrazeno 1 - 10
of 383
pro vyhledávání: '"RODRÍGUEZ, ABEL"'
Autor:
Porwal, Anupreet, Rodriguez, Abel
This paper introduces Dirichlet process mixtures of block $g$ priors for model selection and prediction in linear models. These priors are extensions of traditional mixtures of $g$ priors that allow for differential shrinkage for various (data-select
Externí odkaz:
http://arxiv.org/abs/2411.00471
In this paper, we introduce a hierarchical extension of the stochastic blockmodel to identify multilevel community structures in networks. We also present a Markov chain Monte Carlo (MCMC) and a variational Bayes algorithm to fit the model and obtain
Externí odkaz:
http://arxiv.org/abs/2410.02929
Stochastic variational Bayes algorithms have become very popular in the machine learning literature, particularly in the context of nonparametric Bayesian inference. These algorithms replace the true but intractable posterior distribution with the be
Externí odkaz:
http://arxiv.org/abs/2410.02649
Autor:
Lei, Rayleigh, Rodriguez, Abel
Discrete choice models with non-monotonic response functions are important in many areas of application, especially political sciences and marketing. This paper describes a novel unfolding model for binary data that allows for heavy-tailed shocks to
Externí odkaz:
http://arxiv.org/abs/2407.06395
Autor:
Lipman, Erin, Rodriguez, Abel
The most common approach to implementing data analysis pipelines involves obtaining point estimates from the upstream modules and then treating these as known quantities when working with the downstream ones. This approach is straightforward, but it
Externí odkaz:
http://arxiv.org/abs/2402.04461
Spatial voting models of legislators' preferences are used in political science to test theories about their voting behavior. These models posit that legislators' ideologies as well as the ideologies reflected in votes for and against a bill or measu
Externí odkaz:
http://arxiv.org/abs/2312.15049
Autor:
Jiang, Alex Ziyu, Rodríguez, Abel
Multivariate Hawkes Processes (MHPs) are a class of point processes that can account for complex temporal dynamics among event sequences. In this work, we study the accuracy and computational efficiency of three classes of algorithms which, while wid
Externí odkaz:
http://arxiv.org/abs/2309.14658
Autor:
Lei, Rayleigh, Rodriguez, Abel
We develop a new class of spatial voting models for binary preference data that can accommodate both monotonic and non-monotonic response functions, and are more flexible than alternative "unfolding" models previously introduced in the literature. We
Externí odkaz:
http://arxiv.org/abs/2308.16288
Autor:
Lei, Rayleigh, Rodriguez, Abel
Latent factor models are widely used in the social and behavioral science as scaling tools to map discrete multivariate outcomes into low dimensional, continuous scales. In political science, dynamic versions of classical factor models have been wide
Externí odkaz:
http://arxiv.org/abs/2305.19380
Autor:
Porwal, Anupreet, Rodriguez, Abel
Power-expected-posterior (PEP) methodology, which borrows ideas from the literature on power priors, expected-posterior priors and unit information priors, provides a systematic way to construct objective priors. The basic idea is to use imaginary tr
Externí odkaz:
http://arxiv.org/abs/2112.02524