Claudio Fuentes
Oregon State University
StatisticsBayesian probabilityMachine learningMathematical optimizationAkaike information criterionGompertz functionEconometricsArtificial intelligencePrior probabilityChemistryBayes' theoremContext (language use)Applied mathematicsPopulationMathematicsComputer sciencePascalizationBiologyModel selectionEstimation
48Publications
11H-index
200Citations
Publications 48
Newest
#1Arpan Biswas (OSU: Oregon State University)H-Index: 3
#2Claudio Fuentes (OSU: Oregon State University)H-Index: 11
Last. Christopher Hoyle (OSU: Oregon State University)H-Index: 14
view all 3 authors...
Source
#1Michael S. Blouin (OSU: Oregon State University)H-Index: 54
#2Madeleine C Wrey (Fordham University)
Last. Claudio Fuentes (OSU: Oregon State University)H-Index: 11
view all 6 authors...
Salmonid fish raised in hatcheries often have lower fitness (number of returning adult offspring) than wild fish when both spawn in the wild. Body size at release from hatcheries is positively correlated with survival at sea. So one explanation for reduced fitness is that hatcheries inadvertently select for trait values that enhance growth rate under the unnatural environment of a hatchery, but that are maladaptive in the wild environment. A simple prediction of this hypothesis is that juveniles...
Source
#1Jeremy Gaskins (University of Louisville)H-Index: 7
#2Claudio Fuentes (OSU: Oregon State University)H-Index: 11
Last. Rolando de la Cruz (UAI: Adolfo Ibáñez University)
view all 3 authors...
Across several medical fields, developing an approach for disease classification is an important challenge. The usual procedure is to fit a model for the longitudinal response in the healthy population, a different model for the longitudinal response in the diseased population, and then apply Bayes' theorem to obtain disease probabilities given the responses. Unfortunately, when substantial heterogeneity exists within each population, this type of Bayes classification may perform poorly. In this...
Source
#1Ben J. Brintz (UofU: University of Utah)H-Index: 2
#2Lisa Madsen (OSU: Oregon State University)H-Index: 12
Last. Claudio Fuentes (OSU: Oregon State University)H-Index: 11
view all 3 authors...
This article develops an approximate N-mixture model for infectious disease counts that accounts for under-reporting as well as spatial dependence induced by person-to-person spread of disease. We ...
Source
#1Michael Dumelle (OSU: Oregon State University)H-Index: 1
#2Jay M. Ver Hoef (NMFS: National Marine Fisheries Service)H-Index: 49
Last. Alix I. Gitelman (OSU: Oregon State University)H-Index: 10
view all 4 authors...
Abstract To properly characterize a spatio-temporal random process, it is necessary to understand the process’ dependence structure. It is common to describe this dependence using a single random error having a complicated covariance. Instead of using the single random error approach, we describe spatio-temporal random processes using linear mixed models having several random errors; each random error describes a specific quality of the covariance. This linear mixed model formulation is general,...
Source
#1Yong Chen (OSU: Oregon State University)H-Index: 51
#2N. L. GibsonH-Index: 10
view all 10 authors...
Abstract Real options theory is applied to quantify the value of operational flexibility intrinsic to the hydropower generation capacity from the perspective of US federal power marketing administrations. The option value in this model arises from the tension between the increase in current sales revenue and the increase in the exposure of future power shortages. Using Bonneville Power Administration as an example, we apply the proposed valuation framework, analyze the optimal management policy ...
Source
#1Giancarlo M. Correa (OSU: Oregon State University)
#2Carey R McGilliard (NOAA: National Oceanic and Atmospheric Administration)
Last. Claudio Fuentes (OSU: Oregon State University)H-Index: 11
view all 4 authors...
Source
#2Rolando De la CruzH-Index: 8
Last. Héctor W. GómezH-Index: 19
view all 4 authors...
We introduce a new class of distributions called the epsilon–positive family, which can be viewed as generalization of the distributions with positive support. The construction of the epsilon–positive family is motivated by the ideas behind the generation of skew distributions using symmetric kernels. This new class of distributions has as special cases the exponential, Weibull, log–normal, log–logistic and gamma distributions, and it provides an alternative for analyzing reliability and surviva...
1 CitationsSource
#2J. David Porter (OSU: Oregon State University)H-Index: 11
Last. Claudio Fuentes (OSU: Oregon State University)H-Index: 11
view all 3 authors...
Transit agencies have experienced dramatic changes in service and ridership because of the COVID-19 pandemic. As communities transition to a new normal, strategic measures are needed to support con...
Source
Estimating bird and bat mortality at wind facilities typically involves searching for carcasses on the ground near turbines. Some fraction of carcasses inevitably lie outside the search plots, and accurate mortality estimation requires accounting for those carcasses using models to extrapolate from searched to unsearched areas. Such models should account for variation in carcass density with distance, and ideally also for variation with direction (anisotropy). We compare five methods of accounti...
Source