Prior Design for Dependent Dirichlet Processes: An Application to Marathon Modeling. [PDF]
PLoS ONE, 2016 This paper presents a novel application of Bayesian nonparametrics (BNP) for marathon data modeling. We make use of two well-known BNP priors, the single-p dependent Dirichlet process and the hierarchical Dirichlet process, in order to address two ...
Melanie F Pradier +2 more
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Hawkes process model with a time-dependent background rate and its application to high-frequency financial data [PDF]
Physical Review E, 2017 11 pages, 7 ...
Takahiro Omi +2 more
semanticscholar +8 more sources
State-dependent Hawkes processes and their application to limit order book modelling [PDF]
Quantitative Finance, 2021 We study statistical aspects of state-dependent Hawkes processes, which are an extension of Hawkes processes where a self- and cross-exciting counting process and a state process are fully coupled, interacting with each other. The excitation kernel of the counting process depends on the state process that, reciprocally, switches state when there is an ...
Maxime Morariu-Patrichi +1 more
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Cutting Edge PBPK Models and Analyses: Providing the Basis for Future Modeling Efforts and Bridges to Emerging Toxicology Paradigms [PDF]
Journal of Toxicology, 2012 Physiologically based Pharmacokinetic (PBPK) models are used for predictions of internal or target dose from environmental and pharmacologic chemical exposures.
Jane C. Caldwell +2 more
doaj +2 more sources
A decision dependent stochastic process model for repairable systems with applications
Operations Research Perspectives, 2015 AbstractManagement decisions regarding maintenance protocols critically hinge on the underlying probability distribution of the time between failures in most repairable systems. Replacement of the system with a new one resets the system age to zero, whereas a repair does not alter the system age but may shift the parameters of the failure-time ...
Paul F. Zantek +3 more
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Coupled physical/biogeochemical modeling including O 2 -dependent processes in the Eastern Boundary Upwelling Systems: application in the Benguela [PDF]
Biogeosciences, 2013 Abstract. The Eastern Boundary Upwelling Systems (EBUS) contribute to one fifth of the global catches in the ocean. Often associated with Oxygen Minimum Zones (OMZs), EBUS represent key regions for the oceanic nitrogen (N) cycle. Important bioavailable N loss due to denitrification and anammox processes as well as greenhouse gas emissions (e.g, N2O ...
Elodie Gutknecht +11 more
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Modeling dose-dependent neural processing responses using mixed effects spline models: With application to a PET study of ethanol [PDF]
NeuroImage, 2007 For functional neuroimaging studies that involve experimental stimuli measuring dose levels, e.g. of an anesthetic agent, typical statistical techniques include correlation analysis, analysis of variance or polynomial regression models. These standard approaches have limitations: correlation analysis only provides a crude estimate of the linear ...
Ying Guo, F. DuBois Bowman
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Application of EC, ECE, and ECE-ECE Models with Potential Dependent Transfer Coefficient to Selected Electrode Processes [PDF]
Journal of The Electrochemical Society, 2007 The electrochemical-chemical (EC), electrochemical, chemical, electrochemical (ECE), and electrochemical, chemical, electrochemical-electrochemical, chemical, electrochemical (ECE-ECE) models with and without an included α variability were applied to the reduction of 2-methyl-2-nitropropane, benzenesulfonyl fluoride, and p-toluenesulfonyl fluoride. The
Przemysław T. Sanecki, Piotr M. Skitał
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A Bayesian Vector Autoregressive Model with Nonignorable Missingness in Dependent Variables and Covariates: Development, Evaluation, and Application to Family Processes [PDF]
Structural Equation Modeling: A Multidisciplinary Journal, 2019 Intensive longitudinal designs involving repeated assessments of constructs often face the problems of nonignorable attrition and selected omission of responses on particular occasions. However, time series models, such as vector autoregressive (VAR) models, are often fit to these data without consideration of nonignorable missingness.
Linying Ji +5 more
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Nonlinear Models with Strongly Dependent Processes and Applications to Forward Premia and Real Exchange Rates [PDF]
, 2006 This paper considers estimation and inference in some general non linear time series models which are embedded in a strongly dependent, long memory process. Some new results are provided on the properties of a time domain MLE for these models. The paper also includes a detailed simulation study which compares the time domain MLE with a two step ...
Richard T. Baillie, George Kapetanios
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