References in zbMATH (referenced in 248 articles , 1 standard article )

Showing results 1 to 20 of 248.
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  1. Cantarella, Giulio E.; Fiori, Chiara: Day-to-day dynamic multivehicle assignment: deterministic process models (2021)
  2. Rattihalli, R. N.; Patil, S. B.: Data dependent asymmetric kernels for estimating the density function (2021)
  3. Tokdar, Surya T.; Martin, Ryan: Bayesian test of normality versus a Dirichlet process mixture alternative (2021)
  4. Bertin, Karine; Klutchnikoff, Nicolas; Léon, Jose R.; Prieur, Clémentine: Adaptive density estimation on bounded domains under mixing conditions (2020)
  5. Borrajo, M. I.; González-Manteiga, W.; Martínez-Miranda, M. D.: Bootstrapping kernel intensity estimation for inhomogeneous point processes with spatial covariates (2020)
  6. Cronie, Ottmar; Moradi, Mehdi; Mateu, Jorge: Inhomogeneous higher-order summary statistics for point processes on linear networks (2020)
  7. Flagg, Kenneth A.; Hoegh, Andrew; Borkowski, John J.: Modeling partially surveyed point process data: inferring spatial point intensity of geomagnetic anomalies (2020)
  8. Levin, Michael W.; Duell, Melissa; Waller, S. Travis: Arrival time reliability in strategic user equilibrium (2020)
  9. McSwiggan, Greg; Baddeley, Adrian; Nair, Gopalan: Estimation of relative risk for events on a linear network (2020)
  10. Pitombeira-Neto, Anselmo Ramalho; Loureiro, Carlos Felipe Grangeiro; Carvalho, Luis Eduardo: A dynamic hierarchical Bayesian model for the estimation of day-to-day origin-destination flows in transportation networks (2020)
  11. Qiao, Wanli: Asymptotics and optimal bandwidth for nonparametric estimation of density level sets (2020)
  12. Soize, Christian; Ghanem, Roger G.; Desceliers, Christophe: Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset (2020)
  13. Sun, Chao; Chang, Yulin; Luan, Xin; Tu, Qiang; Tang, Wenyun: Origin-destination demand reconstruction using observed travel time under congested network (2020)
  14. Sun, Yiguo: The LLN and CLT for U-statistics under cross-sectional dependence (2020)
  15. Uppala, Medha; Handcock, Mark S.: Modeling wildfire ignition origins in southern California using linear network point processes (2020)
  16. West, Mike: Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions (2020)
  17. Xie, Dong-Fan; Zhao, Xiao-Mei: Traffic dynamics and mode Choice’s delay effect under traffic restriction in two-mode networks (2020)
  18. Abareshi, Maryam; Zaferanieh, Mehdi; Safi, Mohammad Reza: Origin-destination matrix estimation problem in a Markov chain approach (2019)
  19. Adam E. Lanman; Bryna J. Hazelton; Daniel C. Jacobs; Matthew J. Kolopanis; Jonathan C. Pober; James E. Aguirre; Nithyanandan Thyagarajan: pyuvsim: A comprehensive simulation package for radio interferometers in python (2019) not zbMATH
  20. Béranger, B.; Duong, T.; Perkins-Kirkpatrick, S. E.; Sisson, S. A.: Tail density estimation for exploratory data analysis using kernel methods (2019)

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