Multivariate hidden Markov regression models: random covariates and heavy-tailed distributions
Sign Up to like & getrecommendations! Published in 2019 at "Statistical Papers"
DOI: 10.1007/s00362-019-01146-3
Abstract: Despite recent methodological advances in hidden Markov regression models and a rapid increase in their application in a wide range of empirical settings, complex clustering-based research questions that include the contribution of the covariates set… read more here.
Keywords: hidden markov; regression; models random; regression models ... See more keywords
Optimal Stopping Problems in Lévy Models with Random Observations
Sign Up to like & getrecommendations! Published in 2018 at "Acta Applicandae Mathematicae"
DOI: 10.1007/s10440-018-0212-z
Abstract: In the standard optimal stopping problems, actions are artificially restricted to the moments of observations of costs or benefits. In the standard experimentation and learning models based on two-armed Poisson bandits, it is possible to… read more here.
Keywords: random observations; models random; optimal stopping; stopping problems ... See more keywords
Multivariate sensitivity analysis for dynamic models with both random and random process inputs
Sign Up to like & getrecommendations! Published in 2020 at "Applied Mathematical Modelling"
DOI: 10.1016/j.apm.2019.12.019
Abstract: Abstract Dynamic models with both random and random process inputs are frequently used in engineering. However, sensitivity analysis (SA) for such models is still a challenging problem. This paper, therefore, proposes a new multivariate SA… read more here.
Keywords: process inputs; dynamic models; models random; random process ... See more keywords
A model-based imputation procedure for multilevel regression models with random coefficients, interaction effects, and nonlinear terms.
Sign Up to like & getrecommendations! Published in 2019 at "Psychological methods"
DOI: 10.1037/met0000228
Abstract: Despite the broad appeal of missing data handling approaches that assume a missing at random (MAR) mechanism (e.g., multiple imputation and maximum likelihood estimation), some very common analysis models in the behavioral science literature are… read more here.
Keywords: model based; imputation; models random; regression models ... See more keywords
Asymptotic properties of approximate maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with random effects
Sign Up to like & getrecommendations! Published in 2019 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2018.1440311
Abstract: ABSTRACT Quasi-likelihood nonlinear models with random effects (QLNMWRE) include generalized linear models with random effects and quasi-likelihood nonlinear models as special cases. In this paper, some regularity conditions analogous to those given by Breslow and… read more here.
Keywords: nonlinear models; models random; likelihood nonlinear; random effects ... See more keywords
A class of models for random hypergraphs
Sign Up to like & getrecommendations! Published in 2022 at "Physical review. E"
DOI: 10.1103/physreve.106.064310
Abstract: Despite the recently exhibited importance of higher-order interactions for various processes, few flexible (null) models are available. In particular, most studies on hypergraphs focus on a small set of theoretical models. Here, we introduce a… read more here.
Keywords: models random; random hypergraphs; class models;
Uncertainty quantification for ecological models with random parameters.
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DOI: 10.1111/ele.14095
Abstract: There is often considerable uncertainty in parameters in ecological models. This uncertainty can be incorporated into models by treating parameters as random variables with distributions, rather than fixed quantities. Recent advances in uncertainty quantification methods,… read more here.
Keywords: random parameters; ecological models; uncertainty; models random ... See more keywords